New Research: Does Crypto Perform Better than Stocks, ETFs?…

Crypto v Stocks: Summary

Crypto currencies haven’t been around long. The first one in my database has a start date of late 2014. Based on their short life, they perform substantially better than stocks (twice as good) and ETFs
(three times as good). That’s the good news. The bad news is that the moves up can be difficult to trade because some are steep. Getting out near the top can be a challenge.

In this article, I’ll discuss the results I found after testing crypto currencies and comparing them to stocks and ETFs.

Testing shows that you can make an average of 27% using a simple moving average exit signal.

You can download the crypto results.

Crypto v Stocks: The Data

I compared 38 crypto currencies with 238 stocks (enough to give a good number of samples) and 61 exchange traded funds (no foreign country funds, no leveraged or inverse funds).

All trades started on or after 10/25/2014 (the date of the first crypto currency in the study), to the end of data, 5/25/2023.

Although there was a bear market in 2020 (COVID 19), I did not remove the results for that event.

I found double tops and bottoms (all combinations of Adam and Eve), triple tops and bottoms. I chose these patterns because
they are easy to find, easy to determine the breakout price, and plentiful.

The stocks tested were chosen from my database of stocks which I follow daily. I didn’t concern myself with company size (market cap: small, medium, large). I just let my computer run until it logged enough samples.

To find the patterns, I used three different methods. For crypto, I found them manually first then used an automated system to find new ones coupled with a review of all patterns. I removed only a few, mostly
triple bottoms and tops where one peak was unusually far away from the others (in price). For stocks, I found them manually only and check every one (over the years). For ETFs, I used an automated scan and spot checked
a few.

Crypto v Stocks: Trading Signals

I placed a buy stop a penny above the top of the bullish patterns and below the bottom of bearish patterns. If price gapped open, then I used the opening price as the fill price.

Sale was made at the ultimate high or ultimate low. This allowed me to test how well the chart pattern worked, best case, not how
an arbitrary trading setup worked (such as a moving average crossover or RSI signal). I show a more realistic test setup later.

Because this uses the perfect entry and perfect exit, it’s not realistic, but it does allow us to make conclusions. How you trade a security, with your own entry and exit signals, is up to you.

Here are the trading rules.

• For bullish patterns, place a buy stop a penny above the top of the chart pattern (above double and triple bottoms).
• For bearish patterns, place an order to sell short a penny below the bottom of the chart pattern (below a double or triple top).
• Sell a bullish pattern at the ultimate high, which is the highest high before price drops at least 20% or at the close if we’ve run out of data.
• Cover a short at the ultimate low, which is the lowest low before price rises at least 20% or at the close if we’ve run out of data.

Crypto v Stocks: Results for Upward Breakouts

Table 1 shows results of comparing crypto currencies with stocks and ETFs.

The data shows surprises. I suspected that crypto currencies trended longer than stocks or ETFs and the average or median rise supports that belief. Crytpo outperforms stocks by twice the rise
and ETFs by three times the rise. The differences between the average and median means the big performers tended to skew the average upward. The median performance is the middle performance in a sorted list
of numbers, so that half outperform and half underperform.

My surprise here is that ETFs perform so poorly compared to stocks. Maybe that really isn’t the case. It’s probably more a reflection of using sector funds in the ETFs versus a mutual fund that invests in
the broad market.

The S&P 500 index was the benchmark. All three columns beat the index easily. I logged the performance of the index with the starting and ending dates of each trade and compared performance of the index with
stocks and ETFs.

The 5% failure rate is a reflection of how well the security trends. Crypto currencies have a tiny failure rate. By that, I mean only 7 or 3% of the trades I looked at failed to see price rise at least 5%
before reversing and closing below the bottom of a bullish chart pattern. The other two columns show substantially higher failure rates. ETFs, with a 30% failure rate, is horrible.

The measure rule is a way to gauge trendiness. I measured the height of each pattern and added the value to the top of the chart pattern to get a target. This is an arbitrary measure. It does not mean
that it sucks price up to meet the target. However, it shows how well price can rise at least the pattern’s height. Usually, the better the average rise the higher the measure rule performance. Both crypto currencies
and stocks perform about the same. ETFs suffer, though, but they are not that far behind.

The throwback rate measures how often the security returns to, or comes close to, the breakout price. Usually a return trip happens within a week of the breakout. The three columns show
similar results, which is gratifying.

Crypto v Stocks: Results for Downward Breakouts

Table 2 shows the results for bearish chart patterns (double tops and triple tops).

The average decline shows that crypto currencies outperform the other two columns by a wide margin. The median and average declines for crypto are close (25%, 23%), which is interesting. The other two columns show a wider difference.

Five percent failure rates are tiny for crypto but large for stocks and huge for ETFs.

