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. submitted by
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
- Raw Winrates:
- 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%
- Winrate: 46.4%
- 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%
- Winrate: 65.97%
- 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
- Raw Winrates:
- 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:
- Winrate: 58.19%
- 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.
Raw Data 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
- Winrate: 58.19%
- 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!
- 86 Trades
- Date range: 7/9-7/30
- Winrate: 52.32%
- 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.
*Introductions: I'm joskye. A cryptocurrency investor and holder. *
Hi again. This is the third part in our ongoing series on how to trade better and determine intelligent investments in cryptocurrency for the future.
- In part 1 I talked about the importance of selling enough to make back your principle investment i.e. if you buy something at $300 and it rises to $600 in value, sell $300 to eliminate all future risk of personal loss e.g. if that asset falls to $150 in value after (which can happen easily since suchvolatility is very common in cryptocurrency). In cryptocurrency trading/investments a 100% return of investment should always prompt you to consider selling 1/2 your stack.
- In part 2 I talked about the psychology behind fear of missing out; i.e. the dangers of buying during a sudden rise in an asset's price and how to make the most of such rallies whilst minimising the risks involved in joining them.
- In part 3a I discussed The importance of a value proposition and the absolute need for any cryptocurrency you invest in to already generate or have the potential to generate revenue in a manner completely independent of it's speculative value as dictated by daily market prices.
Part 3b continues where I left off with a discussion about price metrics specifically, what determines the price
and the importance of liquidity
... The day traders:
As I mentioned in my previous article, as of writing almost every cryptocurrency is determined purely by speculative value.
- Thus the absolute price of a given cryptocurrency is determined solely by the day traders and specifically the last price it was agreed that currency would be sold at with confirmation of that price by a buyer who bought it.
- People say lots of things determine the price; marketcap, liquidity, value proposition, revenues generated by the coin, the number of said coin in circulation but ultimately it comes down to the number of buyers and number of sellers competing for that coin.
- Perhaps the other thing is the size of said market relative to the money held by the players in it.
For instance in cryptocurrency Bitcoin is still the biggest player in the game. It carries a per unit price of $900 per coin. There are currently 16,090,137 (16 million) coins in circulation giving it a total marketcap value of [$900 x 16090137 =] $14481123300 or 14.48 billion USD.
- This is 85% of the current cryptocurrency marketcap. (The total marketcap of all cryptocurrencies as of writing is 17.17 billion USD.)
- Compare and contrast Shadowcash (SDC) which has a unit price of $1.27 with 6,616814 coins in circulation giving it a total marketcap value of [$1.27 x 6616814=] $8392766 or 8.39 million USD.
- Thus Shadowcash in comparison to Bitcoin is a tiny cap of the cryptocurrency sphere. Shadowcash has a total value that is only 0.06% of Bitcoin when comparing marketcap's.
Shadowcash looks even more meagre compared to the total cryptocurrency marketcap with only 0.048% of the total cryptocurrency sphere. To any Shadowcash holders despairing at this point, relax. There are over 707 cryptocurrencies trading as of writing and SDC holds the 27th ranking in terms of market cap. In such a competitive field, filled with scams that's pretty good. Moreso when you consider that SDC is a legitimate technology and is currently probably very undervalued.
... Lets look at the rich list for bitcoin:
Why did I just talk about this?
- The top holder has 124,956 Bitcoin valued at $1,12460400 or 1.24 billion USD.
- The top SDC holder has 1027261 SDC valued at $1,304621 or 1.4 million USD.
- Thus the wealth of the top SDC holder is 1.16% that of the wealth of the top Bitcoin holder.
- Well they say that a big fish can easily occupy, make a splash in and empty a small pond just by diving in.
In cryptocurrency I see this happening on the markets all the time
. Indeed market manipulation effects every single cryptocurrency eventually
... Market manipulation!
Large holders of valuable, high marketcap coins will often make multiple small volume purchases of less valuable, low marketcap coins. Often this will follow announcements regarding developments in that low marketcap coin.
