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Former investment bank FX trader: news trading and second order thinking
Thanks to everyone who responded to the previous pieces on risk management. We ended up with nearly 2,000 upvotes and I'm delighted so many of you found it useful. This time we're going to focus on a new area: reacting to and trading around news and fundamental developments. A lot of people get this totally wrong and the main reason is that they trade the news at face value, without considering what the market had already priced in. If you've ever seen what you consider to be "good" or "better than forecast" news come out and yet been confused as the pair did nothing or moved in the opposite direction to expected, read on... We are going to do this in two parts. Part I
Why use an economic calendar
How to read the calendar
Knowing what's priced in
First order thinking vs second order thinking
Knowing how to use and benefit from the economic calendar is key for all traders - not just news traders. In this chapter we are going to take a practical look at how to use the economic calendar. We are also going to look at how to interpret news using second order thinking. The key concept is learning what has already been ‘priced in’ by the market so we can estimate how the market price might react to the new information.
Why use an economic calendar
The economic calendar contains all the scheduled economic releases for that day and week. Even if you purely trade based on technical analysis, you still must know what is in store. https://preview.redd.it/20xdiq6gq4k51.png?width=1200&format=png&auto=webp&s=6cd47186db1039be7df4d7ad6782de36da48f1db Why? Three main reasons. Firstly, releases can help provide direction. They create trends. For example if GBPUSD has been fluctuating aimlessly within a range and suddenly the Bank of England starts raising rates you better believe the British Pound will start to move. Big news events often start long-term trends which you can trade around. Secondly, a lot of the volatility occurs around these events. This is because these events give the market new information. Prior to a big scheduled release like the US Non Farm Payrolls you might find no one wants to take a big position. After it is released the market may move violently and potentially not just in a single direction - often prices may overshoot and come back down. Even without a trend this volatility provides lots of trading opportunities for the day trader. https://preview.redd.it/u17iwbhiq4k51.png?width=1200&format=png&auto=webp&s=98ea8ed154c9468cb62037668c38e7387f2435af Finally, these releases can change trends. Going into a huge release because of a technical indicator makes little sense. Everything could reverse and stop you out in a moment. You need to be aware of which events are likely to influence the positions you have on so you can decide whether to keep the positions or flatten exposure before the binary event for which you have no edge. Most traders will therefore ‘scan’ the calendar for the week ahead, noting what the big events are and when they will occur. Then you can focus on each day at a time.
Reading the economic calendar
Most calendars show events cut by trading day. Helpfully they adjust the time of each release to your own timezone. For example we can see that the Bank of Japan Interest Rate decision is happening at 4am local time for this particular London-based trader. https://preview.redd.it/lmx0q9qoq4k51.jpg?width=1200&format=pjpg&auto=webp&s=c6e9e1533b1ba236e51296de8db3be55dfa78ba1 Note that some events do not happen at a specific time. Think of a Central Banker’s speech for example - this can go on for an hour. It is not like an economic statistic that gets released at a precise time. Clicking the finger emoji will open up additional information on each event.
How do you define importance? Well, some events are always unimportant. With the greatest of respect to Italian farmers, nobody cares about mundane releases like Italian farm productivity figures. Other events always seem to be important. That means, markets consistently react to them and prices move. Interest rate decisions are an example of consistently high importance events. So the Medium and High can be thought of as guides to how much each event typically affects markets. They are not perfect guides, however, as different events are more or less important depending on the circumstances. For example, imagine the UK economy was undergoing a consumer-led recovery. The Central Bank has said it would raise interest rates (making GBPUSD move higher) if they feel the consumer is confident. Consumer confidence data would suddenly become an extremely important event. At other times, when the Central Bank has not said it is focused on the consumer, this release might be near irrelevant.
Knowing what's priced in
Next to each piece of economic data you can normally see three figures. Actual, Forecast, and Previous.
Actual refers to the number as it is released.
Forecast refers to the consensus estimate from analysts.
Previous is what it was last time.
