Author Archives: Cesar Alvarez
Author Archives: Cesar Alvarez
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.’
The reason for these questions was to reduce the frequency of having to check signals and the total number of trades. My first response was that the results would probably be a little lower and the trade count also would be lower. But that was just a guess. I have been doing this long enough to know that I wrong 40% of the time. Curiosity got the better of me and I tested it out.
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.
Several readers asked for additional tests to be done on the strategy on Sector trading using the 200-day moving average. We will be testing allocated 11% per ETF instead of 10%, using asymmetric number of days and adding IEF to the SPY MA200 10 day test.
A user commented on ETF Sector Rotation post about a simple idea for trading the sector ETFs, which I can’t believe I have never tried. I like keeping things simple just like my Brazilian Jiu-Jitsu game.
Continuing from the last post, I will show how using different definitions of passing our out-of-sample test can change our results. How luck can play a role if you use only one strategy to test in out-of-sample. How you split your in-sample(IS) and out-of-sample(OOS) can change results.
I am frequently asked if I do out-of-sample testing. The short answer is not always and when I do, it is not how most people do the test. There are lots of considerations and pitfalls to avoid when doing out-of-sample testing. Out-of-sample testing is not the panacea it is made out to be. There are lots of grey areas which I will discuss below.
As long time readers of my blog know, I often use a market timing indicator in my strategies. My favorite one, and a simple one, is using the 200 day moving average on either the SPY or S&P 500 Index. I recently ran into these posts, Using Market Breadth To Gauge Market Health (Part 5) and Matt’s Breadth Indicator. Matt’s Breadth Indicator (MBI) intrigued me because I had not seen something like this and conceptually it is simple. I also liked that it was not “easy” to test or optimize on. Therefore hopefully not many people would be using this indicator and I could potentially find better values.
In Simple ConnorsRSI Strategy on S&P500 Stocks I showed a ConnorsRSI strategy on S&P500 stocks. In ConnorsRSI Strategy: Optimization Selection, I narrowed down the optimization to three potential variations that one could consider trading. This post will explore Sensitivity Analysis (also known as: Parameter Sensitivity) to help guide us on what to expect from each variation.