- An example of low volume ordering is buying 1 SDC at $1.20, 0.5 SDC at $1.2001, 5 SDC at $1.2010, 3 SDC at $1.21, 10 SDC at $1.22 and 0.11 SDC at $1.24, but then leaving someone else to fill the order for 100 SDC priced at $1.242.
- Thus by spending $23.77, in low volume purchases the buyer can raise the market cap of SDC from ($1.20 * 6,616814 coins) $7.94 million to (1.24 * 6,616814) $8.20 million! (4.2% increase).
Low volume buying in a market with low daily trading volume can gradually drive up the price attracting an influx of buyers into that coin; often they will make larger volume purchases of it which helps drive up the price much further. This will trigger a further chain of buyers experiencing FOMO (fear of missing out, detailed in Part 2) who will drive up the price even further. The price will pump.
Often will smaller cap cryptocurrencies this may result in a sudden 20, 40, 60 or even +100% increase in value often over a very short time space (1-2 days, 1-2 weeks maximum).
The only way to discern if the sudden rise in coin value is due to pre-rigged market manipulation is to look at:
- Often the original purchaser who triggered these events will have accumulated a lot of said cryptocurrency cheaply prior to or during the early stages of the pump and will wind up selling the majority of his/her's purchases when the price reaches a peak; usually when the daily/hourly trading volume on that coin starts to decline but sufficient buyers are still available.
- This results in a sudden or often more gradual dump in the coins value, usually by falling by 75% or more of the rise.
You are looking for organic, gradual growth based on a solid value proposition.
- the value proposition of that coin (discussed extensively in part 3a of this guide)
- the order book
- the depth chart
- the pattern of change on daily trading volume (and liquidity)
- the price charts (15 minute, hourly, 1 day, 3 day, 7 day, 1 month, 6 months)
- the news cycle relevant to that coin
Sudden large spikes in value should make you pause and wonder if it's worth waiting for a gradual correction (organic drop) in price before entering your buy order. Do not fall for a pump and dump.
Stick to the lessons covered in previous parts of this guide (especially part 3a and 2) and you will be much less likely to lose money in the long run trading and investing in cryptocurrencies.
... The pattern of change on daily trading volume, the order book and liquidity:
Lets look at SDC and Bitcoin again. This time we are going to compare the daily trading volume (last 24 hours) in USD.
- In the last 24 hours (dated 8th Jan 2016), SDC traded a total volume of $26,033. This is 0.01% of all USD daily trading volume on exchanges and only 0.39% of the total marketcap of SDC.
- In contrast Bitcoin traded $163,306,776 ($0.16 Billion) over the same 24 hour period. This is 76.15% of USD daily trading volume on exchanges and only 1.12% of it's total marketcap.
I'd just like to use this opportunity to point out and reinforce the idea that day traders not holders dictate the daily price of an asset
. I'd also like to point out daily global trading volume on Forex is $4800 billion which makes Bitcoin a very small fish
in the broader arena of global finance and trade i.e. Bitcoin is still very vulnerable to all the price manipulation tactics and liquidity issues I am going to be describing in this article
by bigger players with richer pockets.
The daily trading volume also gives you an idea of how much fiat currency you can invest into a given cryptocurrency before you suddenly shift the price.
- The numbers means that just because the marketcap of Bitcoin is $14 billion, that does not mean that there is truly $14 billion worth of fiat currencies (USD, Yuan, Euro etc) in Bitcoin; the total fiat volume is merely an estimate based on current price and number of Bitcoin in circulation.
A sudden rise in coin price heavily out of proportion to the rise in daily trading volume should be the first sign to alert you to a pump & dump scam.
- For example based on the 24 hour daily trading volume for SDC I know that if I blindly spent $15,000 (57% of the daily trading volume) buying SDC without any regard to the price, I can be confident that I will likely cause the price of SDC to go up significantly.
- In contrast spending $15,000 to buy Bitcoin (0.0092% of the daily trading volume) without regards to it's price, I can be confident that it will not likely cause a significant rise in the daily spot price of Bitcoin.
