11 Rules to Improve Your Trading: Rules 4 & 5

The purpose of this series of posts is to provide a manageable list of fundamental trading rules to help you improve your trading process - regardless of your experience level.  I will also explain the rationale behind each rule and highlight its significance.  Here are the 4th and 5th in a series of 11 rules that will help you improve your returns and reduce your trading losses.

Rule #4: Use Systematic, Objective, Rule-Based Strategies

If you really want to set yourself apart from the average trader (who loses money in the market), develop and trade your own systematic strategies.  I would estimate that fewer than one out of every ten traders use objective, rule-based strategies.  When you use systematic strategies, you remove emotion from your trading, which enhances returns.  It also makes trading much less stressful.

There are two primary types of systematic strategies: signal driven and rotational.  Signal driven strategies use a specific rule or rules to enter and exit trades (for example: buy when the closing price crosses above a moving average and sell when the closing price crosses below a moving average).  Signal driven strategies often include filters or additional conditions that must be satisfied in order to generate the buy or sell signal.  The most common is a trend filter to ensure that all trades are made in the same direction as the prevailing trend (Rule 1).  Various forms of stops can and should be used during strategy development (Rule 2).

As you can imagine, there are an infinite number of technical indicators or rules that you could use to generate signals or use as filters.  Fortunately, a lot of sample code (often from other users) is provided on many development platforms.  In addition, I get a lot of new ideas from Technical Analysis of Stocks and Commodities and from Active Trader.

When I find a new idea that looks promising, I take a few minutes to program the indicator in AMIBroker and graph the results to evaluate how it works for a range of underlying securities over various time periods.  I frequently modify the ideas from the articles based on my own experience as well, but the monthly articles provide a constant source of new ideas and inspiration.  I have provided sample AMIBroker code in several of my posts.

Rotational strategies are typically based on relative strength, which is usually some form of performance ranking of a fixed list of securities.  Rotational strategies usually hold the highest ranking security on the list and/or sell short the lowest ranking security on the list.  New rankings (and the resulting purchases and sales) could be performed daily, weekly, or even monthly.  As you can see, there is no specific buy or sell signal, the rotational model simply holds the highest ranking security or securities on the list.

It sounds complicated, but it is really very simple.  Every systematic strategy must answer only three questions: what to buy, when to buy, and when to sell.

Rule #5: Backtest Your Systematic Strategies

The good news is that I have met a number of traders who use trading rules.  The bad news is that most of them never backtested their strategies.  Using trading rules is a great start, but unfortunately is not enough. There are only two types of systematic strategies, those that have generated positive returns historically and those that have generated negative returns historically.

Would you ever use your hard-earned money to trade a strategy that lost money historically - in the hopes that the future performance would be different?  That would certainly not be rational.  Unfortunately, many traders using untested systematic strategies are probably trading losing strategies.  The odds of identifying trading rules anecdotally (without the benefit of research and backtesting) that will generate consistent, positive returns are extremely remote.

Traders who use untested strategies are in fact testing those strategies, but they are doing it in real time with real capital at risk.  It is much more efficient to test all of your systematic rules in advance and only trade those strategies that are likely to deliver excess returns in the future.

As I have mentioned in other posts, I use and would highly recommend AMIBroker as a research and testing platform.   I am an AMIBroker client, but Trader Edge and Trading Insights, LLC have no affiliation with AMIBroker.  Their software is an inexpensive, yet very powerful and efficient strategy development platform.  The only drawback is that users must have a working knowledge of programming to get the most out of AMIBroker.

Strategy development platforms allow you to develop and test your own indicators, rules, stops, and strategies.  They also provide optimization engines that allow you to evaluate strategies across a wide range of parameters, to ensure your strategies are robust.  Most also provide a number of different metrics to evaluate your strategies: compound annual return (CAR), risk adjusted return, max drawdown, CAR/max drawdown, sharp ratio, profit factor, percentage of winning trades, percentage of losing trades, average profit per trade, and many more.

Optimization tools can lead to over-fitting the data.  As a result, you should use a forward test to ensure the model works outside the test data.  In addition, you must have enough historical data, which helps prevent over-fitting the data.  Finally, always begin with a premise for a given strategy (an assumption as to why the strategy or rule will add value over time) and only use indicators and filters that are consistent with your premise.

Using backtested, systematic strategies will help you generate consistent returns, reduce risk, and eliminate emotion from your trading.  Trading proven strategies will also give you greater confidence and reduce the stress associated with trading.

Related Posts

For more in-depth information on strategy development and backtesting, please revisit these earlier posts:

Proven Stock Screens Earn 20%+ Annual Returns

A More Efficient Relative Strength Indicator

Take the First Step Toward an Investment Process

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Brian Johnson

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About Brian Johnson

I have been an investment professional for over 30 years. I worked as a fixed income portfolio manager, personally managing over $13 billion in assets for institutional clients. I was also the President of a financial consulting and software development firm, developing artificial intelligence based forecasting and risk management systems for institutional investment managers. I am now a full-time proprietary trader in options, futures, stocks, and ETFs using both algorithmic and discretionary trading strategies. In addition to my professional investment experience, I designed and taught courses in financial derivatives for both MBA and undergraduate business programs on a part-time basis for a number of years.
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