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Forex Trading in Kenya.
Someone posted on here a few days ago asking about forex and forex trading in Kenya, I have gone through the responses and clearly, most people don’t have an idea. It is 3am in the morning and am in a good mood so let me make this post. This will be a comprehensive and lengthy post so grab a pen and paper and sit down. We’ll be here a while. FIRST OF ALL, who am I..? I am a forex trader, in Nairobi, Kenya..i have been actively involved in forex since I found out about it in Feb 2016 when I somehow ended up in a wealth creation seminar (lol) in pride inn Westlands, the one close to Mpaka Rd. Luckily for me, it was not one of those AIM global meetings or I’d be on Facebook selling God knows what those guys sell. I did not take it seriously till August of the same year and I have been active ever since. I don’t teach, mentor or sell a course or signals, I trade my own money. I am also posting from a throwaway account because I don’t want KRA on my ass. What the fuck is forex and forex trading. In simple plain English, forex is like the stock market but for currencies. Stock Market = Shares, forex = currencies. If you want more in-depth explanation, google is your friend. These currencies are pegged on specific countries, united states- dollar, UK- pound, euro zone- euro, Switzerland- Swiss franc, Kenya- Kenya shilling.. you get the point. Now, there are specific events and happenings between these economies that affect the movement and values of the currencies, driving their value (purchasing power up and down). Forex trading exploits these movements to make money. When the value is going up, we buy and vice versa (down –sell) Is forex trading illegal in Kenya? Is it a scam? Illegal, no. scam, no. All the banks in the world do it (KCB made about 4 billion from trading forex in 2019) Have there been scams involving forex in Kenya? Yes. Here is one that happened recently. This one is the most infamous one yet. Best believe that this is not the end of these type of scams because the stupidity, greed and gullibility of human beings is unfathomable. However, by the end of this post, I hope you won’t fall for such silliness. What next how do I make it work..? Am glad you asked. Generally, there are two ways to go about it. One, you teach yourself. This is the equivalent of stealing our dad’s car and hoping that the pedal you hit is the brake and not the accelerator. It is the route I took, it is the most rewarding and a huge ego boost when you finally make it on your own. Typically, this involves scouring the internet for hours upon hours going down rabbit holes, thinking you have made it telling all your friends how you will be a millionaire then losing all your money. Some people do not have the stomach for that. The second route is more practical, structured and smarter. First Learn the basics. There is a free online forex course at www.babypips.com/learn/forex this is merely an introductory course. Basically it is learning the parts of a car before they let you inside the car. Second, start building your strategy. By the time you are done with the babypips, you will have a feel of what the forex market is, what interests you, etc. Tip..Babypips has a lot of garbage. It is good for introductory purposes but not good for much else, pick whatever stick to you or jumps at you the first time. Nonsense like indicators should be ignored. The next step is now the most important. Developing the skill and building your strategy. As a beginner, you want to exhaust your naivety before jumping into the more advanced stuff. Eg can you identify a trend, what is a pair, what is position sizing, what is metatrader 4 and how to operate it, what news is good for a currency, when can I trade, what are the different trading sessions, what is technical analysis, what is market sentiment, what are bullish conditions what is emotion management, how does my psychology affect my trading (more on this later) an I a swing, scalper or day trader etc Mentors and forex courses.. you have probably seen people advertising how they can teach and mentor you on how to trade forex and charging so much money for it. Somehow it seems that these people are focused on the teaching than the trading. Weird, right..? Truth is trading is hard, teaching not quite. A common saying in the industry is “Those who can’t trade, teach” you want to avoid all these gurus on Facebook and Instagram, some are legit but most are not. Sifting the wheat from the chaff is hard but I did that for you. The info is available online on YouTube, telegram channels etc. am not saying not to spend money on a course, if you find a mentor whose style resonates with you and the course is reasonably priced, please, go ahead and buy..it will cut your learning curve in half. People are different. What worked for me might not work for you. Here are some nice YouTube channels to watch. These guys are legit..
After a short period of time, you will be able to sniff out bs teachers with relative ease. You will also discover some of your own and expand the list. Two tips, start with the oldest videos first and whichever of these resonates with you, stick with till the wheels fall off. How long will it take until things start making sense Give yourself time to grow and learn. This is all new to you and you are allowed to make mistakes, to fail and discover yourself. Realistically, depending on the effort you put in, you will not start seeing results until after 6 months. Could take longeshorter so there is no guarantee. Social media, Mentality, Psychology and Books Online, forex trading might not have the best reputation online because it takes hard work and scammers and gurus give it a bad name. However, try to not get sucked into the Instagram trader lifestyle as it is nowhere close to what the reality is. You will not make millions tomorrow or the day after, you might never even make it in this market. But that is the reality of life. Nothing is promised, nothing is guaranteed. Your mentality, beliefs and ego will be challenged in this market. You will learn things that will make you blood boil, you will ask yourself daily, how is this possible, why don’t they teach this in school..bla bla bla..it will be hard but growth is painful, if it wasn’t we’d all be billionaires. Take a break, take a walk, drink a glass of whatever you like or roll one..detox. Chill with your girl (or man) Gradually you will develop mental toughness that will set you up for life. Personally, I sorta ditched religion and picked up stoicism. Whatever works for you. Psychology, this is unfortunately one of the most neglected aspects of your personal development in this journey. Do you believe in yourself? Can you stand by your convictions when everyone is against you? Can you get up every day uncertain of the future? There will be moments where you will question yourself, am I even doing the right thing? the right way? It is normal and essential for your growth. People who played competitive sports have a natural advantage here. Remember the game is first won in your head then on the pitch. Books: ironically, books that helped me the most were the mindset books, Think and grow rich, trading for a living, 4 hour work week, the monk who sold his Ferrari..just google mindset and psychology books, most trading books are garbage. Watch and listen to people who have made it in the investing business. Ray Dalio, warren, Bill Ackman and Carl Icahn. This is turning out to be lengthier than I anticipated so I’ll try to be brief for the remaining parts. Brokers You will need to open up an account with a broker. Get a broker who is regulated. Australian ones (IC Market and Pepperstone) are both legit, reliable and regulated. Do your research. I’d avoid local ones because I’ve heard stories of wide spreads and liquidity problems. International brokers have never failed me. There are plenty brokers, there is no one size fits all recommendation. If it ain’t broke..don’t fix it. Money transfer. All brokers accept wire transfers, you might need to call your bank to authorize that, avoid Equity bank. Stanchart and Stanbic are alright. Large withdrawals $10k+ you will have to call them prior. Get Skrill and Neteller if you don’t like banks like me, set up a Bitcoin wallet for faster withdrawals, (Payoneer and Paypal are accepted by some brokers, just check with them.) How much money can I make..? I hate this question because people have perceived ceilings of income in their minds, eg 1 million ksh is too much to make per month or 10,000ksh is too little. Instead, work backwards. What % return did I make this month/ on this trade. Safaricom made 19.5% last year, if you make 20% you have outperformed them. If you reach of consistency where you can make x% per month on whatever money you have, then there are no limits to how much you can make. How much money do I need to start with..? Zero. You have all the resources above, go forth. There are brokers who provide free bonuses and withdraw-able profits. However, to make a fulltime income you will need some serious cash. Generally, 50,000 kes. You can start lower or higher but if you need say 20k to live comfortably and that is a 10% return per month, then you can do the math on how big your account should be. Of course things like compound interest come into play but that is dependent on your skill level. I have seen people do spectacular things with very little funds. Taxes..? Talk to a lawyer or an accountant. I am neither. Family? Friends? Unfortunately, people will not understand why you spend hundreds of hours watching strangers on the internet so it is best to keep it from them. Eventually you will make it work and they will come to your corner talking about how they always knew you’d make it. The journey will be lonely, make some trading buddies along the way. You’d be surprised at how easy it is when people are united by their circumstances (and stupidity) I have guys who are my bros from South Africa and Lebanon who I have never met but we came up together and are now homies. Join forums, ask questions and grow. That is the only way to learn. Ideally, a group of 5-10 friends committed to learning and growth is the best model. Pushing each other to grow and discovering together. Forex is real and you can do amazing things with it. It is not a get rich quick scheme. If you want a quick guaranteed income, get a job. And now it is 5am, fuck. This is oversimplified and leaves out many many aspects. Happy to answer any questions.
Disclaimer: None of this is financial advice. I have no idea what I'm doing. Please do your own research or you will certainly lose money. I'm not a statistician, data scientist, well-seasoned trader, or anything else that would qualify me to make statements such as the below with any weight behind them. Take them for the incoherent ramblings that they are. TL;DR at the bottom for those not interested in the details. This is a bit of a novel, sorry about that. It was mostly for getting my own thoughts organized, but if even one person reads the whole thing I will feel incredibly accomplished.
For those of you not familiar, please see the various threads on this trading system here. I can't take credit for this system, all glory goes to ParallaxFX! I wanted to see how effective this system was at H1 for a couple of reasons: 1) My current broker is TD Ameritrade - their Forex minimum is a mini lot, and I don't feel comfortable enough yet with the risk to trade mini lots on the higher timeframes(i.e. wider pip swings) that ParallaxFX's system uses, so I wanted to see if I could scale it down. 2) I'm fairly impatient, so I don't like to wait days and days with my capital tied up just to see if a trade is going to win or lose. This does mean it requires more active attention since you are checking for setups once an hour instead of once a day or every 4-6 hours, but the upside is that you trade more often this way so you end up winning or losing faster and moving onto the next trade. Spread does eat more of the trade this way, but I'll cover this in my data below - it ends up not being a problem. I looked at data from 6/11 to 7/3 on all pairs with a reasonable spread(pairs listed at bottom above the TL;DR). So this represents about 3-4 weeks' worth of trading. I used mark(mid) price charts. Spreadsheet link is below for anyone that's interested.
I'm pretty much using ParallaxFX's system textbook, but since there are a few options in his writeups, I'll include all the discretionary points here:
I'm using the stop entry version - so I wait for the price to trade beyond the confirmation candle(in the direction of my trade) before entering. I don't have any data to support this decision, but I've always preferred this method over retracement-limit entries. Maybe I just like the feeling of a higher winrate even though there can be greater R:R using a limit entry. Variety is the spice of life.
I put my stop loss right at the opposite edge of the confirmation candle. NOT at the edge of the 2-candle pattern that makes up the system. I'll get into this more below - not enough trades are saved to justify the wider stops. (Wider stop means less $ per pip won, assuming you still only risk 1%).
All my profit/loss statistics are based on a 1% risk per trade. Because 1 is real easy to multiply.
There are definitely some questionable trades in here, but I tried to make it as mechanical as possible for evaluation purposes. They do fit the definitions of the system, which is why I included them. You could probably improve the winrate by being more discretionary about your trades by looking at support/resistance or other techniques.
I didn't use MBB much for either entering trades, or as support/resistance indicators. Again, trying to be pretty mechanical here just for data collection purposes. Plus, we all make bad trading decisions now and then, so let's call it even.
As stated in the title, this is for H1 only. These results may very well not play out for other time frames - who knows, it may not even work on H1 starting this Monday. Forex is an unpredictable place.
I collected data to show efficacy of taking profit at three different levels: -61.8%, -100% and -161.8% fib levels described in the system using the passive trade management method(set it and forget it). I'll have more below about moving up stops and taking off portions of a position.
And now for the fun. Results!
Total Trades: 241
TP at -61.8%: 177 out of 241: 73.44%
TP at -100%: 156 out of 241: 64.73%
TP at -161.8%: 121 out of 241: 50.20%
Adjusted Proft % (takes spread into account):
TP at -61.8%: 5.22%
TP at -100%: 23.55%
TP at -161.8%: 29.14%
As you can see, a higher target ended up with higher profit despite a much lower winrate. This is partially just how things work out with profit targets in general, but there's an additional point to consider in our case: the spread. Since we are trading on a lower timeframe, there is less overall price movement and thus the spread takes up a much larger percentage of the trade than it would if you were trading H4, Daily or Weekly charts. You can see exactly how much it accounts for each trade in my spreadsheet if you're interested. TDA does not have the best spreads, so you could probably improve these results with another broker. EDIT: I grabbed typical spreads from other brokers, and turns out while TDA is pretty competitive on majors, their minors/crosses are awful! IG beats them by 20-40% and Oanda beats them 30-60%! Using IG spreads for calculations increased profits considerably (another 5% on top) and Oanda spreads increased profits massively (another 15%!). Definitely going to be considering another broker than TDA for this strategy. Plus that'll allow me to trade micro-lots, so I can be more granular(and thus accurate) with my position sizing and compounding.
A Note on Spread
As you can see in the data, there were scenarios where the spread was 80% of the overall size of the trade(the size of the confirmation candle that you draw your fibonacci retracements over), which would obviously cut heavily into your profits. Removing any trades where the spread is more than 50% of the trade width improved profits slightly without removing many trades, but this is almost certainly just coincidence on a small sample size. Going below 40% and even down to 30% starts to cut out a lot of trades for the less-common pairs, but doesn't actually change overall profits at all(~1% either way). However, digging all the way down to 25% starts to really make some movement. Profit at the -161.8% TP level jumps up to 37.94% if you filter out anything with a spread that is more than 25% of the trade width! And this even keeps the sample size fairly large at 187 total trades. You can get your profits all the way up to 48.43% at the -161.8% TP level if you filter all the way down to only trades where spread is less than 15% of the trade width, however your sample size gets much smaller at that point(108 trades) so I'm not sure I would trust that as being accurate in the long term. Overall based on this data, I'm going to only take trades where the spread is less than 25% of the trade width. This may bias my trades more towards the majors, which would mean a lot more correlated trades as well(more on correlation below), but I think it is a reasonable precaution regardless.