Daily trading volume should show a steady increase over time with sustained buy support at new price levels; this is a good marker of organic, sustainable growth.
- It implies a low volume trading at low prices to trick the unseasoned trader to perpetuate higher volume, high price buys.
- If daily trading volume cannot organically increase to sustain the price, it will eventually fall when the original pumper (or group of pumpers) sell to take their profits.
- This does not always have to be the case! Sufficiently large price movements (several 1000%) can significantly raise the next absolute low in price for the mid-term (months) even if that is several 100% lower than the peak!
- Conversely declining trading volumes indicate loss of interest in the coin and a price that is potentially more prone to and at risk of price manipulation with smaller amounts of fiat/bitcoin (than if higher daily trading volumes existed).
- Finally the fact that daily fiat trading volume for Bitcoin and Shadowcash is such a small percentage of it's total marketcap reinforces the idea that price is set by day traders not by holders!
... For more detail you can now look at the depth chart: The depth chart is very useful to know how much fiat currency is required to cause the spot price of a given cryptocurrency to rise or fall by a given amount.
NB the price of most cryptocurrencies is expressed in Bitcoin
- The depth chart groups different bids (buy orders) and asks (sell orders) by price and volume e.g. 17.739 bitcoin worth of SDC are currently on sale at poloniex for 0.00117500 bitcoin each ($1.07 per coin) and 0.149 Bitcoin are on sale at the current spot price of 0.00135750 Bitcoin ($1.24)
- So as of writing, I can see (from the charts) to raise the price of SDC from 0.00135750 Bitcoin ($1.24) to 0.00181381 Bitcoin ($1.66) I would need to spend 26 Bitcoin ($23783).
because it has the largest market cap and daily trading volume of all cryptocurrencies by a very large margin
and because with a few exceptions (Ethereum, Monero) most cryptocurrencies do not have routes to directly purchase via fiat currency without first purchasing Bitcoin.
- The depth chart shows me how many coins I can buy without significantly increasing the price and how many coins I can sell within a given price range. It gives me an idea of the liquidity and volatility of the market i.e. if I buy SDC right now and need to sell it later today or tomorrow for fiat, what is the realistic probability I can get my entire amount in fiat returned to me in the amount originally spent.
Liquidity is super important. People often complain about a market lacking liquidity but that is often because they are trading in fiat volumes which far exceed the daily trading fiat volumes of the cryptocurrency they are referring to. If you are investing or trading in a cryptocurrency, always factor in the your personal liquidity and need for liquidity relative to that of the cryptocurrency you are investing in.
In other words don't expect to make a profit next day selling 'cryptocurrency x' if the size your single buy order composes >90% of the buy orders on the market for 'cryptocurrency x' that day (indeed in such a scenario be very prepared to sell at a loss next day if you absolutely have to)!
- The depth chart also gives me an idea of where significant supports exists (price zones with large buy orders relative to the depth chart) to determine the true base price (in conjunction with daily trading volume) and where significant resistances exist (price zones with large sell orders relative to the rest of the depth chart) to determine what the majority of sellers think the coin is truly worth. Be wary though as buy walls (large supports) and sell walls (large resistances) can be moved at any time.
There are certain patterns on a depth chart that make me believe a significant, sustained price rise is imminent: One example occurs when there is a very large volume of buy orders (>25% of total buy volume within 5% of current price) very
close to the current (spot) price, and a very
large number of sell orders close to but significantly above the spot price (approx 25% total sell volume within 10% of current price) and especially if the total buy order volume is a significantly higher percentage than it has previously been.
This simply indicates high demand at current price which may soon outstrip supply. Again I stress that these patterns can be manipulated easily by wealthy traders.
- It is up to you to study the depth charts and discern the patterns. You will learn more about day trading this way.
... The order book is another way of looking at the depth chart and allows you to see the specific transactions occurring that compose daily trading volume by the second!
