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Managed futures are part of anAlternative investmentstrategy especially in the U.S. through which professional portfolio managers make extensive use of Futures contract as a part of their overall investment strategy. Such strategies aid in mitigating portfolio risks which are difficult to achieve in direct equity investments.

In this article, we cover the following

A managed futures account or managed futures fund is a type of alternative investment through which trading in the futures marketis managed by another person or entity instead of the funds owners. These accounts are not necessarily limited to commodity pools and are operated by Commodity Trading advisors (CTAs) or Commodity Pool advisors (CPOs), which are generally regulated in the U.S. by the Commodity Futures Trading Commission (CFTC) through National Futures Association before they can offer services to the general public. These funds can take either a buy (long) or sell (short) positions in Futures contracts and options in the Commodities (cotton, coffee, cocoa, sugar) Interest rate, Equity (S&P futuresFTSE futures) and Currency markets.

Managed futures are one of the oldesthedge fundstyles, having been in existence since the past 3 decades. The CTAs are required to go through an FBI background check which is required to be updated every year and to be verified by the NFA.

The strategies and approaches within managed futures are extremely varied. The one common unifying characteristic is that these managers trade highly liquid, regulated, exchange-traded instrument and foreign exchange markets. This permits the portfolio to be marked to market every day.

Trend following CTAs develop algorithms to capture and hold longer term trends in the markets which may last from several weeks to a year. They make use of proprietary technical or fundamental trading systems or a combination of both.

Counter trend approaches attempt to capitalize on the dramatic and rapid reversals which take place in such long-term trends.

One of the benefits of including managed futures in a portfolio is risk reduction through portfolio diversification by means of low or negative correlation between asset groups. As an asset class, managed futures programme are uncorrelated with stocks and bonds. For e.g. during times of inflationary pressure, investing in managed futures which trade in commodities and foreign currency futures can provide a counterbalance to the losses which may occur in equity and bond market. If stocks and bonds are underperforming in inflationary scenarios, managed futures might outperform in the same market bining managed futures with other asset classes may improve risk-adjusted portfolio returns over time.

The benefits of Managed Futures can be summarized as follows:

Potential for returns in Up and Down markets with the flexibility of taking long and short positions which allows for profit in both rising and falling markets.

Non- Correlation to traditional investments like equities and bonds.

Despite these benefits there are certain drawbacks of managed future strategies:

The returns for indexes of CTA managers tend to be biased upwards due to the voluntary nature of self-reporting of performance. A CTA with a less impressive performance for a length of time is less likely to report unfavorable returns to such databases, resulting in an index that mostly includes impressive performance.

Other asset classes like Equities or bonds have a natural benchmark for performance reporting. Market capitalization weighted benchmarks for traditional investments mathematically represent the average return applicable to the investors. Such aggregate performance measures are difficult to apply in case of managed futures space.

CTAs are known to charge very high fees for their services. Generally, the fee structure is similar to that a hedge fund utilising the 2/20 structure (2% Management Fees and 20% Performance fees on achieving a high water-mark)

While discretionary CTA managers still exist, the majority of managed futures trading advisors comprises strategies which rely on systematic, computerized approaches to generate market trading decisions. Theoretically, systematic trading strategies strive to eliminate any chance of generating alpha. However, with investment decisions, there are certain strengths and weaknesses associated with systematic strategies:

Decisions are determined by computer models, which guide in maintaining a consistent and disciplined investment approach by removing emotional hurdles and reliance on manager discretion.

Allows for the historical study of price data to research, develop and test strategies so that results in a repeatable process which can be quantified and studies to improve consistency.

Construction of the portfolio using various markets and sectors to increase diversification.

Investing in a passive manner reduces the impact of certain traditional obstacles of investing in CTAs. It also reduces the burden of how to find and monitor the best CTA managers.

System based trading are unable to adapt to news or environments which are different from past environments through which the models were initially derived.

The amount of fees charged is very high which may not necessarily balance out the effects of any downfalls which can be caused due to choppy conditions.

Risk management is often seen as a key success for CTA strategies. Futures portfolio is built by taking positions / exposures in futures contract across various markets.

View CourseRelated CoursesFixed Income CourseBond Trading CourseFixed Income Mathematics Course

A simple way to determine the position size is the below equation:

Portfolio size = Portfolio scaling factor * (Market Conviction * Market Risk allocation) / Volatility of the market

Market conviction defines the direction (buy or sell) and the level of confidence of each market. The market risk allocation is the quantum of risk allocated to an individual market or industry. Given these factors, each position in number of contracts is set by the amount of volatility in each market. For instance, if Salt is less volatile and Oil is highly volatile, the position taken will be smaller, all other aspects remaining equal.