We are going to look at this in a bit more detail later but what you care about is when numbers are better or worse than expected. Whether a number is ‘good’ or ‘bad’ really does not matter much. Yes, really. Once you understand that markets move based on the news vs expectations, you will be less confused by price action around events This is a common misunderstanding. Say everyone is expecting ‘great’ economic data and it comes out as ‘good’. Does the price go up? You might think it should. After all, the economic data was good. However, everyone expected it to be great and it was just … good. The great release was ‘priced in’ by the market already. Most likely the price will be disappointed and go down. By priced in we simply mean that the market expected it and already bought or sold. The information was already in the price before the announcement. Incidentally the official forecasts can be pretty stale and might not accurately capture what active traders in the market expect. See the following example.
An example of pricing in
For example, let’s say the market is focused on the number of Tesla deliveries. Analysts think it’ll be 100,000 this quarter. But Elon Musk tweets something that hints he’s really, really, really looking forward to the analyst call. Tesla’s price ticks higher after the tweet as traders put on positions, reflecting the sentiment that Tesla is likely to massively beat the 100,000. (This example is not a real one - it just serves to illustrate the concept.) Tesla deliveries are up hugely vs last quarter ... but they are disappointing vs market expectations ... what do you think will happen to the stock? On the day it turns out Tesla hit 101,000. A better than the officially forecasted result - sure - but only marginally. Way below what readers of Musk's twitter account might have thought. Disappointed traders may sell their longs and close out the positions. The stock might go down on ‘good’ results because the market had priced in something even better. (This example is not a real one - it just serves to illustrate the concept.)
We know that interest rates heavily affect currency prices. For major interest rate decisions there’s a great tool on the CME’s website that you can use. See the link for a demo This gives you a % probability of each interest rate level, implied by traded prices in the bond futures market. For example, in the case above the market thinks there’s a 20% chance the Fed will cut rates to 75-100bp. Obviously this is far more accurate than analyst estimates because it uses actual bond prices where market participants are directly taking risk and placing bets. It basically looks at what interest rate traders are willing to lend at just before/after the date of the central bank meeting to imply the odds that the market ascribes to a change on that date. Always try to estimate what the market has priced in. That way you have some context for whether the release really was better or worse than expected.
Second order thinking
You have to know what the market expects to try and guess how it’ll react. This is referred to by Howard Marks of Oaktree as second-level thinking. His explanation is so clear I am going to quote extensively. It really is hard to improve on this clarity of thought: First-level thinking is simplistic and superficial, and just about everyone can do it (a bad sign for anything involving an attempt at superiority). All the first-level thinker needs is an opinion about the future, as in “The outlook for the company is favorable, meaning the stock will go up.” Second-level thinking is deep, complex and convoluted. Howard Marks He explains first-level thinking: The first-level thinker simply looks for the highest quality company, the best product, the fastest earnings growth or the lowest p/e ratio. He’s ignorant of the very existence of a second level at which to think, and of the need to pursue it. Howard Marks The above describes the guy who sees a 101,000 result and buys Tesla stock because - hey, this beat expectations. Marks goes on to describe second-level thinking: The second-level thinker goes through a much more complex process when thinking about buying an asset. Is it good? Do others think it’s as good as I think it is? Is it really as good as I think it is? Is it as good as others think it is? Is it as good as others think others think it is? How will it change? How do others think it will change? How is it priced given: its current condition; how do I think its conditions will change; how others think it will change; and how others think others think it will change? And that’s just the beginning. No, this isn’t easy. Howard Marks In this version of events you are always thinking about the market’s response to Tesla results. What do you think they’ll announce? What has the market priced in? Is Musk reliable? Are the people who bought because of his tweet likely to hold on if he disappoints or exit immediately? If it goes up at which price will they take profit? How big a number is now considered ‘wow’ by the market? As Marks says: not easy. However, you need to start getting into the habit of thinking like this if you want to beat the market. You can make gameplans in advance for various scenarios. Here are some examples from Marks to illustrate the difference between first order and second order thinking. Some further examples Trying to react fast to headlines is impossible in today’s market of ultra fast computers. You will never win on speed. Therefore you have to out-think the average participant.