I find it useful because it allows me to identify:
- If there is a string of low volume orders that can be filled to pump the price (or conversely a string of low volume sell orders to dump it). This can play on the psychology of the entire market as many people aren't simply aware of how the manipulations occur; most people simply look at the price!
- Where resistances to price change occur and how much money it will take to break them (i.e. if I am day trading to make a profit via pumping, is it worth me spending X to clear a sell wall to encourage others to buy and push up the price further or do I need to spend so much of my capital that should I fail to stimulate buy orders, I become vulnerable to a dump in coin price with effective subsequent loss of fiat money).
- The presence of automated trading bots rapidly cycling a buy or sell order of fixed volume between a series of prices that dynamically adjust with the overall trend in price movements. Bots can be your best friend (to pumping or dumping price) if you know how to manipulate them!
... The price charts:
Discussions about price charts could be endless. I'm not going to go into too much detail, mostly because I'm an investor who believes the value proposition, good consistent development, decent marketing and communications will ultimately trump spot prices and adverse (or positive) short term price trends in the future.
- I'm also going to skim this because I'm not as versed in this subject as I'd like to be.
- I personally use the candle bar charts on Poloniex to look at 15 minute and daily candles on the hourly, daily, weekly and monthly charts.
- I combine this with charts on Bittrex which can calculate the RSI (to estimate if a coin is overbought or oversold) and Bollinger Bands (again to help estimate if a coin is overbought or oversold).
- I usually look at the overall direction of trading over a period of several days, compare it to the direction and trends over the last month. I then try to interpret it in the context of the daily trading volume and depth charts.
- I often get my predictions on short term price movement wrong if I only look at candle charts without factoring in depth charts, order book and daily trading volume patterns! I have a lot more learning to do on technical analysis.
- The charts do often reveal mid/long term supports and resistances in price!
- Investopedia is a good place to start learning about different mathematical techniques to analyse charts (including any terms used in these articles).
- I'm a big fan of u/kustonoy who inhabits the Ethtrader sub. I personally feel his analysis of the short term markets are generally pretty good. You should never be too lazy to not do your own regular market analysis especially if trading short term, but if you want a good reference point, I suggest following him.
... The news cycle:
- I've mentioned this lower down the list because for intra-day and day traders and even to some extent investors, the news cycle matters very little unless it directly affects the value proposition in some way.
- If a news event does result in real maturation of the proposed value proposition (such that the technology has confirmed a new sustained user base or revenue stream) then it might justify a sustained rise in price regardless of the volatility achieved reaching and following the peak.
- Some assets may have nothing but an endless stream of good news which meets the above criteria yet it's valuation fails to increase. This is likely a sign that a larger player is deliberately manipulating the market to accumulate more of that asset to sell very high later (I believe Ethereum has fallen victim to this recently) or that it is occuring during long period of consolidation is where diversification of asset ownership is happening which means a new price floor is being set for much larger increases later on. The lowest most frequently occurring point which the price repeatedly bounces off of (stops falling below) is the new floor.
... Other interesting points: The 'coin x' scenario and the ridiculousness of marketcap:
'Coin X' is an imaginary hypothetical coin. There are only 10 in circulation. It has no value proposition beyond it's speculative value i.e. it will never generate a revenue independent of it's speculative value.
- If 'coin x' had only 10 in circulation, was indivisible and each coin had a value of $3 billion, the market cap of 'coin x' would surpass Bitcoin!
- If all 10 coins were not on sale then 'coin x' would have a value of zero.
- If 9 people had bought 'coin x' at $1 and the 10th person bought it at $3 billion, it's marketcap would still be $30 billion. This does not mean there is $30 billion of fiat stored in coin X.
- If an 11th buyer came along and bought 'coin x' at $1.20 the price of coin X would fall to $1.20 and the marketcap of 'coin x' would be $12.0.
- This still does not mean there is $12 of fiat stored in coin x.
- This does not mean everyone can sell 'coin x' at $1.20.
- A new buyer blind to the purely speculative nature of 'coin x' looking at the trend charts could try to argue it is now extremely undervalued and a great buy or possibly was a grand scam and untouchable.