Time of Day
Time of day had an interesting effect on trades. In a totally predictable fashion, a vast majority of setups occurred during the London and New York sessions: 5am-12pm Eastern. However, there was one outlier where there were many setups on the 11PM bar - and the winrate was about the same as the big hours in the London session. No idea why this hour in particular - anyone have any insight? That's smack in the middle of the Tokyo/Sydney overlap, not at the open or close of either. On many of the hour slices I have a feeling I'm just dealing with small number statistics here since I didn't have a lot of data when breaking it down by individual hours. But here it is anyway - for all TP levels, these three things showed up(all in Eastern time):
7pm-4am: Fewer setups, but winrate high.
5am-6am: Lots of setups, but but winrate low.
12pm-3pm Medium number of setups, but winrate low.
I don't have any reason to think these timeframes would maintain this behavior over the long term. They're almost certainly meaningless. EDIT: When you de-dup highly correlated trades, the number of trades in these timeframes really drops, so from this data there is no reason to think these timeframes would be any different than any others in terms of winrate. That being said, these time frames work out for me pretty well because I typically sleep 12am-7am Eastern time. So I automatically avoid the 5am-6am timeframe, and I'm awake for the majority of this system's setups.
Moving stops up to breakeven
This section goes against everything I know and have ever heard about trade management. Please someone find something wrong with my data. I'd love for someone to check my formulas, but I realize that's a pretty insane time commitment to ask of a bunch of strangers. Anyways. What I found was that for these trades moving stops up...basically at all...actually reduced the overall profitability. One of the data points I collected while charting was where the price retraced back to after hitting a certain milestone. i.e. once the price hit the -61.8% profit level, how far back did it retrace before hitting the -100% profit level(if at all)? And same goes for the -100% profit level - how far back did it retrace before hitting the -161.8% profit level(if at all)? Well, some complex excel formulas later and here's what the results appear to be. Emphasis on appears because I honestly don't believe it. I must have done something wrong here, but I've gone over it a hundred times and I can't find anything out of place.
Moving SL up to 0% when the price hits -61.8%, TP at -100%
Adjusted Proft % (takes spread into account): 5.36%
Taking half position off at -61.8%, moving SL up to 0%, TP remaining half at -100%
Adjusted Proft % (takes spread into account): -1.01% (yes, a net loss)
Now, you might think exactly what I did when looking at these numbers: oof, the spread killed us there right? Because even when you move your SL to 0%, you still end up paying the spread, so it's not truly "breakeven". And because we are trading on a lower timeframe, the spread can be pretty hefty right? Well even when I manually modified the data so that the spread wasn't subtracted(i.e. "Breakeven" was truly +/- 0), things don't look a whole lot better, and still way worse than the passive trade management method of leaving your stops in place and letting it run. And that isn't even a realistic scenario because to adjust out the spread you'd have to move your stoploss inside the candle edge by at least the spread amount, meaning it would almost certainly be triggered more often than in the data I collected(which was purely based on the fib levels and mark price). Regardless, here are the numbers for that scenario:
Moving SL up to 0% when the price hits -61.8%, TP at -100%
Winrate(breakeven doesn't count as a win): 46.4%
Adjusted Proft % (takes spread into account): 17.97%
Taking half position off at -61.8%, moving SL up to 0%, TP remaining half at -100%
Winrate(breakeven doesn't count as a win): 65.97%
Adjusted Proft % (takes spread into account): 11.60%
From a literal standpoint, what I see behind this behavior is that 44 of the 69 breakeven trades(65%!) ended up being profitable to -100% after retracing deeply(but not to the original SL level), which greatly helped offset the purely losing trades better than the partial profit taken at -61.8%. And 36 went all the way back to -161.8% after a deep retracement without hitting the original SL. Anyone have any insight into this? Is this a problem with just not enough data? It seems like enough trades that a pattern should emerge, but again I'm no expert. I also briefly looked at moving stops to other lower levels (78.6%, 61.8%, 50%, 38.2%, 23.6%), but that didn't improve things any. No hard data to share as I only took a quick look - and I still might have done something wrong overall. The data is there to infer other strategies if anyone would like to dig in deep(more explanation on the spreadsheet below). I didn't do other combinations because the formulas got pretty complicated and I had already answered all the questions I was looking to answer.
2-Candle vs Confirmation Candle Stops
Another interesting point is that the original system has the SL level(for stop entries) just at the outer edge of the 2-candle pattern that makes up the system. Out of pure laziness, I set up my stops just based on the confirmation candle. And as it turns out, that is much a much better way to go about it. Of the 60 purely losing trades, only 9 of them(15%) would go on to be winners with stops on the 2-candle formation. Certainly not enough to justify the extra loss and/or reduced profits you are exposing yourself to in every single other trade by setting a wider SL. Oddly, in every single scenario where the wider stop did save the trade, it ended up going all the way to the -161.8% profit level. Still, not nearly worth it.
As I've said many times now, I'm really not qualified to be doing an analysis like this. This section in particular. Looking at shared currency among the pairs traded, 74 of the trades are correlated. Quite a large group, but it makes sense considering the sort of moves we're looking for with this system. This means you are opening yourself up to more risk if you were to trade on every signal since you are technically trading with the same underlying sentiment on each different pair. For example, GBP/USD and AUD/USD moving together almost certainly means it's due to USD moving both pairs, rather than GBP and AUD both moving the same size and direction coincidentally at the same time. So if you were to trade both signals, you would very likely win or lose both trades - meaning you are actually risking double what you'd normally risk(unless you halve both positions which can be a good option, and is discussed in ParallaxFX's posts and in various other places that go over pair correlation. I won't go into detail about those strategies here). Interestingly though, 17 of those apparently correlated trades ended up with different wins/losses. Also, looking only at trades that were correlated, winrate is 83%/70%/55% (for the three TP levels). Does this give some indication that the same signal on multiple pairs means the signal is stronger? That there's some strong underlying sentiment driving it? Or is it just a matter of too small a sample size? The winrate isn't really much higher than the overall winrates, so that makes me doubt it is statistically significant. One more funny tidbit: EUCAD netted the lowest overall winrate: 30% to even the -61.8% TP level on 10 trades. Seems like that is just a coincidence and not enough data, but dang that's a sucky losing streak. EDIT: WOW I spent some time removing correlated trades manually and it changed the results quite a bit. Some thoughts on this below the results. These numbers also include the other "What I will trade" filters. I added a new worksheet to my data to show what I ended up picking.
Total Trades: 75
TP at -61.8%: 84.00%
TP at -100%: 73.33%
TP at -161.8%: 60.00%
Moving SL up to 0% when the price hits -61.8%, TP at -100%: 53.33%
Taking half position off at -61.8%, moving SL up to 0%, TP remaining half at -100%: 53.33% (yes, oddly the exact same winrate. but different trades/profits)
Adjusted Proft % (takes spread into account):
TP at -61.8%: 18.13%
TP at -100%: 26.20%
TP at -161.8%: 34.01%
Moving SL up to 0% when the price hits -61.8%, TP at -100%: 19.20%
Taking half position off at -61.8%, moving SL up to 0%, TP remaining half at -100%: 17.29%
To do this, I removed correlated trades - typically by choosing those whose spread had a lower % of the trade width since that's objective and something I can see ahead of time. Obviously I'd like to only keep the winning trades, but I won't know that during the trade. This did reduce the overall sample size down to a level that I wouldn't otherwise consider to be big enough, but since the results are generally consistent with the overall dataset, I'm not going to worry about it too much. I may also use more discretionary methods(support/resistance, quality of indecision/confirmation candles, news/sentiment for the pairs involved, etc) to filter out correlated trades in the future. But as I've said before I'm going for a pretty mechanical system. This brought the 3 TP levels and even the breakeven strategies much closer together in overall profit. It muted the profit from the high R:R strategies and boosted the profit from the low R:R strategies. This tells me pair correlation was skewing my data quite a bit, so I'm glad I dug in a little deeper. Fortunately my original conclusion to use the -161.8 TP level with static stops is still the winner by a good bit, so it doesn't end up changing my actions. There were a few times where MANY (6-8) correlated pairs all came up at the same time, so it'd be a crapshoot to an extent. And the data showed this - often then won/lost together, but sometimes they did not. As an arbitrary rule, the more correlations, the more trades I did end up taking(and thus risking). For example if there were 3-5 correlations, I might take the 2 "best" trades given my criteria above. 5+ setups and I might take the best 3 trades, even if the pairs are somewhat correlated. I have no true data to back this up, but to illustrate using one example: if AUD/JPY, AUD/USD, CAD/JPY, USD/CAD all set up at the same time (as they did, along with a few other pairs on 6/19/20 9:00 AM), can you really say that those are all the same underlying movement? There are correlations between the different correlations, and trying to filter for that seems rough. Although maybe this is a known thing, I'm still pretty green to Forex - someone please enlighten me if so! I might have to look into this more statistically, but it would be pretty complex to analyze quantitatively, so for now I'm going with my gut and just taking a few of the "best" trades out of the handful. Overall, I'm really glad I went further on this. The boosting of the B/E strategies makes me trust my calculations on those more since they aren't so far from the passive management like they were with the raw data, and that really had me wondering what I did wrong.
What I will trade
Putting all this together, I am going to attempt to trade the following(demo for a bit to make sure I have the hang of it, then for keeps):
"System Details" I described above.
TP at -161.8%
Static SL at opposite side of confirmation candle - I won't move stops up to breakeven.
Trade only 7am-11am and 4pm-11pm signals.
Nothing where spread is more than 25% of trade width.
Looking at the data for these rules, test results are:
Adjusted Proft % (takes spread into account): 47.43%
I'll be sure to let everyone know how it goes!
Other Technical Details
ATR is only slightly elevated in this date range from historical levels, so this should fairly closely represent reality even after the COVID volatility leaves the scalpers sad and alone.
The sample size is much too small for anything really meaningful when you slice by hour or pair. I wasn't particularly looking to test a specific pair here - just the system overall as if you were going to trade it on all pairs with a reasonable spread.
Here's the spreadsheet for anyone that'd like it. (EDIT: Updated some of the setups from the last few days that have fully played out now. I also noticed a few typos, but nothing major that would change the overall outcomes. Regardless, I am currently reviewing every trade to ensure they are accurate.UPDATE: Finally all done. Very few corrections, no change to results.) I have some explanatory notes below to help everyone else understand the spiraled labyrinth of a mind that put the spreadsheet together.
I'm on the East Coast in the US, so the timestamps are Eastern time.
Time stamp is from the confirmation candle, not the indecision candle. So 7am would mean the indecision candle was 6:00-6:59 and the confirmation candle is 7:00-7:59 and you'd put in your order at 8:00.
I found a couple AM/PM typos as I was reviewing the data, so let me know if a trade doesn't make sense and I'll correct it.
Insanely detailed spreadsheet notes
For you real nerds out there. Here's an explanation of what each column means:
Pair - duh
Date/Time - Eastern time, confirmation candle as stated above
Win to -61.8%? - whether the trade made it to the -61.8% TP level before it hit the original SL.
Win to -100%? - whether the trade made it to the -100% TP level before it hit the original SL.
Win to -161.8%? - whether the trade made it to the -161.8% TP level before it hit the original SL.
Retracement level between -61.8% and -100% - how deep the price retraced after hitting -61.8%, but before hitting -100%. Be careful to look for the negative signs, it's easy to mix them up. Using the fib% levels defined in ParallaxFX's original thread. A plain hyphen "-" means it did not retrace, but rather went straight through -61.8% to -100%. Positive 100 means it hit the original SL.
Retracement level between -100% and -161.8% - how deep the price retraced after hitting -100%, but before hitting -161.8%. Be careful to look for the negative signs, it's easy to mix them up. Using the fib% levels defined in ParallaxFX's original thread. A plain hyphen "-" means it did not retrace, but rather went straight through -100% to -161.8%. Positive 100 means it hit the original SL.
Trade Width(Pips) - the size of the confirmation candle, and thus the "width" of your trade on which to determine position size, draw fib levels, etc.
Loser saved by 2 candle stop? - for all losing trades, whether or not the 2-candle stop loss would have saved the trade and how far it ended up getting if so. "No" means it didn't save it, N/A means it wasn't a losing trade so it's not relevant.
Spread(ThinkorSwim) - these are typical spreads for these pairs on ToS.
Spread % of Width - How big is the spread compared to the trade width? Not used in any calculations, but interesting nonetheless.
True Risk(Trade Width + Spread) - I set my SL at the opposite side of the confirmation candle knowing that I'm actually exposing myself to slightly more risk because of the spread(stop order = market order when submitted, so you pay the spread). So this tells you how many pips you are actually risking despite the Trade Width. I prefer this over setting the stop inside from the edge of the candle because some pairs have a wide spread that would mess with the system overall. But also many, many of these trades retraced very nearly to the edge of the confirmation candle, before ending up nicely profitable. If you keep your risk per trade at 1%, you're talking a true risk of, at most, 1.25% (in worst-case scenarios with the spread being 25% of the trade width as I am going with above).
Win or Loss in %(1% risk) including spread TP -61.8% - not going to go into huge detail, see the spreadsheet for calculations if you want. But, in a nutshell, if the trade was a win to 61.8%, it returns a positive # based on 61.8% of the trade width, minus the spread. Otherwise, it returns the True Risk as a negative. Both normalized to the 1% risk you started with.
Win or Loss in %(1% risk) including spread TP -100% - same as the last, but 100% of Trade Width.
Win or Loss in %(1% risk) including spread TP -161.8% - same as the last, but 161.8% of Trade Width.