Coming up in part II
Now that we have a basic understanding of concepts such as expectations and what the market has priced in, we can look at some interesting trading techniques and tools. Part II
Preparing for quantitative and qualitative releases
Data surprise index
Using recent events to predict future reactions
Buy the rumour, sell the fact
The trimming position effect
Some key FX releases
Hope you enjoyed this note. As always, please reply with any questions/feedback - it is fun to hear from you. *** Disclaimer:This content is not investment advice and you should not place any reliance on it. The views expressed are the author's own and should not be attributed to any other person, including their employer.
TLDR: How do you personally define support and resistance zones algorithmically, if at all. If you don't, why? Is it strategy specific, you've found that you simply don't need them, etc. So I'm relatively new to algo-trading, but I have a bunch of forex trading strategies that I've already manually traded successfully. I would like to create some level of automation for them, with the primary purpose being to give me time away from my keyboard. I keep running into the issue of defining support and resistance zones, on which my strategies almost always depend to work successfully. Some of the things I've tried:
Getting all pivot points for the last 10 or so years on the interval I'm trading and averaging out those within a range in order to get fewer and more concise lines. This sometimes works, but sometimes doesn't, depending on volatility and range of the price within that time. I'd need to manually configure as well as update with some regularity in order to keep the zones accurate across different pairs.
Getting the lowest and highest price of an instrument over the last 10 years. Then for each price from the lowest to the highest, incrementing by 2% of the range every time, counting the number of times that price(in a range of about .5% around the price) serves as a local high or low, and only charting the 10 with the with the fewest touches. and 10 with the most touches. This also gave me inconsistent results leaning on the inaccurate side, and varied *heavily* across instruments.
I've been looking for other ways to determine the support and resistance zones, but I haven't really found anything that gave me anything consistently close to what I'd have determined by eyeballing the chart. I understand that zones are massively subjective, but I'm primarily here for any different perspectives on the matter. I can always tweak things where I need to to make it fit my goals. I just need a general concept that could work. Thank you in advance.
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%
Demo Trading Results
Since this post, I started demo trading this system assuming a 5k capital base and risking ~1% per trade. I've added the details to my spreadsheet for anyone interested. The results are pretty similar to the backtest when you consider real-life conditions/timing are a bit different. I missed some trades due to life(work, out of the house, etc), so that brought my total # of trades and thus overall profit down, but the winrate is nearly identical. I also closed a few trades early due to various reasons(not liking the price action, seeing support/resistance emerge, etc). A quick note is that TD's paper trade system fills at the mid price for both stop and limit orders, so I had to subtract the spread from the raw trade values to get the true profit/loss amount for each trade. I'm heading out of town next week, then after that it'll be time to take this sucker live!
Date range: 7/9-7/30
Adjusted Proft % (takes spread into account): 20.73%
Starting Balance: $5,000
Ending Balance: $6,036.51
Live Trading Results
I started live-trading this system on 8/10, and almost immediately had a string of losses much longer than either my backtest or demo period. Murphy's law huh? Anyways, that has me spooked so I'm doing a longer backtest before I start risking more real money. It's going to take me a little while due to the volume of trades, but I'll likely make a new post once I feel comfortable with that and start live trading again.
Genuine Q: Why Do New Traders Try Trading the Hyper-liquid Assets Dominated by Institutions/HFTs/Algos?
Serious question: not a knock on people who have found success with this! I'm genuinely curious why new traders try starting out by trading the hyper-liquid assets that are so heavily dominated by massive volume from institutions/HFTs/Hedge Funds/Algos etc? Large cap stocks, major forex pairs, commodities, and futures/ETFs/options on these? I would imagine retail wants to trade with other retail, but these assets are overwhelmingly dominated by "professionals". On the flip side, low cap stocks, obscure currencies, even crypto have a much much higher percentage of volume coming from retail. I would think that's where retail would want to start because it's so much easier to "beat" retail than it is to beat sophisticated algos. The liquidity is virtually infinite for a retail trader, so in theory there's unlimited upside, but you're competing with the largest and most sophisticated players in the world. For example HFTs trade on news within microseconds and transmit information across the country at close to the speed of light. The liquidity and order flow in SPX instruments comes from not only futures, SPY, underlyings (and options) but so much occurs inside darkpools that are invisible to retail. Edit: this reminds me of the study published here about futures day traders in Brazil. The study concluded, in essence, that retail traders trading the "Mini-Ibovespa futures" (Brazil's E-mini) essentially never profited in any meaningful sense. Of the 19646 day traders they followed, only 3% had any profit at all after 300 days, and only 0.4% made more than $54/day. The single best performer of the nearly 20k profited just $310/day with massive volatility to his/her daily profits. Also, traders didn't appear to get better over time. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3423101 Again not criticizing people who turn profit but it just seems so much harder to do. Thanks!
