Category Archives for "Mean Reversion"
My second post on this blog was a look at mean reversion, Is mean reversion dead? Given I am using a new data provider(Premium Data), it has been almost two years since that post and there have been other articles on this recently, I figured it was time to check again. The research will focus on Russell 1000 stocks since 1995. The test is back to 1995 covers 3 bull markets and 2 bear markets.
We hear it all the time. “You must use stops.” And most of us use them. But do you know how they change your strategy results? Are they improving your results by giving you higher CAR or lower maximum drawdown? Recently I was speaking with a reader about this topic and he insisted that it you had to have stops to trade. Well, does one?
How should one develop a strategy for leveraged ETFs? Do you develop the strategy on the unleveraged ETF and then apply the rules to the leveraged ETF? Or do you develop the strategy on the leveraged ETF directly? Or do you develop the strategy on the unleveraged ETF then use signals on that to trade the leveraged ETF? On first blush one would think that all three methods would produce identical results. But as we know, the obvious is rarely the right thing for strategy development.
This post will cover in detail two different ways of doing Monte Carlo analysis and the code needed to it in AmiBroker. A reader recently sent me this article, Monte Carlo Analysis For Trading Systems. The article covers three methods of Monte Carlo analysis. One of which I had never thought about and I had to slap my head on how simple it was.
The Simple Ideas for a Mean Reversion Strategy with Good Results post generated lots of comments and emails about other ideas to try. This post will cover three of the most interesting ones.
A reader sent me some trading rules he got from a newsletter from Nick Radge. He wanted to know if these rules really did as well as published in the newsletter. They seemed too simple to produce such good results. The strategy as presented was long and short and went on margin but he wanted to know how it did the long only since he did not short. After contacting Nick Radge at The Chartist, I confirmed with him it was OK to publish these rules.
Over the last month several people have asked me how important it is to have survivorship-free data. For any researcher this is an important question to understand how the different data can change your results. We will be exploring three potential data issues: as traded prices, delisted stocks (survivorship-bias), and historical index constituents (pre-inclusion bias).
As of Friday’s close, the SPX has closed above its 10 day moving average for 17 days. What does the market do when it finally closes below the MA10? Which S&P500 stocks do we want to focus on when it finally does?
My article on “Is mean-reversion dead?” produced lots of suggestions from readers on other tests to try. We will jump right in and look at what these research suggestions produced.
My great friend and expert trader Steven Gabriel often pushes me to answer this question; and prove it. We, perhaps too fondly, remember the great mean reversion trading years of 2005, 2006, 2008, 2009, 2010. We discussed this topic often in 2011 and 2012. Steven Gabriel would often call me on days when in the past, we would both be making 5+% on a day that our stocks would be mean reverting, but now we would be making a mere 1%.
My theory is that mean reversion is in hibernation waiting to come back; or said another way, mean reversion is simply mean reverting. I think that when too many people trade mean reversion, the space gets crowded and we see fewer winning trades and smaller returns. However, this has always been conjecture never backed up with numbers. Are we really seeing fewer trades? Smaller returns? Time to do the research and see what the numbers tell us.