Win or Loss in %(1% risk) including spread TP -100%, and move SL to breakeven at 61.8% - uses the retracement level columns to calculate profit/loss the same as the last few columns, but assuming you moved SL to 0% fib level after price hit -61.8%. Then full TP at 100%.
Win or Loss in %(1% risk) including spread take off half of position at -61.8%, move SL to breakeven, TP 100% - uses the retracement level columns to calculate profit/loss the same as the last few columns, but assuming you took of half the position and moved SL to 0% fib level after price hit -61.8%. Then TP the remaining half at 100%.
Overall Growth(-161.8% TP, 1% Risk) - pretty straightforward. Assuming you risked 1% on each trade, what the overall growth level would be chronologically(spreadsheet is sorted by date).
Based on the reasonable rules I discovered in this backtest:
Date range: 6/11-7/3
Adjusted Proft % (takes spread into account): 47.43%
Global Financial Markets: Habits of Good Traders and Bad Traders [Part 1]
The Internet has created opportunity of easy access to the Global Financial Markets. Everyone who desires to learn and earn can now trade in the Global Financial Markets, irrespective of their location around the world without discrimination. What used to be the secret investment opportunity for the rich and privileged few, has now become an open marketplace through digital platforms made accessible on mobile phones, portable tablets and laptops. Therefore, as Internet connectivity and broadband access continues to penetrate into every remote corners of the globe, the awareness of Global Financial Markets commonly referred to as FOREX TRADING, will continue to soar! According to Ian H. Giddy, Stern School of Business, New York University “The global financial markets include the market for foreign exchange, such as the Eurocurrency and related money markets, the international capital markets, notably the Eurobond and global equity markets, the commodity market and last but not least, the markets for forward contracts, options, swaps and other derivatives”. Simply put, the Global Financial Markets is a virtual platform for online trading of Currencies of countries at the International Foreign Exchange Rate, as it is done real time between Banks, Large Corporations, Investment Firms, Hedge Funds and Private Equity Portfolio managers. These are the big players, usually called the Market Makers. These Market Makers are high value and high volume traders that account for over 90% of the 5 trillion dollars worth of trading done everyday for 24 hours throughout the 5 working days of the week. The participation of Individual Traders called Retail Traders in the Global Financial Markets is only possible through a registered and verified account on the trading platform of licensedand regulated Brokers like in the Stock Exchange industry. While the sound of participating in an open market valued at over 5 trillion dollars per day, sounds attractive and inspiring; very few Individual Traders have successfully earned profits from the Global Financial Markets consistently. In many instances, the odds are usually against the Individual Traders due to the numerous cycles of events and uncertainties that influence Global Economy and Trade relationships between countries of the world which directly or indirectly affect the sentiments of buyers and sellers of the currency of countries against others. While many may assume that making profit in the Global Financial Markets is just as simple as clicking BUY or SELL buttons on the Broker’s trading platform, the few successful traders know that there are a lot more to learn and apply. Like everything in life, learning by doing is the best way to winning the trophy. Fairly enough, all Forex Brokers in the Global Financial Markets provide demo accounts with virtual money to help traders learn and practice before investing their real money. Unfortunately, due to the habit of indiscipline, many traders are usually impatient in learning and often allow greed to push them to rush into live trading without developing the necessary skills and habits that will guarantee consistent profit and successful trading career.
“Discipline is the ultimate secret of Distinction. What makes the difference between Good and Bad Traders is Self-Discipline!”
The majority of this sub is focused on technical analysis. I regularly ridicule such "tea leaf readers" and advocate for trading based on fundamentals and economic news instead, so I figured I should take the time to write up something on how exactly you can trade economic news releases. This post is long as balls so I won't be upset if you get bored and go back to your drooping dick patterns or whatever.
How economic news is released
First, it helps to know how economic news is compiled and released. Let's take Initial Jobless Claims, the number of initial claims for unemployment benefits around the United States from Sunday through Saturday. Initial in this context means the first claim for benefits made by an individual during a particular stretch of unemployment. The Initial Jobless Claims figure appears in the Department of Labor's Unemployment Insurance Weekly Claims Report, which compiles information from all of the per-state departments that report to the DOL during the week. A typical number is between 100k and 250k and it can vary quite significantly week-to-week. The Unemployment Insurance Weekly Claims Report contains data that lags 5 days behind. For example, the Report issued on Thursday March 26th 2020 contained data about the week ending on Saturday March 21st 2020. In the days leading up to the Report, financial companies will survey economists and run complicated mathematical models to forecast the upcoming Initial Jobless Claims figure. The results of surveyed experts is called the "consensus"; specific companies, experts, and websites will also provide their own forecasts. Different companies will release different consensuses. Usually they are pretty close (within 2-3k), but for last week's record-high Initial Jobless Claims the reported consensuses varied by up to 1M! In other words, there was essentially no consensus. The Unemployment Insurance Weekly Claims Report is released each Thursday morning at exactly 8:30 AM ET. (On Thanksgiving the Report is released on Wednesday instead.) Media representatives gather at the Frances Perkins Building in Washington DC and are admitted to the "lockup" at 8:00 AM ET. In order to be admitted to the lockup you have to be a credentialed member of a media organization that has signed the DOL lockup agreement. The lockup room is small so there is a limited number of spots. No phones are allowed. Reporters bring their laptops and connect to a local network; there is a master switch on the wall that prevents/enables Internet connectivity on this network. Once the doors are closed the Unemployment Insurance Weekly Claims Report is distributed, with a heading that announces it is "embargoed" (not to be released) prior to 8:30 AM. Reporters type up their analyses of the report, including extracting key figures like Initial Jobless Claims. They load their write-ups into their companies' software, which prepares to send it out as soon as Internet is enabled. At 8:30 AM the DOL representative in the room flips the wall switch and all of the laptops are connected to the Internet, releasing their write-ups to their companies and on to their companies' partners. Many of those media companies have externally accessible APIs for distributing news. Media aggregators and squawk services (like RanSquawk and TradeTheNews) subscribe to all of these different APIs and then redistribute the key economic figures from the Report to their own subscribers within one second after Internet is enabled in the DOL lockup. Some squawk services are text-based while others are audio-based. FinancialJuice.com provides a free audio squawk service; internally they have a paid subscription to a professional squawk service and they simply read out the latest headlines to their own listeners, subsidized by ads on the site. I've been using it for 4 months now and have been pretty happy. It usually lags behind the official release times by 1-2 seconds and occasionally they verbally flub the numbers or stutter and have to repeat, but you can't beat the price! Important - I’m not affiliated with FinancialJuice and I’m not advocating that you use them over any other squawk. If you use them and they misspeak a number and you lose all your money don’t blame me. If anybody has any other free alternatives please share them!
How the news affects forex markets
Institutional forex traders subscribe to these squawk services and use custom software to consume the emerging data programmatically and then automatically initiate trades based on the perceived change to the fundamentals that the figures represent. It's important to note that every institution will have "priced in" their own forecasted figures well in advance of an actual news release. Forecasts and consensuses all come out at different times in the days leading up to a news release, so by the time the news drops everybody is really only looking for an unexpected result. You can't really know what any given institution expects the value to be, but unless someone has inside information you can pretty much assume that the market has collectively priced in the experts' consensus. When the news comes out, institutions will trade based on the difference between the actual and their forecast. Sometimes the news reflects a real change to the fundamentals with an economic effect that will change the demand for a currency, like an interest rate decision. However, in the case of the Initial Jobless Claims figure, which is a backwards-looking metric, trading is really just self-fulfilling speculation that market participants will buy dollars when unemployment is low and sell dollars when unemployment is high. Generally speaking, news that reflects a real economic shift has a bigger effect than news that only matters to speculators. Massive and extremely fast news-based trades happen within tenths of a second on the ECNs on which institutional traders are participants. Over the next few seconds the resulting price changes trickle down to retail traders. Some economic news, like Non Farm Payroll Employment, has an effect that can last minutes to hours as "slow money" follows behind on the trend created by the "fast money". Other news, like Initial Jobless Claims, has a short impact that trails off within a couple minutes and is subsequently dwarfed by the usual pseudorandom movements in the market. The bigger the difference between actual and consensus, the bigger the effect on any given currency pair. Since economic news releases generally relate to a single currency, the biggest and most easily predicted effects are seen on pairs where one currency is directly effected and the other is not affected at all. Personally I trade USD/JPY because the time difference between the US and Japan ensures that no news will be coming out of Japan at the same time that economic news is being released in the US. Before deciding to trade any particular news release you should measure the historical correlation between the release (specifically, the difference between actual and consensus) and the resulting short-term change in the currency pair. Historical data for various news releases (along with historical consensus data) is readily available. You can pay to get it exported into Excel or whatever, or you can scroll through it for free on websites like TradingEconomics.com. Let's look at two examples: Initial Jobless Claims and Non Farm Payroll Employment (NFP). I collected historical consensuses and actuals for these releases from January 2018 through the present, measured the "surprise" difference for each, and then correlated that to short-term changes in USD/JPY at the time of release using 5 second candles. I omitted any releases that occurred simultaneously as another major release. For example, occasionally the monthly Initial Jobless Claims comes out at the exact same time as the monthly Balance of Trade figure, which is a more significant economic indicator and can be expected to dwarf the effect of the Unemployment Insurance Weekly Claims Report. USD/JPY correlation with Initial Jobless Claims (2018 - present) USD/JPY correlation with Non Farm Payrolls (2018 - present) The horizontal axes on these charts is the duration (in seconds) after the news release over which correlation was calculated. The vertical axis is the Pearson correlation coefficient: +1 means that the change in USD/JPY over that duration was perfectly linearly correlated to the "surprise" in the releases; -1 means that the change in USD/JPY was perfectly linearly correlated but in the opposite direction, and 0 means that there is no correlation at all. For Initial Jobless Claims you can see that for the first 30 seconds USD/JPY is strongly negatively correlated with the difference between consensus and actual jobless claims. That is, fewer-than-forecast jobless claims (fewer newly unemployed people than expected) strengthens the dollar and greater-than-forecast jobless claims (more newly unemployed people than expected) weakens the dollar. Correlation then trails off and changes to a moderate/weak positive correlation. I interpret this as algorithms "buying the dip" and vice versa, but I don't know for sure. From this chart it appears that you could profit by opening a trade for 15 seconds (duration with strongest correlation) that is long USD/JPY when Initial Jobless Claims is lower than the consensus and short USD/JPY when Initial Jobless Claims is higher than expected. The chart for Non Farm Payroll looks very different. Correlation is positive (higher-than-expected payrolls strengthen the dollar and lower-than-expected payrolls weaken the dollar) and peaks at around 45 seconds, then slowly decreases as time goes on. This implies that price changes due to NFP are quite significant relative to background noise and "stick" even as normal fluctuations pick back up. I wanted to show an example of what the USD/JPY S5 chart looks like when an "uncontested" (no other major simultaneously news release) Initial Jobless Claims and NFP drops, but unfortunately my broker's charts only go back a week. (I can pull historical data going back years through the API but to make it into a pretty chart would be a bit of work.) If anybody can get a 5-second chart of USD/JPY at March 19, 2020, UTC 12:30 and/or at February 7, 2020, UTC 13:30 let me know and I'll add it here.
So without too much effort we determined that (1) USD/JPY is strongly negatively correlated with the Initial Jobless Claims figure for the first 15 seconds after the release of the Unemployment Insurance Weekly Claims Report (when no other major news is being released) and also that (2) USD/JPY is strongly positively correlated with the Non Farms Payroll figure for the first 45 seconds after the release of the Employment Situation report. Before you can assume you can profit off the news you have to backtest and consider three important parameters. Entry speed: How quickly can you realistically enter the trade? The correlation performed above was measured from the exact moment the news was released, but realistically if you've got your finger on the trigger and your ear to the squawk it will take a few seconds to hit "Buy" or "Sell" and confirm. If 90% of the price move happens in the first second you're SOL. For back-testing purposes I assume a 5 second delay. In practice I use custom software that opens a trade with one click, and I can reliably enter a trade within 2-3 seconds after the news drops, using the FinancialJuice free squawk. Minimum surprise: Should you trade every release or can you do better by only trading those with a big enough "surprise" factor? Backtesting will tell you whether being more selective is better long-term or not. Hold time: The optimal time to hold the trade is not necessarily the same as the time of maximum correlation. That's a good starting point but it's not necessarily the best number. Backtesting each possible hold time will let you find the best one. The spread: When you're only holding a position open for 30 seconds, the spread will kill you. The correlations performed above used the midpoint price, but in reality you have to buy at the ask and sell at the bid. Brokers aren't stupid and the moment volume on the ECN jumps they will widen the spread for their retail customers. The only way to determine if the news-driven price movements reliably overcome the spread is to backtest. Stops: Personally I don't use stops, neither take-profit nor stop-loss, since I'm automatically closing the trade after a fixed (and very short) amount of time. Additionally, brokers have a minimum stop distance; the profits from scalping the news are so slim that even the nearest stops they allow will generally not get triggered. I backtested trading these two news releases (since 2018), using a 5 second entry delay, real historical spreads, and no stops, cycling through different "surprise" thresholds and hold times to find the combination that returns the highest net profit. It's important to maximize net profit, not expected value per trade, so you don't over-optimize and reduce the total number of trades taken to one single profitable trade. If you want to get fancy you can set up a custom metric that combines number of trades, expected value, and drawdown into a single score to be maximized. For the Initial Jobless Claims figure I found that the best combination is to hold trades open for 25 seconds (that is, open at 5 seconds elapsed and hold until 30 seconds elapsed) and only trade when the difference between consensus and actual is 7k or higher. That leads to 30 trades taken since 2018 and an expected return of... drumroll please... -0.0093 yen per unit per trade. Yep, that's a loss of approx. $8.63 per lot. Disappointing right? That's the spread and that's why you have to backtest. Even though the release of the Unemployment Insurance Weekly Claims Report has a strong correlation with movement in USD/JPY, it's simply not something that a retail trader can profit from. Let's turn to the NFP. There I found that the best combination is to hold trades open for 75 seconds (that is, open at 5 seconds elapsed and hold until 80 seconds elapsed) and trade every single NFP (no minimum "surprise" threshold). That leads to 20 trades taken since 2018 and an expected return of... drumroll please... +0.1306 yen per unit per trade. That's a profit of approx. $121.25 per lot. Not bad for 75 seconds of work! That's a +6% ROI at 50x leverage.