Hello all. I will make this quite frank. I've been noticing dangerous advise being spread around the forums that is based too much on hype and I do not want the layman investor to suffer. We are all here to profit intelligently, not to gamble. So I would just like to offer a few tips to new investors of stellar. I am not a stock professional but have ties to the finance industry and have dabbled in forex and investments. I got burned so that you don't have to, so heed my advise. Especially since I have institutional friends who have helped me along the way (think Goldman, BNP, JP, etc). Tips: 1.) Do not over-diversify your portfolio but pay attention to exposure. Investing is all about the risk-reward ratio. Greater risk does not always mean greater reward. For example, I have 80% of my portfolio in traditional investment vehicles like real estate investment trusts, stocks, bonds, and exchange traded funds. 20% is for cryptos however this is what I consider my 'play' money since cryptos are a very young market, that is based more on potential rather than value (you can't gauge the financial health of crypto using traditional tools like cashflow analysis or price/earnings ratios). I think cryptos are incredibly valuable but going all in especially with the inflated nature of bitcoin, would be dangerous for any of you, so I would suggest you diversify between traditional and cryptos. 2.) Reduce crypto risk by analyzing competitors to your alt coin. As I said before, do not overcompensate this diversification but bet for and against a crypto. In forex institutions use this tool to limit exposure to currency volatility. Imagine you go long GBP/USD, then you should naturally short GBP/CAD to a degree in order to limit exposure, but maximize growth potential. In the crypto world crypto pairs aren't really traded so they are illiquid markets, but I would suggest hedging a bit of stellar with XRP and even bitcoin. With this strategy I have been able to mitigate my losses from the recent stellar drop. Picture cryptos as a ranked list with the most valuable on top and the worst in the bottom. If BTC is on the top of your ranked list and XLM is in 3rd place but XRP is in 2nd place, then short XRP/BTC and go long XRP/XLM. I know these pairings don't all exist but it's to give you an idea how to think about the market. 3.) Support and resistance is important for technical analysis. The way you determine this is simply by seeing the area where past price action has not been able to surpass (resistance) or where past price action has not been able to drop below (support). Usually when a support or resistance level is tested multiple times it becomes stronger. However, there are ways to guess how breakouts are formed. See the chart below. https://imgur.com/u9r2e0c In the chart you have what is called accumulation. The price keeps testing the 400 resistance mark, making it a stronger barrier, however every dip in price is higher than the proceeding dip. This signals that there is a solid accumulation that will result in a break out. Just because a price level is tested multiple times does not mean there is a break out. You need to usually have such an accumulation phase (think of the imagery of stairs). In the same chart you can also see the price has not been able to really go below 400 because it is the new support level and the more it tests it, the stronger the barrier will become. 4.) Statistics has a fine way of helping us in our journey. My best friend is a mathematician and was able to offer advise on statistical trend setting. He stated that the longer the trend is set, the higher probability that it will keep going in that direction. Sounds obvious right? Well there is some truth to this but this goes right to my next point. 5.) For every second and moment you have a position open you increase your risk exponentially. This is why high frequency trading exists. So I am trying to offer a nuanced point that while trend continuation is statistically likely, so is the exponential increase of risk. These two last tips are particularly for leveraged traders. 6.) Be creative. Try to implement value investing criteria on cryptos in order to assess the true value of your chosen currency, whatever that may be. It can truly be difficult for ones like Bitcoin but for centralized cryptos like XRP and non profits like XLM it isn't too difficult. I saw an investor here requesting stellars financial statements and had a slight grin. That is the type of investor you should be. Vigilant, because more than making money, we should all be focusing on protecting money. Do not be greedy, because you will be susceptible to hot tips and emotion. Make 'preserving' your capital a priority. As long as you are gaining above inflation, all of you are winning. And now... 7.) Luck number 7! Anyway, buying on the dips is a great strategy, especially when it is testing a support or resistance zone that has been tested a bit before. Buying into a dip in a zone that has only been tested once is a bit risky. You want to see a form of sustainable accumulation. 