Last Updated on January 21, 2021 by Oddmund Groette
Today we continue backtesting the strategies Larry Connors and his team published in 2009 in a book called High Probability ETF Trading. All the strategies were tested on a basket of 20 liquid ETFs. The previous articles can be found on our page containing many different quantified trading strategies:
12 years have passed since the book was published and it could be interesting to know if the strategies are still performing well.
Today we look at the strategy in chapter 4: The R3 Strategy:
The rules of R3:
The rules are pretty simple:
- The close must be above the 200-day moving average.
- The 2-day RSI drops three days in a row and the first day’s drop is from a reading below 60.
- The 2-day RSI is today below 10.
- If number 1 to 3 is true, then enter at today’s close.
- Exit on today’s close if the 2-day RSI is above 70.
This is all there is to it. Connors added an aggressive version as well: Whenever the position closes below your entry point, add a second unit. We will not test the aggressive version in this article.
The code in Amibroker:
We like to use Amibroker and Tradestation, and in Amibroker the code looks like this:
Buy= RSI(2)<10 AND RSI(2)<Ref(RSI(2),-1) AND Ref(RSI(2),-1)<Ref(RSI(2),-2) AND Ref(RSI(2),-2)<Ref(RSI(2),-3) AND Ref(RSI(2),-3)<60 AND C>MA(C,200);
For more on why we use Amibroker, you might want to read this article:
The results of R3:
We tested the strategy on the data used by Connors. Unfortunately, we didn’t manage to replicate the results 100%: we got fewer fills. Both Connors and we tested on dividend-adjusted data sets, so we are not sure why our results differ slightly.
Anyway, the table below summarizes both Connors’ and our results. Our results cover the whole period the ETF has been listed (since inception) until December 2020 (no commissions and slippage included):
|Result by Connors||The average gain since||Profit|
|The average gain in %||inception to Nov.2020||factor||Difference:|
About 50% of the strategies performed worse in the last 12 years. The five ETFs at the bottom of the test were not part of Connors’ test, but we added them nevertheless (GDX, GDXJ, TLT, XLP, and XME).
The equity curve for the S&P 500 looks like this (SPY, compounded):
For the Nasdaq (QQQ) it looks like this:
How does the R3 perform as a portfolio on all ETFs?
One thing is to test a strategy on one ETF at a time, but more importantly, might be to test it as a portfolio on different ETFs.
Let’s simulate the results on all 25 ETFs from the year 2000 until December 2020. The buy and sell criteria are the same as above, but we include a maximum of five open positions at any time and a maximum 20% of equity for each position. The equity curve looks like this:
The number of trades is 992, the win-ratio is 75%, the average gain per trade is 0.68%, and the profit factor is 2.08. The sovereign debt crisis in 2011 hit the portfolio hard, and the maximum drawdown was during August 2011: -16%. CAGR is 6.47%.
All in all, we would say the strategy performed well, and obviously, this strategy doesn’t fit all markets.
The R3 strategy on Nasdaq and the S&P 500 as a portfolio
Most traders are interested in how it performs on the Nasdaq and the S&P 500. Below is the equity curve with 50% of the equity allocated to each trade in QQQ or SPY (can hold 1 or 2 positions at any time):
The R3 strategy is still working, 12 years after its inception. This is a mean-revertive strategy and works best on equity markets.
We believe the strategy can be improved with certain small changes.
Disclosure: We are not financial advisors. Please do your own due diligence and investment research or consult a financial professional. All articles are our opinion – they are not suggestions to buy or sell any securities.