Profitable investing can be stressful so a share trading strategy with rules is often preferable to one that is based on hunch or analyst advice. Using rules to trade has a number of advantages. For one, we can trade completely unbiased and objectively. This means we can backtest our trading rules over many years of historical data and make sure they are statistically valid.
Doing so, eliminates the emotions and uncertainty in stock trading and makes investing more professional. Ultimately, it also means we have less work to do. All the work is done in backtesting and programming strategies.
11-Rule Share Trading Strategy
In this example, I will be moving away from technical indicators and concentrating solely on fundamental metrics. Financial ratios such as PE and EPS, the type that can easily be found in financial papers and financial websites such as Finviz.com or Google finance, offer popular ways to value shares which can be used to provide buy and sell decisions.
For this analysis, I used the backtester at portfolio123.com which takes data from a number of sources including Value Line and CapitalIQ. I then set up the following 11 rules in the screener and created a portfolio, rebalanced every 4 weeks.
Rule 1: Market capitalization > $100m
Rule 2: PEG ratio < 1%
Rule 3: Earnings growth over the last 5 years > 8%
Rule 4: 1 year price change > 8%
Rule 5: Dividend yield between 2% and 7%
Rule 6: Net margin last 12 months > 5%
Rule 7: Return on equity last 12 months > 5%
Rule 8: PE < 20 and >5
Rule 9: Price to sales > 0.5%
Rule 10: Lowest PE over last 12 months > 5
Rule 11: Net Margin over last 5 years > 3%
Using portfolio123’s backtest model, the 11-rule share trading strategy was first run over the dates 1/1/2000-1/1/2005 on all stocks on the database. The portfolio returned good results with an annual % return of 28.79%, maximum drawdown of -20.06% and sharpe ratio of 1.44. This compares with a -3.71% annual return on the S&P 500 over the same period.
I then moved the tests forward and ran the portfolio over 2005-2010 and 2010-2014, both of which provided positive returns. To complete the analysis I ran the test over the maximum period on the portfolio123 screener, 1/2/1999 to 1/27/2014. As you can see from the below chart, the average return went down as expected, however, the results are still good with an annual return of 15.56% and sharpe ratio of 0.49.
Once the rules have identified those stocks with compelling investment criteria, it is a good idea to combine more qualitative factors into the mix.
Do you understand how the company makes a profit? Do directors and managers hold shares in the company? Is the stock in a sector that is likely to grow over the next 5 years? Are there any anomalies or adverse comments on the most recent annual report? Have you read the risks section of the annual report?
All of these questions can be answered in order to further improve the share trading strategy as described above.
The results of the backtests are definitely interesting and show that the rules are promising. They could likely be further improved by introducing ranking rules, filters and diversification methods.
There are several limitations with the analysis as is and this must also be addressed in future tests. Firstly, no commissions were set, as portfolio123’s ‘Simulation’ model was not used. Slippage was set at 0.25% and carry cost at 1.5%. Secondly, delisted stocks are not included. Although, from personal experience I doubt that including them would have significant effect.
Nevertheless, the results of the 11-rule share trading strategy show some promise.
EDIT: 02.11.2014: I have recently run the rules based approach as a simulation using commissions of $12 per trade and found very little deterioration in the results.
This Week’s 11-Rule Stock Picks
Using the 11-rule share trading strategy on this week’s market provides the following picks:
Fundamental analysis techniques and technical trading systems and code are included in my new book which is out now, heavily discounted for a limited time period:
Thank You For Reading
Joe Marwood is an independent trader and the founder of Decoding Markets. He worked as a professional futures trader and has a passion for investing and building mechanical trading strategies. If you are interested in more quantitative trading strategies, investing ideas and tutorials make sure to check out our program Marwood Research.
This post expresses the opinions of the writer and is for information or entertainment purposes only. It is not a recommendation or personalised investment advice. Joe Marwood is not a registered financial advisor or certified analyst. The reader agrees to assume all risk resulting from the application of any of the information provided. Past performance, historical or simulated results are not a reliable indicator of future returns and may not account for real world settings. Financial trading is full of risk and margin trading can lead to financial losses totalling more than what is in your investment account. We take care to present accurate analysis but mistakes in backtesting and presenting of analysis regularly occur. Please read the Full disclaimer.
Thank you to everyone who takes the time to leave a comment. Your feedback, constructive criticism and identification of mistakes is welcome. In order to concentrate on work I may not have time to respond to all comments.