8.) Do not simply invest in a crypto purely based on the dip. I will admit I have done this sometimes to an extent and it is okay. But the point of this post is to encourage you to do your homework and measure valuations, based on market volume, liquidity, technological announcements, and financial statements. The reason I sometimes partially ignore this is because I usually enter investments to hold at least 8 months -1 year minimum. 9.) Centralization and decentralization do not matter in crypto. I know XRP gets hate and I'd prefer stellar lumens, but that is not purely a reason to not invest in a currency. With centralization you get more compliance and regulatory oversight which marks higher security in investment. Cryptos are amazing, but with institutional involvement, this is an important case to make. 10.) Governments do not have conventional ways to regulate cryptos, but they do have tools to manipulate the market, so be attentive. All it takes is one major country to become heavily involved, in order to ensure a large price drop. 11.) DO NOT SHORT! I REPEAT DO NOT SHORT! Leave this to the professionals. Whereas with buying a currency you have a limited downward risk (you only have the risk to lose all your money), with shorting you effectively have no price floor to limit risk and exposure since the price theoretically has unlimited growth potential. If you decide to short stellar at 0.10 cents then you can lose all your investment and even be in debt (depends on leveraging), because the price can go anywhere from 0 cents to infinity. When you buy, you limit your risk to 0 cents which is where you lose all your money, but maximize growth potential which is technically infinite. This plays into the concept that the longer you have a position open, the greater the exponential risk. I hope you all enjoyed my guide. I am by no means an expert and am new to cryptos, however I've had associates involved for longer and friends that are also in finance (I worked in the back office of a private equity firm even though that wasn't glorious).
Although it might seem easy to invest in Forex nowadays, by just logging into an account with a broker, deposit some money and start actively trading; it has not always been like this, as forex industry has rapidly changed in the past three decades. Before technology and free-floating currencies took over the industry, world currency exchanges were operating under the Bretton Woods System of Money Management. This agreement established rules for commercial and financial relations among top economies, tying their currencies to gold. Hence, a currency note issued by any world government represented a real amount of gold held in a vault by that nation. When in July 1944 delegates from all over the world sign off the pact, the main goal was to reduce lack of cooperation between countries and therefore avoiding currency wars. This process of regulating the foreign exchange brought to the foundation of the international money fund (IMF) and the International Bank of Reconstruction and Development (IBRD), today part of World bank Group. However, in the early 70s the real-world economics outpaced the system, dollar suffered from severe inflation cutting its value by half. At that time unemployment rate was 6.1% and inflation 5.84%. Finally, in August 1971, U.S. government led by Richard Nixon took away gold standard, creating the first fiat currency and replacing Bretton Woods System with De Facto. Together with this there were other important measures taken by the USA president to combat that high inflation regime:
This decision was driven by many European nations asking to redeem their dollars for gold, till leaving Bretton Woods System. This had an enormous impact on USD which plunged against European currencies. Consequently, USA congress release a report suggesting USD devaluation to protect the currency from foreign gougers. However, dollar dropped again, and Treasury Secretary was directed to suspend the USD convertibility with gold; hence foreign governments could no longer exchange their USD with gold.
The inflation level was skyrocketing and one more action taken by Nixon was to freeze all wages and prices for 90 days, this was the first time since WWII.
Import surcharge of 10% was set up to safeguard American products ensuring no disadvantage in trades.
Today, USD dominates financial markets, accounting together with the EURO, for approximately 50% of all currency exchange transactions in the world. 1971 represents the beginning of a new forex trading era, bringing this market to be the largest and most liquid in the world, with an average of daily trading volume exceeding $5trn. All the world’s combined stock markets don t even come close to this, what does this mean to you? In an environment which is controlled by free-floating currencies moving constantly, following principles of supply and demand, there are constant and exciting trading opportunities, unavailable when investing in different markets. In this article are shared main features of what is forex trading today and how can be an incredible new source of income for everyone who is into financial markets.
What Is Forex?