- Either way the next price at which 'coin x' is bought/sold is purely arbitrary and determined by the patience of the seller and the impatience of the buyer.
- [Edit]: I could also issue 10 more of 'coin x' and if it's unit price remained $1.20 the market cap would instantly double from $12 to $24!
I'd like to point out the similarities between ZCash and 'coin x' (especially during it's launch).
- Marketcap is derived from the price, not the other way around. Until a cryptocurrency generates significant revenue independent of it's speculative valuation this will remain the case.
- Price is determined by the day traders, not by the holders.
- The spot price of any given cryptocurrency is determined by the patience of the seller and the impatience of the buyer.
- Price of most cryptocurrencies is derived from bitcoin unless they have a direct fiat gateway. Unless a significant amount of trading volume occurs via the fiat gateway, the price of that cryptocurrency is still heavily dependent on the price of bitcoin.
- Bitcoin is (for now) is the gold standard of cryptocurrencies. Because it has the largest marketcap (by a very massive margin).
- Market manipulation means that large holders in more valuable currencies (large marketcaps) can tamper with and set the value of much smaller currencies (i.e. smaller marketcaps).
- Bitcoin's price itself can be manipulated by investment banks, governments or firms who trade in multi billions of USD daily. This is because the daily trading volume is almost 5 trillion trillion USD (which is several thousand times larger
- There is nothing wrong with investing or trading in cryptocurrencies with low daily trading volumes and marketcaps, just be concious not to put more money into them than their long term buy support can handle and only invest what you can afford to lose.
- The concept of liquidity in a market is important relative to the amount of fiat you are planning to invest or trade in it.
- Whether day trading or investing, pick cryptocurrencies with good fundamentals i.e. excellent development teams, good marketing and strong value propositions that will provide the cryptocurrency in question use and value independent of speculative valuations. You are less likely to get manipulated or scammed in the long run that way especially if you are a holder.
- Be very weary of trading or investing small amounts of money in larger markets that allow leveraged trading. Those markets will behave irrationally and not follow the fundamentals in the short term.
- It is up to you to study the depth charts, order books, candle bar charts, daily trading volumes and news cycle to discern the patterns. The price is a composite of this and the psychology of people who don't understand this. You will learn more about day trading this way and more importantly learn to trade/invest independent of the price.
- Coin market capitalisations and data including rich lists derived from:
1. Coinmarketcap rankings: https://coinmarketcap.com/all/views/all/ 2. Coinmarketcap daily trading volumes https://coinmarketcap.com/currencies/volume/24-hou 3. Bitinfocharts - Top 100 Richest Bitcoin addresses: https://bitinfocharts.com/top-100-richest-bitcoin-addresses.html 4. Crypto ID - Shadowcash Rich list: https://chainz.cryptoid.info/sdc/#!rich
... Further articles in this series: "The intelligent investors guide to cryptocurrency"
Part 0 -
Part 1 -
Part 2 -
Part 3a -
Part 3b -
Part 4 -
Part 5 -
Part 6 -
Part 7a - "The intelligent investors guide to Particl -" Full disclosure/Disclaimer:
At time of original writing I had long positions in Ethereum (ETH), Shadowcash (SDC), Iconomi (ICN), Augur (REP) and Digix (DGD). All the opinions expressed are my own.
I cannot guarantee gains; losses are sustainable; do your own financial research and make your decisions responsibly. All prices and values given are as of time of first writing (Midday 8th-Jan-2017). Second disclaimer: Please do not buy Shadowcash (SDC), the project has been abandoned by it's developers who have moved on to the Particl Project (PART). The PARTICL crowd fund and SDC 1:1 token swap completed April 15th. You can still exchange SDC for PART but only if it was acquired prior to 15th April 2017 see: https://particl.news/a-community-driven-initiative-e26724100c3a for more information. Addendum:
Article updated 23-11-2017 to edit references to SDC (changed to Particl where relevant to reflect updated status) and clean up formatting.
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