Make it real
If you want to do this for realsies, you need to run these numbers for all of the major economic news releases. Markit Manufacturing PMI, Factory Orders MoM, Trade Balance, PPI MoM, Export and Import Prices, Michigan Consumer Sentiment, Retail Sales MoM, Industrial Production MoM, you get the idea. You keep a list of all of the releases you want to trade, when they are released, and the ideal hold time and "surprise" threshold. A few minutes before the prescribed release time you open up your broker's software, turn on your squawk, maybe jot a few notes about consensuses and model forecasts, and get your finger on the button. At the moment you hear the release you open the trade in the correct direction, hold it (without looking at the chart!) for the required amount of time, then close it and go on with your day. Some benefits of trading this way: * Most major economic releases come out at either 8:30 AM ET or 10:00 AM ET, and then you're done for the day. * It's easily backtestable. You can look back at the numbers and see exactly what to expect your return to be. * It's fun! Packing your trading into 30 seconds and knowing that institutions are moving billions of dollars around as fast as they can based on the exact same news you just read is thrilling. * You can wow your friends by saying things like "The St. Louis Fed had some interesting remarks on consumer spending in the latest Beige Book." * No crayons involved. Some downsides: * It's tricky to be fast enough without writing custom software. Some broker software is very slow and requires multiple dialog boxes before a position is opened, which won't cut it. * The profits are very slim, you're not going to impress your instagram followers to join your expensive trade copying service with your 30-second twice-weekly trades. * Any friends you might wow with your boring-ass economic talking points are themselves the most boring people in the world. I hope you enjoyed this long as fuck post and you give trading economic news a try!
Thoughts on cryptocurrency (design, function, quantitative analysis/market forecast) and the politics of aid in the new post-COVID-19 era/epoch
Cryptocurrency $1.4bn of $25bn financial reporting market/space. ETFs at 25% of mutual funds, mutual funds at 40% of the stock market, FinViz.com market cap. as US-based, looking at near 38-40% discounting on population-based speculation (because of 40% worldwide markets under 3% since 1961-2018, and because of OTC derivatives compared with total money supply less inflation, over the past 20-30 years), because of the credit/debit cycle of recessions in less wealthy countries viz. WorldBank data, IMF rules about aid disbursements, etc. FinViz: $41.55tn; at an average with market capitalization given proper weight, 1.95% gains on average, per a review of the total M1 money supply compared with FOREX trades, per day, compared with the commodities schedule, viz. ports and distribution centers/shipping and trucking companies (internal consistency test/check on the market); also, businesses and sectors totaling less than $1.4bn, or some multiplier of that, even accounting for growth, by 2025 or later. Gold and other precious metals, etc., as a function of the BitCoin halving, as an institutional and technological hedge (use BitCoin as a hedge against inflation, or an indicator of it, after the halving, and gold/precious metals as a hedge on BitCoin, as empty money viz. real-perceived value of commodities, and as a way to financially exert institutional leverage on the development of perfect security for distribution supply-chains, AI-based coins, etc. * The U.S. and allies (OECD) stimulus to poorer nations; did the territories get stimulus checks? * Dollar, CryptoBuck, the $1 start-up currency; starts at $1, companies buy a % of that $1, the $1 is scheduled to have its return and discount the rest into charitable funds as the stock market does it’s martingale cycle, moving forward, to fight inflation; that is, every time the stock market does a martingale cycle, 50% less is released as a new coin offering, so initially $1, then $0.50, then $0.25, then $0.125, and so on, with the rest going to charity, thru X number of cycles; thus you have, at the outset, $1 dedicated to investments, and that is used as a tracker, sort of like a cookie, the shareholder % holdings are divided say, every year, or every two years, or every four years, not frequently, in other words, to emphasize the credit/debit cycle outside of the calendar year period, and say it’s pegged to the S&P500, or a section of NASDAQ, or a specific type of instrument, like a portfolio of risk-balanced ETFs, that could be it’s own project, when that doubles in market capitalization, or overall return % since the ICO, the amount of new buy-in to the coin is halved, no matter what the current price of the coin is, such that you can buy a new generation of coins, which are say less risk-averse because of the prior filtering of data through products like Yoga/Coil, of the initial $1 unit, at an additional $0.50, but with the other $0.50 going to charity, and see if you can reach a convention well past 3% of earnings, but in fact almost 100% of future earnings, asymptotically, on small amounts of money, really is the idea. So that as the coin shrinks in utility, the magnification between lending of point-to-point, cent loaned to cent owed, becomes obvious. * StarChart (qualitative sentiment index/NLP insights into music criticism/YouTube commentary, etc.). Art/music, charity, astrophysics. YieldShare, Tully, etc.
Forex is the short way of saying “Foreign Exchange”. This means the global market for exchanging international currencies, also known as the FX market. When someone prices or exchanges a currency against another, the exchange rate is best on the particular forex trading pair (i.e., both currencies involved in the pair). Currency pairs are typically priced out to four decimal places, depending on the currency denomination, where one ten-thousandth of a unit of currency is known as a pip (i.e., 0.0001 unit), which is the smallest price increment (in addition to fractional-pips). The EUUSD, which is the most widely-traded forex pair, is an example of the Euro (EUR) currency against the US dollars (USD) currency. When trading one unit of EUUSD, you can calculate the price in USD (i.e., a price of EUUSD 1.3000 indicates $1.30 per euro). Conversely, when exchanging the USD/EUR, each unit of USD (i.e. each dollar) will have the prace of a specific number of euros (i.e., a USD/EUR price of 0.7700 indicates €0.77 per dollar). A speculator expecting the price of the EUUSD to go up. He will buy the EUUSD pair long (buying a pair to open a trade can be a bullish or long position). Whereas, a speculator anticipating a drop in the price of the EUUSD may sell the pair. (bearish or short position: selling to open a trade).
Largest international market Globally
The forex market is decentralized across the globe. It consists of dealers such as central banks, private and public banks, non-bank intermediaries, brokerages, and large corporations such as insurance giants and other participants engaged in international finance.
TheForeign Exchange marketis the largest globally, with nearly $6 trillion in average daily volume traded as of April 2019, according to the latestBISTriennial Survey of Central Banks.
The FX market suffers the influence mainly by each government’s monetary policy, the supply, and demand of the global economy. As well as international trade agreements, and users and suppliers of currencies (hedgers), in addition to speculators.
Market integrity and progress
While there have been cases of forex market manipulation by the biggest banks and dealers in the past, the amount of influence any one entity can have on the prices of major currencies is negligible. This resistance to serious manipulation risk is due to the enormous amount of trading and resulting liquidity available. The FX Market itself has high price integrity. Because it is an electronic market, efficient and with a certain size. Participants must still adhere to best practices.
Efforts such as theGlobal FX codewere launched to encourage forex dealers to uphold the best-execution where the best price available is given to traders.
These efforts are why the spreads and trading commissions continued to improve over the years, as the FX market evolved. In addition, regulators have competed to increase local market integrity and efficiency by creating more strict regulations. These come from the top-tier financial centers such as the US, UK, Singapore, Japan, Australia, among other advanced economies.
Investing and trading in the forex market
As an asset class, Forex is well-established and offered by many regulated brokerages from within a margin account.
The use of leverage is what makes forex trading more risky than non-margin investing.
Margin-based trading used by investors as well as self-directed traders and fund managers, thanks to the range of risk-management tools available within forex trading platforms (mobile, web, and desktop software). Wiseinvest provides trading signals with risk-management.
Forex market research and analysis
There are two primary ways for traders to assess and identify trading opportunities in the forex market.
One is through the use of fundamental analysis, which looks at economic news and data released by governmental agencies, as well as market sentiment data.
The second is through technical analysis, which pertains to the historical and current market price of the underlying currency.
Advanced forex trading strategies and algorithms
The foundation of successful trading in the forex market is having a trading strategy. It’s based on a specific methodology that best suits your trading needs. Strategies could be manual, automated, or a combination of both.
Over the past decade, there has been a proliferation of automated trading strategies made available for retail traders.
And while there are many serious traders with established track records for their trading systems, there are many more low-quality trading systems falsely marketed as high-quality by overly eager affiliates, making it harder for investors to navigate the market for trading signals.
There has also been an increase in the social copy trade. Where an operator can mimic other operators’ businesses in real time.
Whether using a copy-trading platform or an automated trading system, in almost all cases, this type of investing is considered self-directed and doesn’t require a power-of-attorney or another third-party money manager to handle your account. Unlike other copy and social trading platforms, Wiseinvet’s AI has the ability to execute a huge set of market data. It does by combining technical and fundamental analysis. This strategy can increase the accuracy of trading signals.
Self-directed forex investors
Compared to investing in a managed fund, there is greater responsibility. Traders put it on self-directed traders who use trading systems. A self-directed trader should conduct more detailed due diligence. It can avoid falling for the countless low-quality trading systems that exist on the internet.
Good quality trading systems will have established track records (historical results), and there will be other quantitative performance rankings, along with qualitative data about the strategy developers and any proprietary math used to operate the strategy.
Bad quality trading systems will usually promise high returns will not equally emphasizing potential risk.
There are no guarantees that a strategy will perform well. But conducting proper due diligence can help traders assess various trading systems. They consider using them to aid their trading or investment strategy.
Looking at how EUR-USD has performed in 2019, I struggle to understand the reasons for the -21% value in the EUR currency. The ECB's inflation target per year is 2%, so I'm wondering if looking at how currency trades is not a good indicator of the actual inflation of a currency, as I think that a lot of sentiment is involved when trading currency, just like equities (declaration from the ECB, governments, etc). So how to read the real value of the EUR? How to tell the real value of 1 EUR on January 1st, 2019 and December 31st, 2019? Appreciate any insight here, thank you for taking the time to answer!
Wall Street Week Ahead for the trading week beginning June 24th, 2019
Good afternoon and happy Saturday to all of you here on wallstreetbets. I hope everyone on this subreddit made out pretty nicely in the market this past week, and is ready for the new trading week ahead. Here is everything you need to know to get you ready for the trading week beginning June 24th, 2019.
What to watch in the market in the week ahead: Stocks on track for best first half in 22 years - (Source)
The fate of U.S.-China trade talks could play out in the week ahead, and that could set the tone for markets and the economy in the second half of the year. Stocks set new highs in the past week, after the Federal Reserve signaled it was ready to cut interest rates if necessary, and Fed Chair Jerome Powell said trade and the global economy are two factors the Fed is watching. The S&P 500 was on track, as of Friday, to score a more than 17.6% gain for the first half, which ends Friday. If it stays at that level that would be the best first half performance since 1997, when the S&P was up 19.4% in the first six months. The big event in the coming week has been as anticipated for weeks, and it could sway sentiment for weeks to come. At the end of the week, the G-20 meets in Osaka Japan for meetings Friday and Saturday. ‘Could go either way’ President Donald Trump and Chinese President Xi Jinping are expected to have their own dinner meeting at the G-20 next weekend, following discussions between their trade representatives. That meeting could decide how trade negotiations go forward, and whether the U.S. proceeds with another round of tariffs, this time on $300 billion in goods. “Everybody knows the Trump, Xi meeting could go either way,” said Marc Chandler, chief market strategist at Bannockburn Global Forex. “I think everyone expects a new tariff freeze. That the $300 billion won’t go into effect. The most you can hope for out of G-20 meeting is the tariffs are where they are right now, and there’s no more escalation.That also means China will not release the list of companies they won’t do business with.” Chandler said he will be looking for signaling from Trump and Xi on whether they are working on a deal that would be just on the trade topics, or bigger issues like North Korea and differences on the South China Sea. “I do think the G-20 is quite important in that there’s not question in recent months, the trade war started to really move into measures of confidence and measures of manufacturing activity,” said Ethan Harris, head of global economics at Bank of America Merrill Lynch. Harris said he expects a positive message with an agreement of no further escalation, but probably not signs of significant progress. “I think the vibes coming out of it will be modestly positive,” he said. “Whether there’s an escalation to the next round of China tariffs is going to set the theme for the rest of the year. Even if tariffs on China are reversed, or partly reversed, at some point, every time there’s an escalation or temporary escalation, it’s another kind of blow to confidence,” he said. Harris said there’s the same risk as after the Trump, Xi meeting at the last G-20, where it was a positive tone but there was little progress afterwards and the markets then reacted negatively. “I think there’s been this broad increased awareness from every economist that the trade war is starting to have noticeable impact. Further escalation with China would be quite a big signal. If the Trump administration puts tariffs on all the Chinese products it roughly doubles the size of the trade war and it sends a very strong message that there are very few constraints on where [Trump] goes next,” he said. Powell and data Besides the meeting between Trump and Xi, the market focus will be on anything that could provide clues on what the Fed or even the European Central Bank will do, after ECB President Mario Draghi last week basically promised a new era of easing. Consumer price inflation data is expected for the euro zone, and on Friday, the U.S. personal consumption expenditure data is released, including the PCE deflator, a major inflation indicator for the Fed. There are also a few Fed speakers, including Powell who speaks at the Council on Foreign Relations Tuesday. “It’s probably going to be a big picture kind of talk about the broader challenges of the Fed,” said Ethan Harris, head of global economics at Bank of America Merrill Lynch. “They’re certainly going to ask questions about political influence at the Fed, and he’s going to dodge those. I think what I’m waiting for him to comment on is what it is they’re looking for to determine whether they’re going to cut in July or not.” Harris said Powell is not likely to say anything he did not reveal at his press briefing in the past week, and the big focus will be on the lead up to the weekend G-20. Falling interest rates and rising oil prices were two big factors in the market int he past week. The 10-year Treasury yield dipped briefly below 2%, a near 3-year low, as the Fed signaled its willingness to cut interest rates. “Should we get some sort of trade agreement that would be a nice pop to the [stock] market, but that could take the rate cut off the table,” said Sam Stovall, chief investment strategist at CFRA. Stovall said the stock market will also be watching oil after its rapid run higher, and the events in the Middle East surrounding Iran. West Texas Intermediate futures were up more than 9% in the past week, to $57.43. “The old adage is every $10 increase in the price of oil takes off 20 to 25 basis points off of real GDP growth,” he said. Stovall said stocks have had a solid run so far this year, but they may face some rocky times between now and the end of the summer. “For the rest of this ‘sell in May’ period we could be facing some challenges, headwinds. I think we’ will still end higher on the year. I think the seasonally optimistic September to November period will kick in but there will be a lot of challenges...will the Fed be cutting rates? what are the growth prospects?” he said.