The measure rule target is just 29% for crypto and that’s puzzling. After looking at the data, I found that crypto patterns are substantially taller than those in stocks and ETFs. I show the height as a
percentage of the breakout price on the next line. Crypto securities were 32% tall compared to a height of 6.8% (stocks) and 4.7% (ETFs). That means it’s going to be difficult for price to drop by an average of 32%.

The pullback rate is stable for all three. Again, that’s reassuring.

What do all of the numbers mean? It appears that crypto currencies trend longer and price moves farther than for stock and ETFs (the average rise or decline for crypto is substantially higher than the others).
Failure rates for crypto are smaller than stocks and ETFs. With discipline, trading chart patterns in crypto currencies (if you can withstand the volatility) could be profitable for an experienced pattern trader.

Crypto v Stocks: Lessons

Let’s discuss some important lessons the data teaches us about crypto currency. For these tips, I’m only going to discuss bull markets with upward breakouts.

Crypto…

1. Has a low failure rate (3%).
2. Has a large average rise (65%) and even a median rise is big (38%).
3. It takes an average of 20 days to reach the ultimate high. In other words, the upward move is very steep and fast (65% in 3 weeks). A timely exit after such a fast rise can be difficult.
4. Measure rule: crypto reaches the target 70% of the time, suggesting it’s a good measure to use as a target.
5. Pattern height does not matter for performance (which is unusual).
6. Patterns wider than the median 18 days tended to perform better. Short (below 23.4% of height divided by breakout price) and wide performed best (79% average gain).
7. Patterns without throwbacks posted average gains of 84% compared to 55% for those with throwbacks. This follows what I’ve seen in other chart patterns. It’s as if a throwback robs upward momentum and performance suffers.
8. After a throwback completes, price continues rising 44% of the time. That’s not very good. It suggests that during a throwback, 56% of the time you’ve made the ultimate high.
9. Volume trends downward (between the pattern’s start and end) 70% of the time, but performance improves if volume rises.
10. Heavy breakout day volume helps push price higher (heavy volume: 68% avg rise v 46% after light volume breakout).
11. Performance improves if the time from the trend start to the pattern’s start is shorter than 3 months.
12. Cryptos in the 2010 decade outperformed those in the 2020s by 75% to 62%. Has performance deteriorated because they have become more popular?
13. If the primary trend (comparing the closing price one year before the breakout to the breakout price) is up, crypto outperforms by 69% (uptrends) to 56% (downtrends).

Crypto v Stocks: Example

The chart shown is Arweave USD (AR-USD) on the daily scale.

This shows a triple bottom that I used in the data to study crypto currencies. The triple bottom is highlighted by three TBs. The horizontal red line is the confirmation line. When price closes above that line, you
have a valid triple bottom.

For trading, place a buy stop a penny above the red line. That would get you into the trade with perfect timing, at A.

Over the next 10 days, price climbed from the breakout price of $1.85 (a penny above the red line) and hit the ultimate high (B) at 3.80. That’s a gain of 105% in less than 2 weeks!

However, after the ultimate high at B, the security dropped to C, $2.52 or 34% lower.

If you didn’t sell at B and hung on through the plunge to C, you could have made more money by holding onto AR on the rise to over $7.00

Crypto v Stocks: Realistic Trading Setup and Results

The chart shown is Aave USD (AAVE-USD) on the daily scale.

For a more realistic setup, I tested crypto using a simple moving average crossover. Here’s the setup.

• For bullish patterns, place a buy stop a penny above the top of the chart pattern. If price gaps open, use the opening price. For bearish patterns, place an order to short a penny below the bottom of the pattern.
  If price gaps lower, then use the opening price.
• For upward breakouts, use a 25-period simple moving average (SMA). Starting the day after entry, wait for price to close below the SMA. Sell at the open the next day.
• For downward breakouts, use a 15-period SMA. Starting the day after entry, wait for price to close above the SMA. Cover at the open the next day.

Why 15 and 25 SMA? I tested this setup on three crypto files (out of sample) and found that these two performed best (gave the highest return). I used the remainder of my crypto database for out of sample tests, which
Table 3 shows.

Let’s talk about the chart first. This is an in-sample example of the bullish setup. We have a Adam & Eve double bottom. It confirms as a valid chart pattern when the currency closes above the highest
peak between the two bottoms. That happens at A. A is also where the buy stop would trigger. Because we have an upward breakout, we’ll use the 25-period SMA as the exit signal. Wait for price to close
below the SMA. That happens at B. Exit the next day at the open.

In this example, you’d buy on 1/12/2023 at 67.02, sell on 2/7/2023 at 81.14 and make 26%, assuming there’s no commissions and fees (which there may be).

Table 3 speaks for itself. I used out of sample crypto securities and traded according to the rules discussed above. The average profit was 27% but big winners pulled the average upward (the median win
is only 3%). The win/loss ratio of 58% is quite high where many trend following setups register in the 40% range. The largest loss (44%) happened when a bullish pattern broke out upward and price reversed
within a day or two, tripping the exit signal.

— Thomas Bulkowski

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