How to Diversify Your Trading Returns

Harry Markowitz, the founder of Modern Portfolio Theory, once said that “diversification is the only free lunch.” Decades since his seminal work in developing mean-variance efficient portfolios that maximize return for a given level of risk, this adage still holds true in most market environments. It is common practice for fund managers to diversify among asset classes based on Markowitz’s findings. However, diversification with his methods can be taken one step further. 

While diversifying your account in all suitable asset classes is worthwhile, a trader can also diversify an account with different trading styles which will create uncorrelated return streams. For example, Perry Kaufman suggests that a well-diversified trader has an ideal mix of three, maybe four, unique strategies. Generally speaking, these three trading styles can be categorized as Trend Following, Mean Reversion, or Pattern Recognition. Furthermore, styles can be differentiated by time horizon.  For example, having short-, medium-, as well as long-term varieties of even one of these three strategies as part of your account will add effective diversification. Each of these three categories has merit on its own, but when combined can offer a more robust solution with less volatility in returns.

Trend Following is considered one of the simplest, yet most robust, trading methods. Kaufman suggests that new traders start with Trend Following since trends will always exist at different points in market cycles. Trend Following also teaches sound risk management since it practices Conservation of Capital. In other words, Trend Following programs take a lot of small predefined losses at the trade level thereby minimizing any large adverse impact from one position. Collectively, over a full market cycle these small losses should be outweighed by the gains. However, during a range-bound, trendless market these losses can amount to a meaningful drawdown. While this is a significant drawback to a Trend Following program, a trendless period is temporary and executing a trend strategy over a complete market cycle should produce positive results and favorable risk-adjusted returns.

Conversely, mean reversion trading prospers during a trendless market. A classic mean reversion strategy will fade the extremes of a range. That is, when a price reaches a high point in a channel, band, or other range barrier a mean reversion strategy will offer a sell signal and capture the pullback move to the midpoint or another level in the range. On the other hand, it will provide a buy signal when the price enters into a predefined lower boundary of the range. Conceptually, it can be seen how this style is complimentary to Trend Following. That is, as breakouts and price extremes lack the follow through necessary to create a trend, the equity curve of a Trend Following strategy will decline due to price reversals stopping out open trades. Meanwhile, the mean reversion program would be generating profits as the trades capture reversal moves when prices remain range-bound. Kaufman suggests that traders use the Efficiency Ratio* to determine the trendiness of a market and test appropriate strategies to find the most robust solution. Some examples of mean reversion trading strategies include pairs trading, intermarket divergence, Bollinger Band divergence, and relative value.

The most unique strategy for diversification enhancement falls into the category of pattern recognition. These trading programs exploit market anomalies such as seasonality, chart patterns, market internals, price shocks, or trading around an expected event. In order to identify seasonal opportunities, traders can run tests on historical data to determine behavioral characteristics for a market or security during a period of the time. For instance, one of the most popular examples of seasonality would be the “sell in May and go away” mantra for the stock market. Event trading takes place by quantifying a market’s historical reaction to an announcement (e.g. an economic report) or price shock and estimating how the price should move based on similar past occurrences. As Kaufman advises, “The profit opportunity does not lie in taking a position ahead of the report and anticipating the market reaction, but in studying the systematic patterns that come after the initial price reaction on the news” (Trading Systems and Methods, Kaufman). Event trading systems recognize patterns that are used for short term strategies and offer another layer of return diversification that can be completely unrelated to trend or mean reversion trading.

The simplest way to begin building a robust trading solution for your assets is to begin mastering one of the three styles mentioned above. Learn from the best practitioners and test your ideas before committing real capital. Finding a strategy that fits your trading personality will take time as you begin to experience the drawdowns, costs, and behavior of the return streams. However, creating your ideal blend of strategies across various asset classes will provide your account with additional benefits from diversification that a simple blend of asset classes alone cannot offer.

As always, please feel free to contact me with any comments or questions. Thanks for reading.

John

*Efficiency Ratio = Absolute value of the net change in price movement over n periods divided by the sum of all component moves, taken as positive numbers, over the same n periods.