All about risk

November 29, 2015 11:00 AM

Risk management is often cited as a key to success for managed futures strategies. Despite this claim, the process and tools for validating this statement have remained somewhat elusive for investors of Commodity Trading Advisors (CTA). Investors often are given descriptive statements and must base their decisions on qualitative analysis. Here we quantify CTA risk management. The multi-factor model incorporates key aspects of portfolio construction including liquidity considerations, correlation, volatility adjustment and capacity constraints. 

Factor-based return analysis is a commonly used technique for performance evaluation. The use of factors to understand return drivers and portfolio construction has a long history in the equity space. Only recently, Greyserman and Kaminski (2014) applied a multi-factor model to examine CTA style factors focusing on three construction styles based on market size, equity bias and trading speed. This article reveals a modified framework for factor construction that focuses on risk management. The key difference is that each risk management factor focuses primarily on how risk is allocated in a portfolio, not on how momentum signals are constructed. 

Portfolio construction demonstrates how varying risk allocation can be used to construct risk management factors based on liquidity, correlation, volatility and capacity. To investigate the impact of risk management factors in aggregate, the Newedge Trend Index is examined for exposure to risk management factors. In a simple analysis, several risk management factors demonstrate significant exposure in the Newedge Trend Index. A similar analysis is then applied to a set of daily managed Futures 40 Act mutual fund strategies. This suggests that risk management decisions may help to explain CTA performance relative to a benchmark.

Futures portfolio construction

Futures portfolios are built by taking positions in futures contracts across an array of markets, and are defined by the size of a position in each market. One simple way to determine the position size for each market is the following equation:

Market conviction defines the direction and the level of confidence for each market. Market risk allocation is the amount of risk allocated to a particular market. Given the conviction and the risk allocation, each position (in a number of contracts) is set by the amount of volatility in each particular market. For example, if corn is not very volatile and oil is very volatile, the position in oil will be smaller, all other things equal. Each position allocates a certain amount of risk. At the portfolio level, the portfolio scaling factor scales positions up or down to achieve a total risk target for the entire portfolio. 

For many CTAs, portfolio construction can be simplified into a three-step process: Valuation/model conviction, risk adjustment and measurement and risk allocation. For trend-following portfolios, valuation and model conviction are determined by quantitative models. This often is determined by moving average or channel breakout models. The magnitude is often called the trend strength and the sign determines a short or long trend position. Once the model conviction is determined in step two, the position sizes are set based on the volatility of each market.

Finally, in step three, risk is allocated across markets. If no additional considerations are added in step three, the portfolio equally allocates risk. In practice, there may be other considerations that can shift risk away from equal allocation. For example, considerations such as liquidity, trading costs, inter-market correlations, position and risk limits, capacity considerations and other portfolio constraints also may be relevant. Adding these considerations can incorporate risk management aspects that move portfolio risk away from equal risk allocation. 

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About the Author

Kathryn M. Kaminski holds a PhD from the MIT Sloan School of Management as well as visiting lecturer positions at the Stockholm School of Economics and MIT Sloan School of Management. Her research interests are in portfolio management, behavioral finance and alternative investments. She is an investment researcher at RPM Risk & Portfolio Management. Contact her at