For many CTAs portfolio construction can be simplified into a 3 step process which can be displayed with the help of the below diagram:

If the portfolio construction process is simplified into the above stages, stage one is Model conviction, while stages two and three indicate risk management.

Once stage one is separated from risk management and kept constant, risk management decisions can be isolated for creating risk management based factors. The risk management process is dependent on the below factors:

The Liquidity factor measures the effect of allocating relatively more risk to highly liquid markets like the money markets. Liquidity is defined by the volume and volatility for each market. In terms of the liquidity factor, the risk allocation across markets will tilt more towards the liquid markets. When this factor indicates a positive return, it means that a portfolio which allocates more risk to more liquid markets outperforms the equal dollar risk portfolio.

The Correlation Factor measures the effect of incorporating correlation into the risk allocation process. This allocation is determined by ranking the markets based on their correlation contribution for each market. When a market is highly correlated with multiple other markets but the initial markets is not in an offsetting position, less risk shall be allocated to it. The idea is that if one market is falling, the other market should be in a position to compensate for the same. When the correlation factor returns are positive, it means that a portfolio incorporating correlation in risk allocation outperforms equal dollar risk portfolio.

The Volatility Factor measures the effect of reacting more slowly to changes in the market volatility through the volatility of market mentioned in the above equation. The strategy will generally involve a 3 month look-back period which means the volatility will be analysed in the past say 3-6 months. A positive return for this factor means that over that time frame, the portfolio with the slower volatility adjustment outperforms the baseline.

The Capacity factor measures the effect of re-allocating risk based on capacity constraints. This factor compares the performance of a portfolio which trades at $20 billion in capital with the baseline strategy trading at $5billion in capital. The same volatility target, limits and restrictions are applied to each of the $5bn and $20bn strategies, except few of these limits are more binding for a larger portfolio. In response to these limits, a larger portfolio will re-allocate risk to other positions for achieving the total risk target. When the capacity factor returns are positive, it is an indication that the portfolio shall outperform the baseline portfolio.

For every individual factor, the impact of each risk management aspect can be measured across the set of included markets (equities, commodities,fixed incomeand currency).

The below table indicates the performance statistics for the benchmark strategy and the above risk management factors.

Since 2001, the liquidity and correlation factor returns have been positive on average while the volatility and capacity factors have been on the negative trend. The Capacity factor has the most negative realised Sharpe ratio during this period indicating re-allocation of risk due to capacity constraints underperforming the baseline strategy by 0.94% per year on average from 2001-2015.

The correlation factor became more positive post 2008 though the element of volatility continues to exist suggesting that adjusting risk for correlation would have improved portfolio performance post 2008. The liquidity factor was positive prior to 2005 and again post 2011. There seems to be certain time periods where the capacity constrained portfolio either underperforms or outperforms the targeted baseline strategy (trading at $5billion). This suggests that exposure to capacity constraints can cause performance to deviate from the baseline strategy.

TheSharpe Ratio is a measure for computing the risk-adjusted returnand has become an industry standard for such calculations. It is computed using the below formulae:

Sharpe Ratio = (Mean Portfolio Return Risk Free Rate) /Standard deviation of portfolio return

A draw down is a period of negative positions i.e. the percentage change in the NAV between a high peak and subsequent trough. It takes into account the accumulated losses over a period of time i.e. multi period risk measure. A draw down is not necessarily a sign of distress, but tightly connected to the fact that the markets are not always trending, and managed futures programmes in general are expected to generate positive returns during such periods.

A maximum drawdown is the worst case scenario a CTA manager has experienced since a specified period of time most commonly, since inception. For correct evaluation, corrections should be made to the account for track length, frequency of measurement and volatility of the asset.

The Calmar ratio was developed as an alternative to the Sharpe ratio which is known to have its own shares of flaws. This ratio is used to evaluate a return from one period to against the maximum draw-down the program has experienced during the mentioned period.

Calmar Ratio = (Annualised Return t)  / (Maximum drawdown t)

A high calmar ratio indicates that for a given annual return, the manager had attained a low draw-down.

Being in possession with more information never hurts and it can help avoid investing in CTA programmes which do not fit investment objectives or risk tolerance ability, an important consideration before investing with any money manager. Given the proper due diligence about investment risk, however managed futures can provide a viable alternative investment vehicle for small investors looking to diversify their portfolios thereby spreading their risks.

Filed Under:Risk Management BasicsDerivatives Basics

worked as JPMorgan Equity Analyst, ex-CLSA India Analyst ; edu qualification – engg (IIT Delhi), MBA (IIML); This is my personal blog that aims to help students and professionals become awesome in Financial Analysis. Here, I share secrets about the best ways to analyze Stocks, buzzing IPOs, M&As, Private Equity, Startups, Valuations and Entrepreneurship.

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