Category Archives for "Mean Reversion"
A reader emailed me about testing a weekly mean reversion rotation strategy on S&P500 stocks. My first thought was, why had I not done this type of test before? The very first strategy that I worked on with Larry Connors was this type of strategy. The strategy I will be testing today is a simpler version and different universe but how well will it hold up?
Testing period is from 1/1/2007 to 10/31/2017.
Each weekend, take all the stocks that have setup and then rank using one of the mean reversion methods below. Buy top 5 that are most sold off. Hold 1 week and sell. Then buy the ones that are now the most sold off
This post is the continuation of the steps for creating a mean reversion strategy from the first part of The ABCs of creating a mean reversion strategy – Part 1. You can also listen to part 2 of my interview on Better System Trader here.
A quick recap of the topics covered in part 1. I covered trading universe, indicators to measure daily mean reversion, combining multiple mean reversion indicators, and last bar mean reversion.
I was recently interviewed on Better System Trader, click here for part one of the interview, about the steps for creating a stock mean reversion strategy. I will be covering and expanding on the topics from the interview. These steps, for the most part, would apply to any strategy one is creating. The focus will be a long stock mean reversion strategy using daily bars.
Like all traders, I am always on the lookout for any new indicators better than the ones I am using. I have been using and promoting RSI2 since 2004 for mean reversion trading. I created the ConnorsRSI in 2012. Am I married to these indicators? No. If I find something ‘better’ I will drop them. I came across this article Battle of the oscillators, I had to try it out.
One thing to understand, is that each situation is different. An indicator that works great on ETFs may work not as well on futures. Also, each person has a different metric on what is ‘better.’
I recently had someone email me about the performance of a strategy I created back in late 2005/early 2006 and traded for a few years. I remember the strategy being a daily mean reversion set up with an intraday pullback entry. I figured it probably had not done well over the last decade. I stopped trading in the middle of 2008 because I did not like how it was behaving. In the backtest it did well in bear markets but was not doing so in the middle of 2008.
I ran the strategy from 2007, using the rules as they were published and was pleasantly surprised by the results. A CAR of 25%. Overall not too bad. Wish I had still been trading it. This is an eleven year out of sample test.
In the previous post, Simple ConnorsRSI Strategy on S&P500 Stocks, I showed a simple strategy which I optimized which gave 1,300 variations. Today, I will cover various methods to choose a strategy to potentially trade.
A frequently asked question is how I pick which variation from an optimization run to trade. This post will cover a ConnorsRSI strategy on S&P500 stocks. We will use a wide range on the parameters to give us lots choices to be used in the next post. I the next post, I will show how I take the results and narrow it down to one potential variation to trade. And then the final post, I will cover parameter sensitivity to help determine if the results are likely overfit or not.
3/27/2017 CORRECTION: When I originally posted this, the results shown in the tables were not for the rules shown below. The table results are now matching the rules as below. The spreadsheet also has the corrected results.
My last post on using PercentRank to measure mean reversion proved very popular. A reader looked at the trades and wondered if it would be best to exit after five days because the average trade with longer holds was a loser. I am surprised I have not covered this topic before.
In most of my mean reversion posts, I use RSI(2) to determine if a stock has sold off. In this post, I will explore how to use a stock’s recent return to determine if it has sold off. This will be done in way to normalize the return between low and high volatile stocks. This basic strategy has only two setup rules.
In my last post I showed research on how optimization results can be mean reverting. Sometimes, my research keeps getting side tracked as I think of random ideas to look at. In this post, we look at the random walk my research took starting from my mean reverting optimization research. I will show how changing the start date can have a big change in the results, correlation of 1990’s to now, and random data and how it correlates.