Author Archives: Cesar Alvarez
Author Archives: Cesar Alvarez
I saw this interesting graph the other day on The Big Picture and wanted to know more. Are stocks really moving less in tandem? Could there be another explanation for what is going on? Researching the numbers behind the chart may provide some interesting insights.
From: WSJ
After my interview on ‘Don’t Talk About Your Stocks’, (site no longer exists)’ Andrew pointed me to a strategy he is trading called the DTAYS Quantitative Growth Fund. He was curious to see back tested results. Always looking for new ideas to write and tested, I jumped on it.
Unfortunately, the results will not be exactly as he trades it. Andrew uses the IBD50 as his trading universe. As is the bane to stock researchers, I do not have historical data on the IBD50. One could create some great models using that data. Instead, the test will be on the standard stock universe
Last week I was interviewed by Andrew Selby of Don’t Talk About Your Stocks. We covered lots of topics in the 45 minute interview. We covered my trading mistakes, why you need a trading buddy, matching your trading style to your personality, and many more topics.
Link: http://www.donttalkaboutyourstocks.com/dtays-016-cesar-alvarez/
If you have any questions from the interview, post them in the comment section of this page.
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).
The ‘Intermediate Term Stock Rotation Strategy Using S&P500 Stocks’ post generated lots of reader suggestions on what to investigate further.
The ideas we will investigate are:
I have been shorting stocks since 2006 using a quantified strategy that has remained relatively unchanged through the years. From 2006 to 2012, the strategy was one of my most consistent and profitable of all the strategies I have traded. I love shorting stocks because it is very hard psychologically, because of that, I believe that there is a good edge there. The test results have always bothered me because of the differences between back tested assumptions that sometimes are challenging to actually reproduce in real-world trading. Then in 2013 my fears became realized and all four fears below really hit me.
One of my research goals for this year is to find an intermediate term rotation strategy using S&P500 stocks. Then right on cue, I read the following post Intermediate momentum! which points to research Is momentum really momentum? by Robert Novy-Marx. In that he mentions that “intermediate horizon past performance, measured over the period from 12 to seven months prior, seems to better predict average returns than does recent past performance.” I have never tried an idea like this. In the blog comments, a user says he got great results using the current NDX100 stocks not the historical. This introduces pre-inclusion bias but maybe the results will still be good. What a great way to start the year with ideas I have never tested.
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.