Author Archives: Cesar Alvarez
Author Archives: Cesar Alvarez
This extended research is from two readers’ requests. Request one is adding stop losses on the “Monthly S&P500 Stock Rotation Strategy.” Request two is seeing the equity curves from “Percent S&P500 Stocks Trading Above MA50 as Market Timing Indicator.”
From the “Should You Buy the Best or Worst YTD Stocks” post, several readers made comments if one could make a monthly rotation system from this idea. From that post, buying either the strongest or weakest stocks out-performed the SPX with the weakest giving the best results. Will that be the case again?
Does the percent of S&P500 stocks trading above their 50 day moving average predict future market returns? Over the last several weeks, I have seen several charts of the percent of S&P500 stocks trading above their 50 (or 200) day moving average overlaid on the S&P500. From these charts, it appears one could build a market timing indicator. The concept really looks like it has promise.
Chart from April to November 2013.
Is it better to buy the worst year-to-date performing stocks or the best year-to-date performing stocks for the month of December? Common wisdom would say stay away from the losers because those are the one that people are selling for tax reasons. Are fund managers buying the winners for window dressing?
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.
In the previous post “Which S&P500 stocks to focus on when the SPX has 5 higher closes,” we discovered which stocks (from the S&P 500) produced the best returns when the market closed higher five consecutive days . The results from that work, as often happens, suggested a deeper look; specifically, can those concepts be applied to S&P 500 stocks without having to wait for specific market conditions (e.g. five up days in the SPX)? If so, maybe this is the start of a viable, standalone trading strategy. As indicated, this post builds on the previous post, so please refer as needed.
Rob Hanna had a good post recently; titled What the String of 5 Higher Closes Under These Circumstances is Suggesting . With mean reversion trading, you are expecting stock prices to snap back towards their mean, like a rubber band stretched too far. But, sometimes, that rubber band can be stretched so far that it breaks (and therefore, won’t snapback). For some time, I have been searching for how to tell when that rubber band is stretched so far that it is broken. Rob’s post had several key concepts that might help us to solve this puzzle and possibly even be the foundation of a stock strategy.
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.
When I buy a stock, I know the edge is for the stock to go up. I know that does not mean every stock is a guaranteed winner. Or that my losses will be small. But every now and then you get what I call a broken arrow. I was in Expedia (EXPE) as it triggered in my SP500 rotation system. It was in a nice up trend, everything looking great.
And then …earnings happened.