Forex is the acronym for foreign exchange which intends to be a decentralized or over the counter (OTC) marketplace, where currencies from all over the world are traded 24 hours, five days a week. Main financial centres include New York, Chicago, London, Tokyo and Frankfurt for Eurozone. It is by far the largest market in the world in terms of volume, followed by the credit market. Being highly liquid is an important feature that allows traders to be able to enter and exit their positions very quickly. Nevertheless, while trading forex, an investor should be aware of several components: Dynamicity – forex is an extremely fast environment, this means that currency rates can move very fast, influenced by price action signals and fundamental factors. Therefore, going into forex trading, one needs to be aware of adopting serious risk and money management strategies in order to be effective, limiting losses. Zero Sum Game – trading forex is not like investing in the stock market but is known to be a zero-sum game. For example, going into the equity market buying some tech shares, they could both rise or decrease in value. In forex is different because currencies work in pairs; for instance, an investor decides Euro will go up he or she is doing it against another currency. Thus, in this specific marketplace one currency will rise while the other will fall, meaning an investor is buying the currency hoping it will appreciate to the other, or selling the one that will depreciate. See image below: Figure 1: Main traded currency pairs https://preview.redd.it/vu77ziuoyle31.png?width=574&format=png&auto=webp&s=9b1693bf27508fcb142705c309de1fc5b3e8fa19 Currency pairs are composed by a base and a price currency. Main forex trading principle is how much price currency an investor can buy using 1 unit of the base, thus, the base currency, which is the first one in line within the quotation, is always equal to 1. Because like every financial instrument currency pairs are driven by fundamentals of supply and demand, forex is intensively influenced by geopolitical and macroeconomic factors. Capital Markets – these are the most visible indicators of a country economic health, where usually the healthier the economy the stronger the currency. For example, a rapid sell-off from a country will show that nation is not economically stable, subsequently investors will think negatively of it depreciating its currency. Moreover, many countries are sector driven, this means that their currencies are strictly correlated with certain resources. For instance, Canada which is a commodity-based market, CAD is strictly linked to price of Brent and metals, a swing in those will affect the Canadian currency. Finally, credit market is also connected to forex since also relies heavily on interest rate so, a change in bond yield will have major impact on currency prices. like increase in yield will favour bullish market for USD International Trade – Trade levels serve as a proxy for relative demand of goods from a nation, a country which goods and services that are in high demand internationally, will experience an appreciation to its currency. This is an effect driven by all other countries converting their currencies into the one of that state to purchase its goods and services. Let’s say a product from USA is in high demand globally, all the other countries must sell their currencies to buy dollars to then see their goods shipped, thus USD will appreciate. Trade surplus and deficit also indicate a nation competitive standing in international trade. Countries with a large trade deficit are usually importers resulting in more of their currencies being sold to buy goods worldwide, thus they will see their currencies devaluate. Geopolitics – The political landscape of a nation places a major role in the economic outlook for that country and consequently, the perceived value of its own currency. Beside building up price action strategies, based purely on price levels, forex traders constantly look at economic calendars and news to gauge what could move currencies. A geopolitical event which is having a great impact on GBP, is the election of Boris Johnson as UK prime minister, driving the local currency to 2 years low, yesterday 29th of July 2019. Therefore, when investors observe instability from a nation political environment, there are high chances that the currency of that country will depreciate.
Why Trading Forex
Beside swapping from a gold standard to free-floating, which change the whole forex trading game, technology is another crucial factor that helped this financial sector to spread globally. With the introduction of internet in the 90s forex opened to retail investors giving access to various trading platforms. The introduction of online platforms and retail investments have increased forex market volume by 5%, up to $250bn of its daily turnover. Different traders may have different reasons for selecting forex, however, mostly is because this is a fertile market plenty of daily opportunities to gauge price action and profit from it.
