BTC Long Day Trade Equity Backtest
In this post we’ll take a look at the backtest results of opening one BTC long day-trade position each trading day from Sept 17 2014 through June 9 2020 and see if there are any discernible trends. We’ll also explore the profitable strategies to see if any outperform buy-and-hold BTC.
There are 15 backtests in this study evaluating over 6,200 BTC long day trade occurrences.
Let’s dive in!
Contents
Summary
Opening positions Monday morning and closing them Monday captured 16% of the gains with only 4.7% of the time / market exposure.
Avoiding overnight and weekend exposure captured 84% of the gains with only 24% of the time / market exposure.
Methodology
Strategy Details
- Symbol: BTC
- Strategy: Day Trade (positions are held for 24 hours or less, ignoring weekends)
- Days Till Expiration: N/A
- Start Date: 2014-09-07
- End Date: 2020-06-09
- Positions opened per trade: 1
- Entry Days: daily
- Entry Signal: N/A
- Timing: 9:00am ET and/or 4:00pm ET
- Strategies
- Overnight (open position at market close and close at market open)
- Intraday (open position at market open and close at market close)
- Buy/Hold (open position at market open and close the following market open)
- Trade Entry
- Mondays
- Tuesdays
- Wednesdays
- Thursdays
- Fridays
- Trade Exit
- Mondays
- Tuesdays
- Wednesdays
- Thursdays
- Fridays
Assumptions
- Margin requirements are always satisfied
- Margin calls never occur
- Margin requirement for all positions is 30%
Mechanics
- Prices are in USD
- Prices are nominal (not adjusted for inflation)
- Commission to open or close positions is 0.00 USD
- Slippage is calculated according to the slippage table
- For comprehensive details, visit the methodology page
Results
Win Rate
Buy and hold outperformed with regard to win rate vs trading overnight or intraday.
Day trades with a Friday exit yielded the greatest win rate.
Average Win
Buy and hold outperformed with regard to average win magnitude vs trading overnight or intraday.
Day trades with a Thursday exit had the greatest average win magnitude.
Lose Rate
Buy and hold outperformed with regard to lose rate vs trading overnight or intraday.
Day trades with a Friday exit had the lowest loss rate.
Average Loss
Trading overnight outperformed with regard to lose rate vs intraday or buy/hold.
Day trades with a Monday exit had the lowest average loss magnitude.
Compound Annual Growth Rate
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Annual Volatility
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Sharpe Ratio
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Max Drawdwn
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Max Drawdown Duration
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Monthly Returns
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Total P/L
Buy and hold outperformed with regard to total return vs trading overnight or intraday.
Day trades with a Monday exit had the greatest total P/L.
Overall
Profitability of various day trading strategies had mixed results.
Buy and hold outperformed over the duration of the backtest vs trading overnight or intraday.
Kurtosis
Daily returns were binned in 25 basis point (bp) increments and charted against a gaussian (normal) distribution. The distribution curve more accurately aligns with a laplace distribution vs a normal distribution.
Discussion
There are 168 hours in a week. Buying and holding bitcoin over the duration of the backtest yielded over a 25x return (2414.44%). By trading intraday on only Mondays and tying up capital for a mere 8 hours per week, one would have nearly quintupled their money (385.86%).
Said another way, 4.7% of the time in the market captured 16% of the gains. That’s a 3.4x improvement in return per unit of time in the market (capital efficiency).
If returns are reinvested (read: compounded), participating only during intraday hours accounts for 24% of the time exposure and captures 84% of the gains for a 3.5x capital efficiency.
Additional Resources
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June 12, 2020 @ 8:11 am
I am so glad I stumbled across this site while researching how to properly do backtests for my options trading strategies. Thank you!
June 12, 2020 @ 3:56 pm
Hi Jason – happy to hear it’s helpful.
June 14, 2020 @ 3:47 pm
I like the reduced risk by limiting the trading time to 8 hours/week. Good job
August 14, 2020 @ 4:29 am
Hi,
1) with these Strategies, where you close and open a new position intermediately, what will be the difference if you just buy and hold, without selling?
2) in regulated brokers it’s not possible to buy bitcoin (only bitcoin futures, where I think that results will be similar to this strategy) and GBTC
3) When you close a position, in this backtest, it can be a profit or loss, correct?
4) it’s possible to back-test a longer holding period, like 1 week or 1 month? and GBTC?
thank you very much and keep with your great research!
August 17, 2020 @ 12:31 am
Hey Uri —
1) I’m not sure I understand the question. Perhaps restate differently?
2) This is true, and agree the results should be similar.
3) Correct.
4) It is. Is the idea to stratify results by week of month or month of year?
You’re welcome! Appreciate the kind words.
August 17, 2020 @ 5:07 am
Thanks for your answer!
In question 1, I mean, that this strategy will be similar to big and never sell?
what is the advantage of close a position and buy again intermediately?
5) I think that this back-test show a good performance, because it include a big bull market in bitcoin,
if you make this back-test from 2018 to 2020, I think that you will get very different results…
August 18, 2020 @ 12:06 am
Correct, should be similar to buy and never sell.
There is no advantage if the intent is to buy/hold. It’s strictly an administrative activity to measure daily returns. For example, if someone wanted to “buy and hold” only on Tuesdays (granted, this isn’t an actual buy and hold), exiting and reopening the following day does nothing more than allow measuring of the previous day’s performance.
5) It’s quite possible. The same thing happened on the AAPL equity study: https://spintwig.com/aapl-long-day-trade-equity-backtest/#Discussion
The outperforming strategy started underperforming in 2016 onward.
October 25, 2020 @ 12:35 pm
I do not believe you are able to trade BTCUSD commission free anywhere (with the exception of derivatives which obviously complicates everything) so do you think it is likely the backtest results are not very representative when assuming 0% commissions? It would be interesting to see the results assuming the fee structure of a major BTC fiat exchange like Coinbase Pro.
Cheers
October 25, 2020 @ 11:17 pm
That’s a good point.
According to Coinbase Pro the trade fee is a % of the notional traded – 0.5% for amounts <= $10k. https://help.coinbase.com/en/pro/trading-and-funding/trading-rules-and-fees/fees
That's a 1% drag every week! I didn't realize commissions are that high. I guess it's apparent that I don't trade BTC so my assumption is a poor one in this case 🙂
The relative performance of the different strategies stands but implementation is impractical due to costs. I'll look into reproducing this study with the trade fees intact and will be sure to include them in other BTC studies.
Good call!
November 6, 2020 @ 6:52 am
Hi, how will be the results if instead of backtest, BTC, Long Day Trade, you do backtest, BTC, Long MONTH Trade, that means open a position the first of the month, and close it at the end of the month, and then open a new long position…
November 6, 2020 @ 8:35 am
Great question.
Not sure on performance. However, it would be quite susceptible to timing luck. For example, we could open a position on the 1st and close on the 30th, or we could open on 15th and close on 14th. There are essentially 30 variations of this (ignoring Feb), one for each day of the month. Each will have a unique result.
Since BTC only has about 6 years of trading history, that’s only 6 “January” trades. The observation count would be too low to derive defensible stats.