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.
This has been bugging me for a while so thank you for endulging my rambling. TL;DR at the end.
I'd like for everyone to just think about what we're trying to do here. Don't forget what the ultimate goal is. Anyone remember? Is it to make a profit? No, that's a secondary goal. The primary goal is to develop widespread adoption of cryptocurrency as an alternative to fiat currency. Anyone remember this lofty goal or did we all forget this while chasing 30% daily price swings. We're trying to complete with USD, GBP, EUR, and CNY, remember? This is EUR vs. USD.
You'll note that this is all data (or click on "All" button on the bottom), going back to 1993 through today. What do you notice? You'll notice an open of $1.22 to €1. After a few months
, it fell about 10%, then rose up 24% over the next two years
only to drop about 40% over seven years
and then almost doubling over eight years
only to drop about a third in the last ten years
to where it is today - almost where we were 25 years ago (approximately). This is BTC vs. USD.
You'll note that this is all data going back to 2011. During the last seven years
it has... oh my God are you kidding me?! This is LTC vs. USD.
Let's not forget what we're talking about. We're talking about currency. For currency to be used, it needs to be relatively stable. Now compare the charts above. Let's say we created a new country called Cryptonia. Which of these would you like to use as currency? EUR? BTC? LTC? My money is on EUR. Why? Because it's relatively stable.
Now let's fast forward a bit and pretend that Cryptonia has adopted Litecoin as its official currency. Our largest trading partner is the US. How would transactions between merchants work in this scenario, taking into account the last few days. I'll use the following prices:
- 1/16: $227
- 1/17: $163
- 1/18: $194
Let's run through a transaction:
- Cryptonian citizen C1 is selling a widget at 1 Litecoin to an American citizen A1
- A1 pays $227 and C1 gets that converted to 1LTC
- C1 is also selling another widget to A2 on the same day for 1LTC and has 2LTC total
- A1 decides that they don't want the item and would like to return it. C1 issues refund of 1LTC. A1 gets $163. A1 loses $64 or 28.2% on the return.
- C1 now has 1LTC
- A2 is decides to do nothing.
- A2 decides to sell the widget to C2 for 1LTC
- C2 says the price is fair since it was 1LTC a few days ago and buys it
- A2 gets $194, a 19% profit from two days ago
- A1 is pissed
- C1 is happy since they made one sale
- A2 is happy since they made a 19% profit
- C2 is happy since they have a widget at a fair price
This works both ways as far as you can do the math in USD vs. LTC to see how this screws over at least one party due to the wild price swings. Note: fiat currency does the same thing with one key difference explained later on.
Don't forget that this is all within 3 days. Now sure, obviously the last few days isn't something that happens every day ... but doesn't it? Look at the examples of EUR:USD. Any sharp spikes or drops have taken months to execute - enough time for relative prices
to adjust. Look at cryptocurrency prices - the swings (from a percentage basis) are wild on a regular basis. In short, cryptocurrency isn't acting like currency. It's acting like an asset and not just an asset but a highly speculative one. The IRS is right to treat it like an asset because if it looks like an asset, and it acts like an asset, then it is an asset.
Where do I believe this should go? I believe cryptocurrency market needs to mature. I believe these drastic price swings need to stop. When will this happen? I believe it'll happen when the cryptocurrency market reaches a happy plateau where the market cap has reached a point where the buyers and sellers mostly eliminate one another and the relatively large price swings - from a percent point of view - are as boring as Mr. Stein
. EUR vs. USD went up 0.03% today. 0.03%. In LTC-speek, that's going up $0.58 for the whole day. Oh and it was a wild ride too. Why it went all the way down to $1.21697 and all the way up to 1.22645. I know, I know - tie me down because I'm out of control.
Is this the only problem? No. Cryptocurrency has another problem and that's the sheer number of types of coins available. How many coins are available? 1,448
. Nearly 1,500 coins all competing with each other for market share. We have Bitcoin at about $200b all the way to something like Digital Money Bits (DMB, an appropriate acronym). What is it? Who cares, it's worth $3,832. Not $3.832 billion or million but literally $3,832 with a volume of $35,509 today and hey, just this June, its market cap reached an all time high of $62,000! You missed the recent run-up though and boy did you miss it. On January 1st, its market cap was worth almost five hundred dollars! Yep, about two Litecoins! But look at it now - it went from $500 market cap to $3,832 in less than three weeks. Clearly this one is shooting to the moon.