This past week saw the following moves in the S&P:
S&P 500 is off to it best June performance since 1955, up 7.34% as of yesterday’s close. If yesterday was the last trading day of June, this performance would have been strong enough to push the month to 6th best going back to 1930. Looking back to late May, this performance is still impressive even though it was anticipated following May’s abysmal showing. However, such strong performance in June may not carry over into July. Below S&P 500 performance in June has been split into positive and negative tables. Each table contains July’s historical performance as well as full-year performance. Historically July has been weaker after a positive June. July averages just 0.48% after an up June compared to a gain of 2.84% after a down June. Examining the Top 20 Junes and subsequent Julys showed only a modest improvement in performance with average July gain climbing to 1.11%. However, even if July does disappoint this year, the full year is likely to still be quite fair as past positive Junes where followed by full-year gains 80% of the time with an average gain of 13.44%.
U.S. stocks could have a big year if LPL Research’s forecasts prove correct. All year, we’ve maintained our fair value target on the S&P 500 Index of 3,000, implying that we expect this bull market and economic expansion to continue. If the S&P 500 closes the year at 3,000, the index will have gained 19.7% in 2019. On the surface, that seems like a high hurdle for U.S. stocks. However, the S&P 500 has already gained about 16% this year, so a rally to 3,000 isn’t far out of reach. The S&P 500 also hasn’t posted a 20% gain for the year since 2013, an unusually long stretch compared to history. “It is interesting that the S&P 500 hasn’t gained more than 20% in any one year for five consecutive years,” noted LPL Senior Market Strategist Ryan Detrick. “Only once since 1950 did it go more than five years in a row without gaining 20%, thus if this pattern continues we very well might get to 20% in 2019.” As our LPL Chart of the Day “Can The S&P 500 Index Really Gain 20% This Year?” shows, it is quite rare for the S&P 500 to go this long without a 20% annual gain. Could the streak end in 2019? Be sure to read our Midyear Outlook 2019, which is set for release next week, for more on why this could be the case.
As widely anticipated, the Fed did not change its target rate today. Instead, the Fed set the stage for cuts possibly later this year. Overall, the market’s response was a choppy climb to a modestly higher close. A more enthusiastic move by the market may have occurred if the Fed cut rates. Gold’s reaction was more favorable, finishing the day higher by over 1%. Generally, the lower interest rates go, the more desirable gold can become as lower rates typically result in a weaker dollar.
In the above chart, gold’s monthly performance from 1975 to 2018 is displayed. Historically, October has been gold’s worst month and June is a close second. Historically, after weakness in June, gold has, on average, enjoyed solid gains in July, August and September. Some of this strength in gold is likely due to safe-haven demand during the stock market’s worst two months, August and September. Gold’s best three months, July to September, could easily be above average this year, especially if the Fed decides to cut sooner rather than later.
Are Bulls An Endangered Species?
The S&P 500 Index closed at a new all-time high yesterday, the 5th new high so far in 2019. After May, the worst month for the S&P 500 since 2010, June is up 7.3% as of 06.20.19, which would be the best June since 1955. Much of the rally this month has been sparked by a more dovish Federal Reserve (Fed), combined with U.S.-China trade discussions potentially back on track. What’s quite interesting about things now though, is many signs of investor sentiment are a long way from bullish. Remember, from a contrarian (or opposing) point of view, this can suggest there is still money on the sidelines. “The S&P 500 might be at new highs, but global fund managers and individual investors are quite underweight equities right now,” explained LPL Senior Market Strategist Ryan Detrick. “If you are looking for a reason this rally can continue, that could be it.” For example, the recent Bank of America Merrill Lynch June Global Fund Manager Survey (a survey of managers who oversee more than $600 billion in assets) showed the largest jump in cash since August 2011. Additionally, equity allocation was the lowest it had been since March 2009, and the equity-to-bond allocation was the lowest since May 2009. Not to mention the allocation to bonds was the highest it had been in eight years. “Money on the sidelines might sound cliché, but it really seems to be the case this time,” said Detrick. With the S&P 500 hitting more all-time highs, having money in the market may make more sense (or cents!). Individual investors are skeptical as well, as the recent American Association of Individual Investors (AAII) Sentiment Survey showed more bears than bulls for six straight weeks, the longest stretch since November 2016. Finally, as our LPL Chart of the Day shows, AAII bulls have been under 30% for six consecutive weeks for the first time since January 2016.
Broad Strength in Health Care Sector
In an earlier post, we highlighted the fact that some of the ten best performing S&P 500 Industries between the S&P 500's highs on 4/30 and 6/20 were from the Health Care sector. It hasn't just been these four industries that have been strong in the Health Care sector either. The performance snapshot of the sector below shows just how strong the sector has been lately. While all six of the industries within the sector aren't up YTD or so far in Q2, between the S&P 500's highs on 4/30 and 6/20, Health Care is the only sector where every industry within the sector has posted positive returns. Not even the industries within the Utilities sector have been this uniformly positive. The best performer of the bunch has been Health Care Technology, which is up 8% since the end of April and has extended its YTD gain to 36.8%. The worst performing industry in the sector has been Biotech which is up 2.1% since 4/30, and while that may not sound like much, it's still better than more than half of the other industries in the index.
While the S&P 500 made a new high for the first time in 35 trading days yesterday, many of the characteristics of the groups driving the rally have shifted. To highlight this, in the table below we summarize the ten best and worst performing S&P 500 Industries from the close on 4/30 through yesterday. During that 35 trading day stretch, 34 Industries saw positive returns while another 27 declined. Industries that have seen the biggest gains between the two new highs are primarily defensive in nature as all but three come from sectors that are typically considered defensive (Consumer Staples, Health Care, and Real Estate). Health Care has been the real star of the show, though. Of the sector's six different industries, four of them made the top ten! On the downside, cyclical industries have dominated the weak side. When industries like Semis, Autos, Construction & Engineering, and Air Freight are lagging the market, it really illustrates the presence of economic concerns. Leading the way lower, Energy Equipment and Services declined over 10%, followed by Semiconductors which were down just under 10% after failing at resistance on Thursday for the third time in a month. These two industries are followed by two industries (Tobacco and Power and Renewable Energy) that come from sectors that are traditionally considered defensive, but they have their own specific issues to deal with.
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Micron Technology, Inc. $33.25
Micron Technology, Inc. (MU) is confirmed to report earnings at approximately 4:00 PM ET on Tuesday, June 25, 2019. The consensus earnings estimate is $0.75 per share on revenue of $4.72 billion and the Earnings Whisper ® number is $0.75 per share. Investor sentiment going into the company's earnings release has 40% expecting an earnings beat The company's guidance was for earnings of $0.75 to $0.95 per share. Consensus estimates are for earnings to decline year-over-year by 75.96% with revenue decreasing by 39.46%. Short interest has decreased by 16.6% since the company's last earnings release while the stock has drifted lower by 20.3% from its open following the earnings release to be 14.5% below its 200 day moving average of $38.89. Overall earnings estimates have been revised higher since the company's last earnings release. On Thursday, June 20, 2019 there was some notable buying of 12,540 contracts of the $25.00 put expiring on Friday, July 19, 2019. Option traders are pricing in a 4.5% move on earnings and the stock has averaged a 5.5% move in recent quarters.
BlackBerry Limited (BB) is confirmed to report earnings at approximately 7:00 AM ET on Wednesday, June 26, 2019. The consenus estimate is for breakeven results on revenue of $249.12 million and the Earnings Whisper ® number is $0.02 per share. Investor sentiment going into the company's earnings release has 66% expecting an earnings beat. Consensus estimates are for earnings to decline year-over-year by 100.00% with revenue increasing by 16.96%. The stock has drifted lower by 14.1% from its open following the earnings release to be 4.2% below its 200 day moving average of $8.85. On Wednesday, June 12, 2019 there was some notable buying of 3,499 contracts of the $9.00 call expiring on Friday, June 28, 2019. Option traders are pricing in a 10.2% move on earnings and the stock has averaged a 8.4% move in recent quarters.
FedEx Corp. (FDX) is confirmed to report earnings at approximately 4:00 PM ET on Tuesday, June 25, 2019. The consensus earnings estimate is $4.81 per share on revenue of $17.96 billion and the Earnings Whisper ® number is $4.95 per share. Investor sentiment going into the company's earnings release has 45% expecting an earnings beat. Consensus estimates are for earnings to decline year-over-year by 18.61% with revenue increasing by 3.73%. Short interest has increased by 60.1% since the company's last earnings release while the stock has drifted lower by 4.3% from its open following the earnings release to be 14.3% below its 200 day moving average of $192.96. Overall earnings estimates have been revised lower since the company's last earnings release. On Wednesday, June 19, 2019 there was some notable buying of 3,273 contracts of the $175.00 call expiring on Friday, July 19, 2019. Option traders are pricing in a 2.7% move on earnings and the stock has averaged a 4.8% move in recent quarters.
Nike Inc (NKE) is confirmed to report earnings at approximately 4:15 PM ET on Thursday, June 27, 2019. The consensus earnings estimate is $0.66 per share on revenue of $10.16 billion and the Earnings Whisper ® number is $0.71 per share. Investor sentiment going into the company's earnings release has 70% expecting an earnings beat. Consensus estimates are for earnings to decline year-over-year by 4.35% with revenue increasing by 3.79%. Short interest has increased by 0.6% since the company's last earnings release while the stock has drifted higher by 0.6% from its open following the earnings release to be 6.8% above its 200 day moving average of $80.27. Overall earnings estimates have been revised lower since the company's last earnings release. On Thursday, June 20, 2019 there was some notable buying of 3,156 contracts of the $92.50 call expiring on Friday, July 19, 2019. Option traders are pricing in a 2.6% move on earnings and the stock has averaged a 4.8% move in recent quarters.
General Mills, Inc. (GIS) is confirmed to report earnings at approximately 7:00 AM ET on Wednesday, June 26, 2019. The consensus earnings estimate is $0.76 per share on revenue of $4.23 billion and the Earnings Whisper ® number is $0.79 per share. Investor sentiment going into the company's earnings release has 52% expecting an earnings beat. Consensus estimates are for earnings to decline year-over-year by 3.80% with revenue increasing by 8.73%. Short interest has increased by 1.3% since the company's last earnings release while the stock has drifted higher by 11.2% from its open following the earnings release to be 16.9% above its 200 day moving average of $45.98. Overall earnings estimates have been revised higher since the company's last earnings release. Option traders are pricing in a 5.3% move on earnings and the stock has averaged a 4.4% move in recent quarters.
Walgreens Boots Alliance Inc (WBA) is confirmed to report earnings at approximately 7:00 AM ET on Thursday, June 27, 2019. The consensus earnings estimate is $1.43 per share on revenue of $34.53 billion and the Earnings Whisper ® number is $1.45 per share. Investor sentiment going into the company's earnings release has 38% expecting an earnings beat. Consensus estimates are for earnings to decline year-over-year by 6.54% with revenue increasing by 0.57%. Short interest has decreased by 8.1% since the company's last earnings release while the stock has drifted lower by 6.1% from its open following the earnings release to be 21.7% below its 200 day moving average of $67.02. Overall earnings estimates have been revised lower since the company's last earnings release. On Tuesday, June 4, 2019 there was some notable buying of 1,012 contracts of the $50.00 put expiring on Friday, June 28, 2019. Option traders are pricing in a 3.0% move on earnings and the stock has averaged a 6.2% move in recent quarters.
Constellation Brands, Inc. (STZ) is confirmed to report earnings at approximately 7:30 AM ET on Friday, June 28, 2019. The consensus earnings estimate is $2.09 per share on revenue of $2.06 billion and the Earnings Whisper ® number is $2.16 per share. Investor sentiment going into the company's earnings release has 73% expecting an earnings beat. Consensus estimates are for earnings to decline year-over-year by 5.00% with revenue decreasing by 7.62%. Short interest has increased by 66.1% since the company's last earnings release while the stock has drifted higher by 2.9% from its open following the earnings release to be 3.0% below its 200 day moving average of $189.32. Overall earnings estimates have been revised lower since the company's last earnings release. On Wednesday, June 12, 2019 there was some notable buying of 1,200 contracts of the $110.00 put expiring on Friday, January 17, 2020. Option traders are pricing in a 3.2% move on earnings and the stock has averaged a 6.0% move in recent quarters.
