I’m no crypto expert, and I’m no trading guru.
This is why the simplicity of the Turtle Trading Strategy appeals to me.
As of this writing, since February 14, 2018, I have seen my account go up 19% while Bitcoin is down 57% ($8520 to $3675).
I’ve done it by following the Turtle Trading Strategy, trading long on 12 different coins, and short on 4 different coins.
There isn’t enough data to say whether this strategy “works” for crypto, but I like it so far.
The Turtle Trading strategy tells me exactly:
- When to get in (long or short)
- How much to risk (exactly how much of a coin to buy on every trade)
- When to get out (take profits or stop losses)
I don’t have to stress out about whether I should wait until the coin drops another percent before I cut my losses. I don’t have to know the fundamentals of any coin. I don’t have to understand what a head and shoulders pattern is (or pretty much any other technical indicator). I don’t have to wonder how much of my account to use for a trade. I don’t have to belong to a crypto trading forum or read articles about crypto, and I don’t have to watch the markets all day.
Check out these explainer videos showing my process.
How I Decided to Start Using Turtle Trading:
When I stumbled onto a reference to the Turtle Trading System in this article, I had been trading cryptocurrency on GDAX for about 2 months. I had been very lucky to buy in when everything was going up (November 15, 2017) and of course thought I was a fucking genius. I would buy in when a coin had been going up for a day or so, and sell when it dropped 10% from its recent highs. This was working very well for about a month when the market was skyrocketing to $20,000/BTC.
But then everything started falling, and I quickly realized my “system” was garbage. Not only that, it was a really stressful way to trade, because I had no clear buy and sell signals. I would just be guessing. I would lose 10% of my account in a day on a coin that had been on a good run, or I’d be all-in on one coin that was flat while another coin was rising.
What I wanted is what everybody wants – a system that is stress-free and works more often than it doesn’t.
After reading this article and trying to use the script it referenced to backtest Turtle Trading on Tradingview.com with not great results (I’m not very good at writing even simple code, and I didn’t see myself taking the time to learn), I wanted to know more about the details of the system.
I read the articles I could find about turtle trading and crypto (very limited at that time), checked out trendfollowing.com, and read the book called The Complete Turtle Trader by Michael Covel, hoping to get some definitive answers about whether this system was legit, and whether it would work right now with crypto trading.
I was hoping to see whether there was any data showing how the system worked in real life instances, not just cherry-picked examples where a stock or coin made a meteoric rise and pretty much anyone would have made money.
The book was an interesting read, but it didn’t reference many actual trades or sets of trades by the turtles. The articles I read about turtle trading and crypto (at least the ones that weren’t meant to sell me anything) also didn’t seem to really understand the system very well – not well enough for me to rely on their analysis.
So, I decided the only way I was going to get the answers I wanted was to start tracking several coins on my own.
Before you keep reading, you should have already read this PDF (45 minute read) describing the system to understand the basics of what I’m describing here.
I set up a spreadsheet and manually tracked every first entry trade for Bitcoin, starting on October 26, 2013 for all 3 turtle trading methods (20-day high/low entries, 55-day high/low entries, and the Whipsaw Method). I didn’t track the ½N trades after the initial trade because of the added complexity.
Then I did the same with 12 altcoins starting on November 15, 2017.
I knew early on this wouldn’t provide me with “proof” because there wouldn’t be enough data (and because the markets are so young, the trends are changing quickly, so data from 2013 doesn’t necessarily apply to 2018). Nevertheless, it did give me enough information to want to continue to investigate further.
Need more info? Check out these explainer videos.
I used the free version of tradingview.com as a reference and recorded the trades, and it took approximately 100 hours to complete. Now, I take 15-20 minutes a day to update all the research.
This process helped me understand how the system works, and although isn’t near enough trades to be statistically reliable (I’ve tracked about 350 trades, and I think a couple thousand trades would be necessary to come to any legitimate conclusions), it gave me as much information as I needed to start using the system in real life.
On February 14, 2018, I committed to following the system until at least the end of 2018. I’m currently still turtle trading.
To stay on top of the markets, I set up another spreadsheet that I use to track the 10 and 20-day highs and lows for Bitcoin and 12 altcoins.
When a coin gets close to an entry (20 day high or low), I plug the numbers in to know exactly how much of my account to use for each trade. This is based on the 20-day Average True Range and the risk management strategy of never losing more than 2% of my account per trade.
Then, I set up trades to trigger at the appropriate time. Once the trades happen, I set up stop-losses and wait. It’s pretty simple, as long as I follow the rules.
Since February 14, 2018, the system I’m using is doing better than the market (which has been in bear-mode pretty much the whole time).
My Results Don’t Exactly Match the Research:
Hindsight is 20/20, and when you’re doing research you never miss a trade or get out too early or too late. There’s also a lot of price sliding that can occur while buying or selling. Transaction fees are hard to build into the research. Sometimes these cryptocurrency exchanges will have abnormal spikes or dips that the historic data doesn’t show. Therefore, the results I’ve had with my own account are not the same as what the research shows.