How traders profit from trading forex? Basics of trading are rather simple to understand. An investor buys an asset at a certain price hoping to get rid of it for a higher price. The more volatile is the market for that specific financial instrument, the more revenue is possible to make. Therefore, a trader is looking for long up and down moves rather than market fluctuating sideways. Volatility is great in forex and a trader can expect to regularly see prices oscillating 50-100 pips on major currency pairs almost any day of the week. Yet again, due to this enormous constant fluctuation, potential losses or gains can be very high thus, rigours money management must be applied to avoid major damages and become a profitable trader. To conclude, volatility is the main characteristic investors are looking at and that is why it is one of the main feature traders can take advantage. See image below: Figure 2: FDAX Volatility, H4 (30th May 2019, 16:00, 30th July 2019, 16:00)
Accessibility & Technology
While volatility is the most important element out in the market that tell us why forex is the best market to trade, accessibility comes straight after. This market is more accessible than all the others, trading forex requires an online desk position and as little as $100 to start off an account. In comparison with the other financial markets, forex requires a rather low trading capital. Moreover, trading forex can be easily accessible from your PC, tablet or mobile since most of retail broker firms operate online. Although, accessibility cannot tell the quality of the market by itself, it definitely shows a reason why many investors try their first trading experience on forex. Also, the rapid introduction of technology since the 90s, made trading much easier. There are every year more advanced online platforms to trade on with many possible updates and that is why trading forex is edging for many global investors.
Before the introduction of free-floating currency and more importantly cutting hedge technology, forex was a market that could have been traded only by institutional investors. Nowadays however, even retail and individual investor can take advantage of the huge volume forex offers every day. Banks Interbank market is the major responsible for the high volume registered daily in forex. This is the place where banks exchange currency among each other, facilitating forex transactions for customers and speculate for their trading desks.
Clients transactions: in this case banks of all size act as dealer for clients, where the bid-ask spread represents the profit for the institutions.
Speculation: currencies are traded to profit from their price fluctuations as well as to increase diversification on their portfolio
Because banking institutions are the biggest players in foreign exchange market, they are able to push up and down the price of currencies giving an extreme advantage and higher volatility to individual traders who are trying to gauge price moves. Central Banks Central banks representing their nation’s government, are crucial in forex. They oversee monetary and fiscal policies having massive influence on currency rates. A central bank is responsible for fixing the price level of its native currency on the market, in other words they take care of the regime currencies will float in the open market.
Floating: these are the currencies which price floats on the open market based on principles of supply and demand relative to other currencies
Pegged (fixed exchange rate): opposite to floating currencies pegged ones are not free-floating in the open market however, their government rather tie them to the value of a stronger foreign currency. Pegged currencies are more seen in developing countries (CYN to USD).
Because central banks manage interest rates in order to increase the competitiveness of their native nation to another.
Dovish: these policies will be lowering down interest rates. A central bank which applies dovish conditions aims to give economic stimulus and guard against deflation. Usually a policy intended to give economy stimulus will weakening the currency value.
Hawkish: on the other hand, hawkish policies lead to an increase in interest rate. A central bank that uses hawkish measures aims to reduce inflation. Typically, this kind of policies will reinforce the country currency value.
Investment Managers & Hedge Funds Portfolio managers and hedge funds are the second investors in forex after central and investment banks. They are hired by huge institutions such as pension to manage their assets. However while portfolio managers of pool funds will buy currency to speculate on foreign securities, hedge funds execute speculative trades as part of their strategies. Corporations Also international corporation play a big role in forex. Those firms operating globally, buying and selling goods and services are involved in forex transactions daily. Imagine an American company producing pipes that imports Japanese components and sell the finished product to China. After the sale is closed the CYN must be converted back to USD, while the American company must exchange USD into JPY to repay for the components supply. Moreover, company involved in international trade have an interest in forex in order to hedge the risk associated with currencies fluctuations making several foreign exchange transactions. For instance, the same American company might buy JPY at spot rate, or enter a swap agreement to obtain JPY in advance, overtaking the risk of the Japanese currency to rise in the future. Therefore, forex become crucial to run companies with many subsidiaries and suppliers all over the word. Individual & Retail Investors Even though this investor cluster brings to forex a very limited volume compared to financial institutions and corporations, it is rapidly growing in numbers and popularity. These base their trades on a mixture of fundamentals and technical analysis. Bottom line, main reason why forex is the most traded market in the world is because gives everyone, from top financial institutions to retail and individual trades, opportunities to make returns on capital invested from currencies price fluctuations related to global economy.
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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