Lennar Corp. (LEN) is confirmed to report earnings at approximately 6:00 AM ET on Tuesday, June 25, 2019. The consensus earnings estimate is $1.13 per share on revenue of $5.11 billion and the Earnings Whisper ® number is $1.16 per share. Investor sentiment going into the company's earnings release has 54% expecting an earnings beat. Consensus estimates are for earnings to decline year-over-year by 28.48% with revenue decreasing by 6.39%. Short interest has decreased by 3.6% since the company's last earnings release while the stock has drifted higher by 0.7% from its open following the earnings release to be 9.6% above its 200 day moving average of $46.84. Overall earnings estimates have been revised lower since the company's last earnings release. On Wednesday, June 19, 2019 there was some notable buying of 7,349 contracts of the $52.50 call expiring on Friday, July 19, 2019. Option traders are pricing in a 6.4% move on earnings and the stock has averaged a 5.1% move in recent quarters.
FactSet Research Systems, Inc. (FDS) is confirmed to report earnings at approximately 7:00 AM ET on Tuesday, June 25, 2019. The consensus earnings estimate is $2.37 per share on revenue of $358.95 million and the Earnings Whisper ® number is $2.39 per share. Investor sentiment going into the company's earnings release has 47% expecting an earnings beat. Consensus estimates are for year-over-year earnings growth of 8.72% with revenue increasing by 5.60%. Short interest has increased by 37.7% since the company's last earnings release while the stock has drifted higher by 26.3% from its open following the earnings release to be 25.6% above its 200 day moving average of $237.31. Overall earnings estimates have been revised higher since the company's last earnings release. On Tuesday, June 18, 2019 there was some notable buying of 2,350 contracts of the $280.00 put expiring on Friday, July 19, 2019. Option traders are pricing in a 5.7% move on earnings and the stock has averaged a 4.9% move in recent quarters.
Paychex, Inc. (PAYX) is confirmed to report earnings at approximately 8:30 AM ET on Wednesday, June 26, 2019. The consensus earnings estimate is $0.65 per share on revenue of $979.93 million and the Earnings Whisper ® number is $0.66 per share. Investor sentiment going into the company's earnings release has 48% expecting an earnings beat. Consensus estimates are for year-over-year earnings growth of 6.56% with revenue increasing by 12.49%. Short interest has decreased by 0.8% since the company's last earnings release while the stock has drifted higher by 9.1% from its open following the earnings release to be 16.0% above its 200 day moving average of $74.61. Overall earnings estimates have been revised higher since the company's last earnings release. On Thursday, June 13, 2019 there was some notable buying of 2,024 contracts of the $90.00 call expiring on Friday, September 20, 2019. Option traders are pricing in a 4.0% move on earnings and the stock has averaged a 1.3% move in recent quarters.
Wall Street Week Ahead for the trading week beginning July 22nd, 2019
Good morning and happy Saturday to all of you here on wallstreetbets. I hope everyone on this subreddit made out pretty nicely in the market this past week, and is ready for the new trading week ahead. Here is everything you need to know to get you ready for the trading week beginning July 22nd, 2019.
Week ahead: Earnings, GDP expected to show sluggish growth as investors await rate cut - (Source)
Sluggish economic and earnings growth will be a theme in markets in the week ahead, as investors await a Fed interest rate cut at the end of the month. More than a quarter of the S&P 500 companies report earnings in the coming week, the second big week of the second quarter reporting season. FAANG names, like Alphabet and Amazon, and blue chips from McDonald’s to Boeingand United Technologies are among the more than 130 companies reporting. There is also some key economic data, including Friday’s second quarter GDP, which should show a slowing to 1.8% from the first quarter’s 3.1% pace, according to Refinitiv. On Thursday, durable goods are reported and will include an update on businesses investment. There are also existing home sales Tuesday, new home sales Wednesday and advance economic indicators Thursday. But there will be no Fed speakers, after a parade of central bank officials in the past week, including Fed Chair Jerome Powell. The most impactful comments, however, came Thursday from New York Fed President John Williams, who set off a debate about how much the Fed could cut rates at its July 30-31 meeting — 25 or 50 basis points. Even as the New York Fed later said Williams comments were not about current policy, market pros took heed of his words about how central bankers should “act quickly.” Fed dominates Fed officials do not speak publicly in the days ahead of policy meetings, but market pros will find plenty to debate. Fed funds futures were predicting a 43% chance of a 50 basis point cut in July, after shooting as high as 70% Thursday afternoon. “For sure, the Fed is going to dominate for next week. I think we’ll get at least a 25 basis point cut. I’m thinking we’re not going to get 50 basis point cut...The Fed has been burned when it’s been bold,” said Tony Roth, chief investment officer at Wilmington Trust. Roth said he believes the market is already pricing in a quarter-point cut, and he does not see the Fed’s rate cut as much of a longer-term catalyst for stocks. If it trims by a half percentage point, he expects just a short-term pop. Economists believe the Fed will cut interest rates even though recent data has improved. That’s in part because Powell has stressed the Fed is focused on the global economic slowdown, trade wars and low inflation, and that it will do what it takes to keep the economy expanding. “The only real catalyst that would really help the market would be if there was a trade deal with China,” Roth said. “I think the likelihood of that is less than > 10%. We’re very pessimistic on the possibility of a real deal with China prior to the [2020 presidential] election.” So, in the void ahead of the Fed’s meeting, the market will be watching earnings. As earnings rolled out this past week, stocks took a rest from their record-setting streak, as some companies lowered forecasts and most beat earnings and revenue estimates. As of Friday morning, 77% of the roughly 80 companies reporting had beaten earnings estimates, and 65% topped revenue forecasts, according to Refinitiv. Based on actual reports and forecasts, earnings per share for the S&P companies are expected to be up 1% in the second quarter. That is up from expectations that the profit growth would be slightly negative this quarter. “If you look at the numbers, we’re above the averages for top and bottom line beats, but at the same time when you look at revisions, every day we’re getting revisions for third and fourth quarter, and they’re coming down.There’s a real worry of an earnings recession, when you get out into the third and fourth quarter and out to next year,” Roth said. Roth said he’s currently neutral on risk assets, and he sees a slowdown brewing in the smallest U.S. companies that could spread up the food chain. “We do see those fundamental cracks in the economy in small business and the small business labor market, and on top of that you have these big macro risks out there,” such as trade and the upcoming election, Roth said. Slower economy As earnings growth was muted in the second quarter, so was the pace of economic gains. If growth comes in as expected, it would be the first quarter where growth was under 2% since the first quarter of 2017. Economists are watching to see how consumer spending fared in the quarter, after a recent pickup and also whether business inventories are declining. “The data we need is not Q2. What’s at risk is the growth and magnitude of the Fed rate cut. I don’t think Q2 is going to have much impact on the Fed’s thinking,” said Marc Chandler, chief market strategist at Bannockburn Global Forex. “It’s really how Q3 is progressing. It seems to me the economy softened in April and May and picked up in June with jobs data, retail sales and manufacturing sector.” Chandler said investors will also be focused on the European Central Bank, which some economists believe could cut its overnight deposit rate to negative 0.5% from negative 0.4% currently when it meets Thursday. Chandler said odds are about 50% for the rate cut, which many also expect in September. “While we’re waiting for the Fed to figure out whether it’s 25 or 50 basis points, and we’re waiting for the ECB to get all its forms sorted out ... the emerging markets are pushing ahead,” said Chandler, noting Russia and Turkey could cut rates in the next several days, after similar moves in the past week by South Africa, South Korea and Indonesia. “It just makes the story more global. You’re seeing the trade numbers from China, Japan, Singapore and South Korea weaken. You’re seeing exports form China suffer. Exports from all of Asia are suffering,” he said. “The big surprise for China and Japan has also been on the import side. The declines in their imports is really someone else’s [drop in] exports.” Rate cuts and currency wars Dollar strength has been a consequence of the trade war, and Fed action could help turn it around. “If the Fed fails to move, you’re going to end up with an increasingly stronger dollar,” which impacts corporate earnings, Roth said. “The dollar is quite strong and is increasingly going to be a headwind for U.S. companies. It hasn’t appreciated that much in 12 months, but if we see a divergence in monetary policy between the U.S. and the rest of the world, you would see a carry trade develop where people would want to buy assets in the U.S.,” he said. The dollar index was slightly higher on the week, but Wall Street has been focused on President Donald Trump’s negative comments on the currency’s strength. As Trump has criticized the Fed, he also complains that other central banks manipulate their currencies to give them an edge in trade. Trump has said the Fed should already be cutting rates, something it hasn’t done since December 2008. A number of Wall Street strategists have said they now believe it is possible that the U.S. government could intervene to weaken the dollar, but that would be unlikely.
This past week saw the following moves in the S&P:
Lagging Small-caps: Seasonal and Economic Factors Weigh
Small-caps measured by the performance of the Russell 2000 have been lagging since mid-March with the gap in performance widening in June and continuing into July. At yesterday’s close the Russell 2000 was up 15.35% year-to-date compared to a gain of 19.87% for the Russell 1000. Based upon historical trends this is not unusual for this time of the year nor during times when U.S. economic data is mixed. In the following chart the one-year seasonal pattern of the Russell 2000/Russell 1000 has been plotted (solid black line with grey fill) along with 2019 year-to-date (blue line). This chart is similar to the chart found on page 110 of the 2019 Stock Trader’s Almanac. When the lines are rising small-caps are outperforming, when the lines are falling small-caps are lagging. Small-caps exhibited typical seasonal strength during the first quarter but have been fading ever since. In some years, small-cap strength can last until mid-June however, that is not the case this year. Going forward, small-cap underperformance is likely to persist until early in the fourth quarter with possible a hint of strength at the end of August.
It’s usually about this time of the year, when trading volumes begin to slump and markets meander that we begin to hear talk of the infamous “Summer Rally” featured on page 74 of the Stock Trader’s Almanac 2019. The “Summer Rally” is usually the weakest seasonal rally of them all. We looked at the current Summer Rally and found it to be above average already, up 10.2% from the Spring low on May 31, and that does portend well for the Summer and Fall Corrections. We lined up the Summer Rallies ranked from weakest to strongest since 1964. Over the past 55 years prior to this year DJIA has rallied and average of 9.1% from its May/June low until its Q3 high. The Fall Rally averages 10.9% and the Summer and Fall Corrections average a loss of just under 9% for a net average gain of a few percentage points over the summer and fall. As shown in the table below, when the Summer Rally is greater than or equal to the 55-year 9.1% average, the summer and fall correction tend to be bit milder, -6.2% and -8.2%, respectively. Summer Rally gains beyond 12.5% historically had the smallest summer and fall corrections. One prominent exception being 1987.
Earnings (and Guidance) Likely to Make or Break the Rally
Once again today, DJIA, S&P 500 and NASDAQ closed at new all-time highs. With today’s modest gains, DJIA is up 17.3% year-to-date. S&P 500 is even better at 20.2% while NASDAQ is still best at 24.5%. Compared to historical average performance in pre-election years at this time of the year, DJIA and S&P 500 are comfortably above average. NASDAQ’s impressive 24.5% gain is just average (since 1971). NASDAQ’s Midyear Rally delivered again, but officially ended last Friday. The seasonal pattern charts, above and below, along with July’s typical performance over the last 21 years suggest further gains during the balance of July and the third quarter could be limited. For the market to make meaningful gains in the near-term earnings will need to decent and forward guidance will also need to be firm.
Yesterday was another one of those days that makes you scratch your head. In a relatively busy day for economic data, Initial Jobless Claims came in within 25K of a 50-year low, and the Philly Fed Manufacturing report saw its largest m/m increase in a decade. That follows other data last week where Retail Sales were very strong and CPI and PPI both came in ahead of consensus forecasts. The trend of better than expected data since the June employment report on July 5th is reflected in recent moves of the Citi Economic Surprise Index which has rallied from -68.3 up to -41.5. Granted, it’s still negative, but what was looking like a real dismal backdrop for the economy just three weeks ago seems to be showing signs of improvement.
On top of the economic data, two notable interviews from FOMC officials Williams from New York and Vice Chair Clarida moved markets. Given the strong tone of economic data, one would expect both officials to try and tone down rising market expectations regarding any aggressive policy moves at the July meeting. Well, markets don’t always make sense. In their respective interviews, both Williams and Clarida not only didn’t tone down expectations, but they added fuel to the fire. Williams noted that “it pays to act quickly to lower rates" and "vaccinate” the economy "against further ills." Clarida was even more direct when he said that “Research shows you act preemptively when you can.” In other words, the data-dependent Fed is casting the data aside and ready to move anyway. In his interview on Fox Business, Clarida almost got a chuckle when asked whether there was any chance the Fed wouldn’t cut rates in July. The dovish turn from the Fed was immediately reflected in market expectations for rate policy at the July meeting. Back in June, market expectations for a 50 basis points (bps) cut at the next meeting peaked out at under 50%. Then, in the days following the June employment report, expectations dropped all the way down to 3%. In the last ten days, though, the trend has completely reversed, and as of yesterday’s close topped out at 71% versus just a 29% chance for a 25 bps cut. Probabilities for a 50 bps cut came in a bit overnight but are still at about 50/50. Yesterday alone, though, expectations for a 25 bps cut and a 50 bps cut more than completely reversed from the prior day, and remember, that’s after what was a good day of economic data! Can you imagine what expectations would be like if the data was actually bad?
The Bloomberg World index is a cap-weighted index made up of nearly 5,000 stocks from around the world (including US stocks). While the S&P 500 has been hitting new all-time highs over the last week, the Bloomberg World index remains 7% below highs that it last made back in January 2018.
