Cesar Alvarez

Author Archives: Cesar Alvarez

External Strategy Rule Evaluation. Too many rules?

A common question I get is where do I find all my research ideas. My main source is Quantocracy. He does a great job of curating posts because the work is manually done. Then there the Better System Trader and Trend Following Radio podcasts. Usually from these sources I get a nugget of an idea to research or a simple strategy. Sometimes the post/podcast will recommend a book.

From one of these sources came the recommendation of the book “Trade Like A Stock Market Wizard” by Mark Minervini. Fortunately for me, my local library carried it. The strategy he covers in the book is a mixed of fundamentals, chart reading and technical analysis. Not something I would normally care about. I really enjoyed the chapters on risk management. In one chapter, he has very specific technical rules that all stocks must follow. On seeing this, I wondered could these rules be a basis for a trend following stock strategy? My second thought was, there are lots of rules there. Are all the rules necessary? The latter question is what I will focus on this post.

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Weekly Mean Reversion Rotation Strategy on S&P500 Stocks

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?

Basic Rules

Testing period is from 1/1/2007 to 10/31/2017.

Setup

  • Stock is a member of the S&P500 index
  • Stock is trading above its 200-day moving average
  • The SP500 index is trading above its 200-day moving average

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

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The ABCs of creating a mean reversion strategy – Part 2

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.

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The ABCs of creating a mean reversion strategy – Part 1

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.

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Indicator Comparison: Ehler My Stochastic Indicator, RSI and ConnorsRSI

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.’

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September 20, 2017

ETF Sector Trading: The effect of daily, weekly and monthly timeframes

I recently gave a presentation on Sector trading using the 200-day moving average at the Northwest Traders and Technical Analysts. Some questions asked were:

  • What if we only trade this monthly?
  • What if we used weekly bars to trade only weekly?
  • What if we used weekly bars to trade monthly?

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.

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September 6, 2017

Broken Strategy or Market Change: Investigating Underperformance

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.

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July 12, 2017

Out-of-sample testing and luck

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 out-of-sample. How you split your in-sample(IS) and out-of-sample(OOS) can change results.

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