This is a problem. Decentralization has an unfortunate side effect of - duh - nobody being in charge. There's no real clearance for these and some people with a little bit of money can literally copy and paste
a whitepaper and have this chart
and have a serious valuation of almost $17b from $140 million in literally 30 days. This doesn't act like a currency either.
This is a problem.
Don't forget, this isn't like the dot-com era. We're not launching IPO's and .com companies that have different ideas. Amazon isn't like Ebay, or Google, or Yahoo, or Facebook or anything else. They all have different ideas for different segments of the population. We are in the cryptocurrency market. The world today has 180 fiat currencies
. Cryptocurrency market is approaching 1,500. We need to trim the fat and the outright forgeries. Market cap isn't enough to weed them out. There needs to be something, a stabilizing force, that should act as a clearinghouse for launch of new cryptocurrencies. The market has failed to destroy shitcoins. Heck, it rewarded them based on lies, paid endorsements, FOMO, and FUD for other coins. This doesn't help the cryptocurrency market. It helps a few people get really wealthy really quickly and you are left holding the bag, so to speak. Should coins only be allowed to be introduced when its network reaches a certain hash rate? Isn't that the only objective point of value we have - number of mathematical calculations and power used in those calculations? You can't fake that.
What's another problem with cryptocurrency? It's what it represents. The governments don't see crypto as a positive force. After all, it directly competes with their own currencies. Can the governments shut this down? No - this is the Internet, after all. But they can kill it in other ways. I don't know how many people here remember but my first brush with Bitcoin was the ransomware viruses which wanted $300 in Bitcoin to unlock files. Bitcoin was seen as something tied to illegal activities. If governments - and let's say the US, South Korea, and China in particular - ban Bitcoin and cryptocurrencies in particular then what they'll really do is make transactions illegal. What's the on-ramp and off-ramp to/from crypto? The banks which are already regulated. Now let's say you're in the US, your bank account is tied to your Coinbase account and you have some cryptocurrency. US issues a regulation which states that trading cryptocurrency is now illegal. It issues orders to all US banks to shut down related accounts. The following things will happen: cryptocurrency prices will tank and everyone is going to scramble taking money out which would likely overload the system, causing massive delays.
But let's say you're left holding your crypto and it's been a month. What can you do with it? Not much. Crypto isn't accepted in enough places yet. You can continue holding, hoping the price and ability to extract will come back one day. After all, you can't get your money back. Your bank closed your related account. You can open another one at any new bank but they'll either ban you from connecting your account to Coinbase or they'll confiscate any money coming from Coinbase and charge you with a crime. Now have the governments banned crypto? No - you can use and trade crypto all you want since it can't be traced. But have they effectively? Yes. Ironically, it's the banks that'll save us and I think that's why Ripple blew up. After all, if you have a cryptocurrency that sucks the bank's [censored] and plays along, you can get:
- somewhat decentralized
- tied to various governments, i.e. no ban, little competition
- and use the banks money for lobbying to make sure the governments don't ban it
I think that's why something like Ripple blew up - because it doesn't care much about regular people, it wants to be the speedy highway for bank<->bank transfers.
What's a solution to this problem? More regulation and playing nice with the governments. Crypto isn't going mainstream if you shut out all governments. It needs to be connected. This means working with regulators to make sure that KYC laws
are followed, that people report and pay money on any gains, and that - to a point - there's some supervision and tracing of transactions in a way that if you're robbed, you can get your money back. This will create a new job field
, which - considering our current growth - will create a whole slew of high-paying white-collar jobs. Considering the high-level of transactions, banks would start this, followed by private companies, governments, and law-enforcement agencies. A good way to start this is what CBOE and CME have started to do - legitimize the currency. This is a foot in the door to the real holy grail: FOREX markets. When it's legitimized and not in serious competition with governments, it'll be embraced and its availability - along with instant transfers and low fees - will be widely supported by serious platforms.
Until these problems are fixed, the cryptocurrency market will remain what it is today: a speculative asset and not a currency. During the time it's taken me to write this post, Litecoin has gone up 2.6%. Euro remains at 0.03% gain.
Thanks for reading! TL;DR
- We're supposed to be creating a new type of currency - cryptocurrency - as opposed to chasing profits. To do this, we need to have stable charts and not wild price swings.
- We need to dump most coins on the market and focus on serious ideas that have potential. Market cap has failed to reign in fraud with large, multi-billion dollar shitcoins flooding in. Network hash rate and power usage is a measure we can use to determine objective worth.
- We're competing with governments and until we find a way to work with them, the governments can choke the life out of the entire cryptocurrency markets. This should start with KYC implementations and interoperability with the markets such as FOREX.
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