Below is a chart showing the ratio of the S&P 500 to the Bloomberg World index since the World index's inception back in August 2003. While the World index outperformed the US for five years in the mid-2000s, the US has been outperforming since the end of 2007, which includes both the Financial Crisis and the bull market that has been in place since the 2009 lows.
Along with the relative strength chart between the two indices above, below we show the price change of the S&P 500 versus the Bloomberg World index since August 2003. Through today, the S&P was up 203% versus a gain of 142% for the Bloomberg World index.
Since the November 2016 election, the S&P 500 is up 40% versus a gain of 26% for the Bloomberg World index. Notably, the World index kept up with the S&P through early 2018, but weakness for the World index in mid-2018 and a failure to bounce back as much as the US this year has left the World index well behind.
The S&P 500 is up over 20% YTD, but over the last 12 months, it is up just under 10% on a total return basis. And within the S&P 1500, there are only 44 stocks that are up more than 50% on a total return basis over the last 12 months. These 44 stocks are listed below. Innovative Industrials (IIPR) -- a cannabis REIT -- has been the best performing stock in the S&P 1500 over the last year with a total return of 302%. In second place is eHealth (EHTH) with a gain of 269%, followed by Avon Products (AVP) at +174.8% and Coca-Cola Bottling (COKE) at +128.58%. Coca-Cola Bottling is probably one of the last names you would have guessed as a top five performer over the last year! Other notables on the list of biggest winners include Advanced Micro (AMD), LendingTree (TREE), Starbucks (SBUX), AutoZone (AZO), Chipotle (CMG), Hershey (HSY), and Procter & Gamble (PG). Some names that aren't on the list that you may have expected to see? AMZN, NFLX, MSFT? Nope. None of the mega-cap Tech companies are on the list of biggest winners due to serious weakness from this group in Q4 2018.
Although the last two trading days have seen exceptionally narrow daily ranges, today we wanted to take a quick look at the S&P 500's frequency of 2% daily moves (either up or down) in the post-WWII period. The chart below breaks out the frequency of 2% days by year, and years with more than 25 one-day moves of 2% are notated accordingly. Overall, there have been an average of 11 daily 2% moves in a given year. After five straight years from 2007 to 2011 where we saw an above-average number of 2% days, the last seven years have only seen one year with an above-average number of occurrences (2018, 21). Remember, in 2017 there wasn't one single trading day that saw the S&P move up or down 2%! So far this year, there have only been four 2% days, but with the most volatile part of the year on tap, we are likely to see that number increase in the months ahead. Don't expect the relative calm that we have seen in the last few trading days to last forever. Volatility is unpredictable and usually comes up and surprises you when you least expect it!
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Amazon.com, Inc. $1,964.52
Amazon.com, Inc. (AMZN) is confirmed to report earnings at approximately 4:00 PM ET on Thursday, July 25, 2019. The consensus earnings estimate is $5.29 per share on revenue of $62.51 billion and the Earnings Whisper ® number is $5.70 per share. Investor sentiment going into the company's earnings release has 78% expecting an earnings beat. Consensus estimates are for year-over-year earnings growth of 4.34% with revenue increasing by 18.20%. Short interest has increased by 14.0% since the company's last earnings release while the stock has drifted higher by 1.8% from its open following the earnings release to be 13.0% above its 200 day moving average of $1,737.93. Overall earnings estimates have been revised lower since the company's last earnings release. On Thursday, July 11, 2019 there was some notable buying of 3,494 contracts of the $2,000.00 call expiring on Friday, August 16, 2019. Option traders are pricing in a 4.4% move on earnings and the stock has averaged a 4.0% move in recent quarters.
Facebook Inc. (FB) is confirmed to report earnings at approximately 4:05 PM ET on Wednesday, July 24, 2019. The consensus earnings estimate is $1.90 per share on revenue of $16.45 billion and the Earnings Whisper ® number is $2.01 per share. Investor sentiment going into the company's earnings release has 82% expecting an earnings beat. Consensus estimates are for year-over-year earnings growth of 9.20% with revenue increasing by 24.33%. Short interest has increased by 21.7% since the company's last earnings release while the stock has drifted higher by 0.7% from its open following the earnings release to be 20.8% above its 200 day moving average of $164.17. Overall earnings estimates have been revised higher since the company's last earnings release. On Wednesday, July 17, 2019 there was some notable buying of 16,697 contracts of the $290.00 call expiring on Friday, September 20, 2019. Option traders are pricing in a 6.5% move on earnings and the stock has averaged a 8.6% move in recent quarters.
Tesla, Inc. (TSLA) is confirmed to report earnings at approximately 5:15 PM ET on Wednesday, July 24, 2019. The consensus estimate is for a loss of $0.52 per share on revenue of $6.38 billion and the Earnings Whisper ® number is ($0.44) per share. Investor sentiment going into the company's earnings release has 33% expecting an earnings beat. Consensus estimates are for year-over-year earnings growth of 84.80% with revenue increasing by 59.41%. Short interest has increased by 26.5% since the company's last earnings release while the stock has drifted higher by 1.2% from its open following the earnings release to be 8.1% below its 200 day moving average of $280.96. Overall earnings estimates have been revised higher since the company's last earnings release. On Tuesday, July 16, 2019 there was some notable buying of 30,445 contracts of the $50.00 put expiring on Friday, August 16, 2019. Option traders are pricing in a 7.8% move on earnings and the stock has averaged a 7.4% move in recent quarters.
Boeing Co. (BA) is confirmed to report earnings at approximately 7:30 AM ET on Wednesday, July 24, 2019. The consensus earnings estimate is $1.89 per share on revenue of $20.27 billion and the Earnings Whisper ® number is $1.91 per share. Investor sentiment going into the company's earnings release has 17% expecting an earnings beat. Consensus estimates are for earnings to decline year-over-year by 43.24% with revenue decreasing by 16.44%. Short interest has increased by 11.2% since the company's last earnings release while the stock has drifted lower by 0.1% from its open following the earnings release to be 4.0% above its 200 day moving average of $362.82. Overall earnings estimates have been revised lower since the company's last earnings release. On Monday, July 8, 2019 there was some notable buying of 6,176 contracts of the $325.00 put expiring on Friday, August 16, 2019. Option traders are pricing in a 3.8% move on earnings and the stock has averaged a 3.0% move in recent quarters.
AT&T Corp. (T) is confirmed to report earnings at approximately 6:50 AM ET on Wednesday, July 24, 2019. The consensus earnings estimate is $0.89 per share on revenue of $45.02 billion and the Earnings Whisper ® number is $0.90 per share. Investor sentiment going into the company's earnings release has 66% expecting an earnings beat. Consensus estimates are for earnings to decline year-over-year by 2.20% with revenue increasing by 15.48%. Short interest has increased by 16.4% since the company's last earnings release while the stock has drifted higher by 5.5% from its open following the earnings release to be 4.5% above its 200 day moving average of $31.37. Overall earnings estimates have been revised lower since the company's last earnings release. On Monday, July 8, 2019 there was some notable buying of 144,398 contracts of the $28.00 call expiring on Friday, January 17, 2020. Option traders are pricing in a 4.1% move on earnings and the stock has averaged a 4.5% move in recent quarters.
Snap Inc. (SNAP) is confirmed to report earnings at approximately 4:10 PM ET on Tuesday, July 23, 2019. The consensus estimate is for a loss of $0.10 per share on revenue of $358.48 million and the Earnings Whisper ® number is ($0.08) per share. Investor sentiment going into the company's earnings release has 61% expecting an earnings beat The company's guidance was for revenue of $335.00 million to $360.00 million. Consensus estimates are for year-over-year earnings growth of 9.09% with revenue increasing by 36.69%. Short interest has decreased by 3.8% since the company's last earnings release while the stock has drifted higher by 13.5% from its open following the earnings release to be 36.9% above its 200 day moving average of $10.24. Overall earnings estimates have been revised lower since the company's last earnings release. On Friday, July 5, 2019 there was some notable buying of 7,449 contracts of the $19.00 call expiring on Friday, July 26, 2019. Option traders are pricing in a 13.7% move on earnings and the stock has averaged a 19.1% move in recent quarters.
ShiftPixy, Inc. (PIXY) is confirmed to report earnings at approximately 8:00 AM ET on Monday, July 22, 2019. The consensus estimate is for a loss of $0.08 per share on revenue of $14.39 million. Investor sentiment going into the company's earnings release has 44% expecting an earnings beat. Consensus estimates are for earnings to decline year-over-year by 33.33% with revenue increasing by 53.48%. Short interest has decreased by 8.2% since the company's last earnings release while the stock has drifted lower by 50.9% from its open following the earnings release to be 63.8% below its 200 day moving average of $1.74. Overall earnings estimates have been revised higher since the company's last earnings release. The stock has averaged a 16.9% move on earnings in recent quarters.
Halliburton Company (HAL) is confirmed to report earnings at approximately 6:45 AM ET on Monday, July 22, 2019. The consensus earnings estimate is $0.30 per share on revenue of $5.97 billion and the Earnings Whisper ® number is $0.29 per share. Investor sentiment going into the company's earnings release has 60% expecting an earnings beat. Consensus estimates are for earnings to decline year-over-year by 48.28% with revenue decreasing by 2.88%. Short interest has increased by 39.2% since the company's last earnings release while the stock has drifted lower by 31.6% from its open following the earnings release to be 25.7% below its 200 day moving average of $29.27. Overall earnings estimates have been revised lower since the company's last earnings release. On Tuesday, July 16, 2019 there was some notable buying of 9,264 contracts of the $20.00 put expiring on Friday, August 16, 2019. Option traders are pricing in a 5.3% move on earnings and the stock has averaged a 3.5% move in recent quarters.
Twitter, Inc. (TWTR) is confirmed to report earnings at approximately 7:00 AM ET on Friday, July 26, 2019. The consensus earnings estimate is $0.19 per share on revenue of $828.49 million and the Earnings Whisper ® number is $0.24 per share. Investor sentiment going into the company's earnings release has 75% expecting an earnings beat The company's guidance was for revenue of $770.00 million to $830.00 million. Consensus estimates are for earnings to decline year-over-year by 0.00% with revenue increasing by 16.60%. Short interest has increased by 9.0% since the company's last earnings release while the stock has drifted lower by 0.4% from its open following the earnings release to be 10.1% above its 200 day moving average of $33.39. Overall earnings estimates have been revised higher since the company's last earnings release. On Monday, July 15, 2019 there was some notable buying of 7,151 contracts of the $60.00 call expiring on Friday, January 15, 2021. Option traders are pricing in a 10.4% move on earnings and the stock has averaged a 12.7% move in recent quarters.
Visa Inc (V) is confirmed to report earnings at approximately 4:05 PM ET on Tuesday, July 23, 2019. The consensus earnings estimate is $1.33 per share on revenue of $5.70 billion and the Earnings Whisper ® number is $1.37 per share. Investor sentiment going into the company's earnings release has 79% expecting an earnings beat. Consensus estimates are for year-over-year earnings growth of 10.83% with revenue increasing by 8.78%. Short interest has decreased by 6.9% since the company's last earnings release while the stock has drifted higher by 11.7% from its open following the earnings release to be 19.5% above its 200 day moving average of $150.03. Overall earnings estimates have been revised higher since the company's last earnings release. On Tuesday, July 16, 2019 there was some notable buying of 4,839 contracts of the $165.00 put expiring on Friday, August 16, 2019. Option traders are pricing in a 3.1% move on earnings and the stock has averaged a 2.6% move in recent quarters.
I was going through old emails today and came across this one I sent out to family on January 4, 2018. It was a reflection on the 2017 crypto bull market and where I saw it heading, as well as some general advice on crypto, investment, and being safe about how you handle yourself in cryptoland. I feel that we are on the cusp of a new bull market right now, so I thought that I would put this out for at least a few people to see *before* the next bull run, not after. While the details have changed, I don't see a thing in this email that I fundamentally wouldn't say again, although I'd also probably insist that people get a Yubikey and use that for all 2FA where it is supported. Happy reading, and sorry for some of the formatting weirdness -- I cleaned it up pretty well from the original email formatting, but I love lists and indents and Reddit has limitations... :-/ Also, don't laught at my token picks from January 2018! It was a long time ago and (luckliy) I took my own advice about moving a bunch into USD shortly after I sent this. I didn't hit the top, and I came back in too early in the summer of 2018, but I got lucky in many respects. ----------------------------------------------------------------------- Jan-4, 2018 Hey all! I woke up this morning to ETH at a solid $1000 and decided to put some thoughts together on what I think crypto has done and what I think it will do. *******, if you could share this to your kids I’d appreciate it -- I don’t have e-mail addresses, and it’s a bit unwieldy for FB Messenger… Hopefully they’ll at least find it thought-provoking. If not, they can use it as further evidence that I’m a nutjob. 😉 Some history before I head into the future. I first mined some BTC in 2011 or 2012 (Can’t remember exactly, but it was around the Christmas holidays when I started because I had time off from work to get it set up and running.) I kept it up through the start of summer in 2012, but stopped because it made my PC run hot and as it was no longer winter, ********** didn’t appreciate the sound of the fans blowing that hot air into the room any more. I’ve always said that the first BTC I mined was at $1, but looking back at it now, that’s not true – It was around $2. Here’s a link to BTC price history. In the summer of 2013 I got a new PC and moved my programs and files over before scrapping the old one. I hadn’t touched my BTC mining folder for a year then, and I didn’t even think about salvaging those wallet files. They are now gone forever, including the 9-10BTC that were in them. While I can intellectually justify the loss, it was sloppy and underlines a key thing about cryptocurrency that I believe will limit its widespread adoption by the general public until it is addressed and solved: In cryptoland, you are your own bank, and if you lose your password or account number, there is no person or organization that can help you reset it so that you can get access back. Your money is gone forever. On April 12, 2014 I bought my first BTC through Coinbase. BTC had spiked to $1000 and been in the news, at least in Japan. This made me remember my old wallet and freak out for a couple of months trying to find it and reclaim the coins. I then FOMO’d (Fear Of Missing Out”) and bought $100 worth of BTC. I was actually very lucky in my timing and bought at around $430. Even so, except for a brief 50% swing up almost immediately afterwards that made me check prices 5 times a day, BTC fell below my purchase price by the end of September and I didn’t get back to even until the end of 2015. In May 2015 I bought my first ETH at around $1. I sent some guy on bitcointalk ~$100 worth of BTC and he sent me 100 ETH – all on trust because the amounts were small and this was a small group of people. BTC was down in the $250 range at that point, so I had lost 30-40% of my initial investment. This was of the $100 invested, so not that much in real terms, but huge in percentages. It also meant that I had to buy another $100 of BTC on Coinbase to send to this guy. A few months after I purchased my ETH, BTC had doubled and ETH had gone down to $0.50, halving the value of my ETH holdings. I was even on the first BTC purchase finally, but was now down 50% on the ETH I had bought. The good news was that this made me start to look at things more seriously. Where I had skimmed white papers and gotten a superficial understanding of the technology before FOMO’ing, I started to act as an investor, not a speculator. Let me define how I see those two different types of activity:
Investors buy because the price is less than the value they see in the investment. Speculators buy because they think that someone will pay more in the future than they are paying now.
