Category Archives for "Stocks"
I recently read on Don’t Talk About your Stocks about an idea that stocks that were losers after (4, 6, 8) weeks should be sold to make way for other stocks that may do better. Will this idea improve the results from the original DTAYS Weekly Breakout Strategy? This reminded me of research I did while working for Larry Connors. On a mean reversion strategy we were researching, we noticed that after 10 days, 95% of the positions end up being losers. Then came the ‘obvious’ rule to add. Exit a position if it had not bounced after 10 days. We both thought this would greatly improve the results. It did the opposite and hurt them. Why? Because it was better to wait for the bounce even if the trade was a loser.
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.
Continuing on from our previous posts and research, Should one trade high or low volatility stocks? , Stops and trading high vs low volatility stocks, and Low Volatility Stocks and Profit Targets, we are now testing how these results translate to a portfolio. I pick one variation from each of the tables from the Low Volatility Stocks and Profit Targets. From that one a variation we create a portfolio with a maximum of 10 stocks.
In the two previous posts, we have looked at low volatility stocks vs. high volatility stocks with trailing stops. Overall, the data pointed to trading lower volatility stocks. In this post, the focus is on low volatility stocks but now adding profit target stops to see how they can improve the results.
In my last post, Should one trade high or low volatility stocks?, we placed stocks into three volatility buckets and compared their performance. Several readers pointed out that using a fixed percentage stop made it more likely for high volatility stocks to hit the stop thus not performing as well. Readers suggested using an Average True Range stop or a time stop. We will explore those two stops and see how the volatility buckets compare.
Before we get to the tests, I need to explain a new metric I will be using. At Connors Research we use Individual Trade Quality, ITQ, when we were comparing results of non-portfolio tests, such as these tests. The simple way to understand ITQ is it analogous to Sharpe Ratio in a portfolio test. To get more details on ITQ see How to Measure the Individual Trade Quality of Your Strategy.
During some recent research I noticed that picking random stocks in the SP500 produced returns much better than I would expect. This observation was recently echoed by another researcher that I know. Could one make a market beating system by basically randomly pick stocks?
The research that led to this observation was on market timing. Can having a good market timing rule, a profit target and stop loss be enough to randomly pick stocks and beat the market. The answer may surprise you.
After my interview on ‘Don’t Talk About Your Stocks,’ 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
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: