Last Updated on March 6, 2021 by Oddmund Groette
Larry Connors and Cesar Alvarez published a book called High Probability ETF Trading in 2009. All of the strategies covered in the book showed great results, but almost 12 years have passed since the tests were done (up until 12/31/2008). How has the strategy performed since then?
We test the strategy exactly the same way as Connors did. However, Connors didn’t simulate the test as a portfolio. Perhaps needless to say, many of the signals happen at the same time for many ETF’s. Markets are correlated, and especially during panics, we tend to get many signals at the same dates. We end the article by testing the strategy as a portfolio.
You can find more strategies from Larry Connors on this page:
Connors says: quantify, quantify, quantify!
Connors argues the key to success in trading is “quantify, quantify, quantify”, just like “location, location, location” are the three most critical variables for success in the real estate business. We tend to agree. All of the strategies presented in his book are 100% testable, and pretty easy to test as well. No fancy code or deep thinking required.
One of the main objectives for Connors when he develops a strategy, is a high win-ratio, at least 65%. He didn’t argue why in his book, but we assume it’s to avoid behavioral mistakes. It’s very hard to succeed with strategies that have low win-ratios and many losers, but an occasional big winner that makes up for the small losers.
Connors tested only ETFs, not stocks. Why? The argument is simple: An ETF is unlikely to go to zero, while a stock theoretically can go to zero. While an ETF might not go to zero, many of them correlate. Thus, you might get many signals on the same dates. Correlation is often a huge problem for any trader.
The tests were done from the inception of the ETF until the end of 2008. Connors’ tests were done on the 20 most popular ETFs at the time based on volume.
Connors’ rules of the game:
The overall rules of all the strategies presented in his book were as follows. We quote from the book:
- Only buy when the close is above the 200-day average.
- Only short when the close is below the 200-day average.
- Buy ETFs on pullbacks, not breakouts.
- Short ETFs into short-term strength.
- Use dynamic exits. The exits are all based on moving averages.
- ETF correlations change faster than most people believe they do.
- Sector ETFs tend to move from overbought to oversold better than individual stocks.
- Country ETFs tend to move from overbought to oversold better than sector ETFs.
- ETF products are being constantly created. The more you keep abreast of these developments, the better your trading.
Ok, let’s look at the strategy:
The rules of the 3-day high/low method:
The basic principle of the strategy is to but when an ETF has made lower highs and lower lows for three consecutive days. In plain English, the strategy is like this:
- Today’s close must be higher than the 200-day moving average.
- Today’s close must be lower than the 5-day moving average.
- Two days ago both the high and low were lower than the day before.
- Yesterday the high and low were lower than the day before.
- Today the high and low are lower than yesterday.
- If conditions 1-5 are true, then buy today at the close.
- Exit at the close when the close is above the 5-day moving average.
The strategy has seven criteria. Connors also added an aggressive version: Buy a second unit if prices close lower than your initial entry price anytime you’re in the position. This is rather vague, and not considered in our tests.
In Amibroker the code is like this:
Buy= C>MA(C,200) AND C<MA(C,5) AND H<Ref(H,-1) AND L<Ref(L,-1) AND Ref(H,-1)<Ref(H,-2) AND Ref(L,-1)<Ref(L,-2) AND Ref(H,-2)<Ref(H,-3) AND Ref(L,-2)<Ref(L,-3);
For more on why we use Amibroker, you might want to read this article:
The results are summarized in this table:
|Result by Connors||Average gain since||Profit|
|Average gain in %||inception to Nov.2020||factor||Difference:|
The table indicates 13 of 20 ETFs have performed worse since the original test. The equity curve for ILF is a perfect example of this (compounded) :
The most-traded ETF, the S&P 500 (SPY), has this equity curve:
The ETF with the best profit factor, XHB, has this equity curve:
How does the strategy perform as a portfolio?
Let’s assume you go live with the strategy by using all 25 ETFs (the original 20 tested by Connors and the additional five included by us). By having max 5 positions open at the same time and allocating 20% of the equity to each position, we get this result (compounded):
Some facts about the portfolio:
- The average gain per trade is 0.38% on 1616 trades from the year 2000 until November 2020.
- CAGR is 5.74%.
- Win-ratio is 72.3%
- The profit factor is 1.53
- The maximum drawdown is 16.4%. For comparison, the SPY has a max drawdown of 55% during the period.
The worst drawdown happened at the end of July 2011 when the EU debt crisis hit.
The strategy seems to have deteriorated a little but still shows some promise. Most likely it performs better by adding or changing some of the variables.
If you like this article, you might like other articles about trading strategies:
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.