Investors trade on information (The white paper was really well-written, had a clear technical advantage over other alternatives, and addresses a need that I can understand and value.) Speculators trade on sentiment. (Buy the rumor! Sell the news!)
Investors usually look at the investment and themselves and can describe why they purchase in those terms (ABC-Coin provides (service) that isn’t addressed yet and matches (requirements) for an investment.) Speculators usually describe why they bought something in terms of how other people think (I think that other people think that the price will rise, so I want to get ahead of that.)
Investors don’t necessarily check the price every day. The can, and very often I do, but it isn’t required because fundamentals don’t often change on a dime. Speculators need to be glued to a price feed, because sentiment very often changes on a dime.
Investors like ideas, people, business plans, and market opportunities. Good ones are like Spock. Speculators like trends. They are tribal.
Investors have a longer time horizon than speculators. In cryptoland, the notion of a “longer” time horizon is still laughably small (months) compared to traditional markets, but it certainly isn’t weeks or days or hours, which is whre speculators often live.
So what has been my experience as an investor? After sitting out the rest of 2015 because I needed to understand the market better, I bought into ETH quite heavily, with my initial big purchases being in March-April of 2016. Those purchases were in the $11-$14 range. ETH, of course, dropped immediately to under $10, then came back and bounced around my purchase range for a while until December of 2016, when I purchased a lot more at around $8. I also purchased my first ICO in August of 2016, HEAT. I bought 25ETH worth. Those tokens are now worth about half of their ICO price, so about 12.5ETH or $12500 instead of the $25000 they would be worth if I had just kept ETH. There are some other things with HEAT that mean I’ve done quite a bit better than those numbers would suggest, but the fact is that the single best thing I could have done is to hold ETH and not spend the effort/time/cost of working with HEAT. That holds true for about every top-25 token on the market when compared to ETH. It certainly holds true for the many, many tokens I tried to trade in Q1-Q2 of 2017. In almost every single case I would have done better and slept better had I just held ETH instead of trying to be smarter than Mr. Market. But, I made money on all of them except one because the crypto market went up more in USD terms than any individual coin went down in ETH or BTC terms. This underlines something that I read somewhere and that I take to heart: A rising market makes everyone seem like a genius. A monkey throwing darts at a list of the top 100 cryptocurrencies last year would have doubled his money. Here’s a chart from September that shows 2017 year-to-date returns for the top 10 cryptocurrencies, and all of them went up a *lot* more between then and December. A monkey throwing darts at this list there would have quintupled his money. When evaluating performance, then, you have to beat the monkey, and preferably you should try to beat a Wall Street monkey. I couldn’t, so I stopped trying around July 2017. My benchmark was the BLX, a DAA (Digital Asset Array – think fund like a Fidelity fund) created by ICONOMI. I wasn’t even close to beating the BLX returns, so I did several things.
I went from holding about 25 different tokens to holding 10 now. More on that in a bit.
I used those funds to buy ETH and BLX. ETH has done crazy-good since then and BLX has beaten BTC handily, although it hasn’t done as well as ETH.
I used some of those funds to set up an arbitrage operation.
The arbitrage operation is why I kept the 11 tokens that I have now. All but a couple are used in an ETH/token pair for arbitrage, and each one of them except for one special case is part of BLX. Why did I do that? I did that because ICONOMI did a better job of picking long-term holds than I did, and in arbitrage the only speculative thing you must do is pick the pairs to trade. My pairs are (No particular order):
I also hold PLU, PLBT, and ART. These two are multi-year holds for me. I have not purchased BTC once since my initial $200, except for a few cases where BTC was the only way to go to/from an altcoin that didn’t trade against ETH yet. Right now I hold about the same 0.3BTC that I held after my first $100 purchase, so I don’t really count it. Looking forward to this year, I am positioning myself as follows:
ETH will still be my core holding. It is the “deepest in the stack” crypto investment that I have. “Deep in the stack” is a programming term that gets at the idea that most software is built on other software. If you just think about your notebook, you have your OS, and programs run on that. But even inside the OS there is a stack. The bottom of your stack is the kernel, and on top of that are the drivers, protocols, and other layers that allow the programs to talk to the OS, the hard drive, the screen, the mouse, your printer, etc. You can change your mouse or printer easily. Changing things deeper in the stack becomes harder and harder. ETH is deep in the crypto stack, so is very hard to dislodge – Around 60 of the top 100 cryptocurrencies by market cap run on top of Ethereum, so getting rid of Ethereum is something that would take a long time to do.
DNT, QTUM, ZRX, and OMG are all, to varying degrees, “deep in the stack” tokens that, once established, will be very hard to dislodge.
That said, I am peeling away some of my holdings into USD right now, because big changes are afoot and they are going to cause market disruptions. I’m going to come right out and admit that this is speculative, but I’m also going to back it up with some non-speculative facts.
The SEC has been sending out hundreds of subpoenas to cryptocurrency organizations over the past 3-4 months. These subpoenas are simply asking for information and nobody has been charged with any crimes or misdoings, but it is clear that the SEC is getting together information so that they can begin to regulate cryptoland. When that happens, other countries will follow, and that means:
Some tokens will be deemed outright scams and people will be prosecuted.
Some tokens will be deemed securities and will be regulated.
Some tokens will not be deemed scams or securities and will continue as they have.
Looking at this, it is clear to me that the tokens that escape prosecution and regulation should do better, but the short-term impact will be brutal and ugly. It would not surprise me at all to see a 50% drop in overall market cap within Q1-Q2, with Q1 being more likely.
Cryptoland has always been a bit nuts, but it is more nuts now than I have ever seen it. Back in 2011-2014 it was a freaks-n-geeks show where people were all about the technology and I would sit around for a 3-day weekend installing a *nix VM on my Windows machine so that I could compile the most recent source and run a CUDA SHA-256 routine rather than thrash my CPU. If that doesn’t make sense to you, you wouldn’t have even thought about being involved.
Now, people see Bitcoin advertisements in their Facebook feed and think “I gotta get on the BTC train!” before going to Coinbase and buying some with a credit card. They don’t know anything about crypto, and they are getting eaten alive – It is no coincidence that BTC peaked after the Thanksgiving holidays when people sat around the table and Janice got Uncle Mike and Cousin Bob all excited as she talked about going to Cancun for Christmas because of her crypto winnings. Huge amounts of fiat got transferred from newbies to BTC whales during this period, and once the whales were done, BTC had dropped from $20,000 to $12,000. It’s now back at $15,000, but for people who bought at a higher level, this sucks. As a result many have moved from BTC to ETH, with the single biggest money flow in crypto in December being the BTC à ETH flow. As a result, it’s no coincidence that ETH is at all-time highs now. The thing is, though, that even most people that moved from BTC to ETH really have no idea what they are doing. They are acting on buzzwords and emotion. They are speculators and are going to get crushed.
The stock market is quite high right now, but people are starting to worry that it is too high and that we are going to enter into a period of inflation again. This has caused gold to go up a lot the last quarter and is likely also responsible a bit for the rise in cryptos. If this view is correct, then cryptos stay stronger than if that pressure wasn’t there. If wrong, then cryptos will swing down as money exits cryptoland for more traditional markets.
I am spending most of my time and money on the arbitrage effort. The nice thing about arbitrage is that it works as the markets go up, and it works as the markets go down. When markets are too volatile, however, arbitrage can get very messy and dangerous, with each trade generating a loss instead of a profit, so I am working right now to tune the algorithms to take into account rate-of-change and add in some circuit breaker triggers. Once this is done I will expand those operations.
I am getting much more serious about systems security.
I have a Nano Ledger and recommend that anyone with >$1000 of crypto have one. The Trezor is also supposed to be good, but I haven’t used it.
I will set up a dedicated *nix notebook that is used for nothing except my crypto work. All it takes is one keylogger to get on your PC/Mac and your crypto is gone. What is on your Nano Ledger will be OK, but they will sweep out your exchange account or Coinbase account faster than you can type. A standard Linux installation with Chrome and nothing else is as about as secure as you can get in the civilian world.
If you don’t use LastPass or a similar password manager yet, you need to do that. Your password to LastPass should be at least 16 characters long and should not have a recognizable English word in it. If you think that “Iluvu4evah” is a secure password, you’re wrong.
Hackers know that “4”=”for” and “u”=”you”. Writing a script to substitute those in is trivial if they want to write the script, but it’s much easier for them to download one of the many, many programs out there that already do this.
If your password contains any string of numbers from anything that can be associated with you at any time in your life, it is insecure. Take those numbers out of the character count because they are an insignificant barrier to cracking your account.
The good news is that you probably won’t be targeted, but if you ever mention online that you are doing anything significant in crypto, that chance increased enormously.
*Never* talk with *anyone* about how much you have in crypto. You’ll notice that I haven’t here. There is no reason to tell even a family member how much you have unless you are sharing a tax form. Sure, you may trust them, but all it takes if for someone to overhead someone else mention at a party that a relative got into crypto a long time ago and made a bunch of money. That person can also then be subjected to the $10 hack and force you to send all your crypto to them.
Your password to LastPass (Or equivalent.) should look something like this -> 6k0jQMoziX&D#4W8
Yes, it’s a headache. Imagine your headache, though, were you to open your account one day and find all of your money gone.
Looking at my notes, I have two other things that I wanted to work into this email that I didn’t get to, so here they are:
Just like with free apps and other software, if you are getting something of value and you didn’t pay anything for it, you need to ask why this is. With apps, the phrase is “If you didn’t pay for the product, you are the product”, and this works for things such as pump groups, tips, and even technical analysis. Here’s how I see it.
Technical analysis (TA) is something that has been argued about for longer than I’ve been alive, but I think that it falls into the same boat. In short, TA argues that there are patterns in trading that can be read and acted upon to signal when one must buy or sell. It has been used forever in the stock and foreign exchange markets, and people use it in crypto as well. Let’s break down these assumptions a bit.
i. First, if crypto were like the stock or forex markets we’d all be happy with 5-7% gains per year rather than easily seeing that in a day. For TA to work the same way in crypto as it does in stocks and foreign exchange, the signals would have to be *much* stronger and faster-reacting than they work in the traditional market, but people use them in exactly the same way. ii. Another area where crypto is very different than the stock and forex markets centers around market efficiency theory. This theory says that markets are efficient and that the price reflects all the available information at any given time. This is why gold in New York is similar in price to gold in London or Shanghai, and why arbitrage margins are easily <0.1% in those markets compared to cryptoland where I can easily get 10x that. Crypto simply has too much speculation and not enough professional traders in it yet to operate as an efficient market. That fundamentally changes the way that the market behaves and should make any TA patterns from traditional markets irrelevant in crypto. iii. There are services, both free and paid that claim to put out signals based on TA for when one should buy and sell. If you think for even a second that they are not front-running (Placing orders ahead of yours to profit.) you and the other people using the service, you’re naïve. iv. Likewise, if you don’t think that there are people that have but together computerized systems to get ahead of people doing manual TA, you’re naïve. The guys that I have programming my arbitrage bots have offered to build me a TA bot and set up a service to sell signals once our position is taken. I said no, but I am sure that they will do it themselves or sell that to someone else. Basically they look at TA as a tip machine where when a certain pattern is seen, people act on that “tip”. They use software to see that “tip” faster and take a position on it so that when slower participants come in they either have to sell lower or buy higher than the TA bot did. Remember, if you are getting a tip for free, you’re the product. In TA I see a system when people are all acting on free preset “tips” and getting played by the more sophisticated market participants. Again, you have to beat that Wall Street monkey.
If you still don’t agree that TA is bogus, think about it this way: If TA was real, Wall Street would have figured it out decades ago and we would have TA funds that would be beating the market. We don’t.
If you still don’t agree that TA is bogus and that its real and well, proven, then you must think that all smart traders use them. Now follow that logic forward and think about what would happen if every smart trader pushing big money followed TA. The signals would only last for a split second and would then be overwhelmed by people acting on them, making them impossible to leverage. This is essentially what the efficient market theory postulates for all information, including TA.
OK, the one last item. Read this weekly newsletter – You can sign up at the bottom. It is free, so they’re selling something, right? 😉 From what I can tell, though, Evan is a straight-up guy who posts links and almost zero editorial comments. Happy 2018.
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