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Home Dean Hoffman Articles

Estimating Future Risk

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July 10, 2018
in Dean Hoffman Articles, Uncategorized
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Here, is a scenario to consider. Two money managers have identical MAR ratios. They have the same CAGR and the same maximum drawdown. The investor’s job is to pick the better manager. What tools except for MAR can the investor use?

For many, industry standards like Sharpe Ratio, Sterling Ratio and Sortino Ratio come to mind. Although, it is my opinion that these ratios represent more hindsight than foresight.

Take, for example, the S&P option writing programs of the early to mid-2000’s. One of the best known was ACE Investment Strategies. ACE had performance ratios off the charts (Sharpe, Sterling, Sortino, MAR) with smooth, consistent growth and barely noticeable drawdowns. From just about any measure, investors could not have asked for more. It was the darling of retail brokerage firms with small minimum account size requirements. (See graph below)

 

 

 

 

 

 

 

 

However, just like Long Term Capital Management, Ace experienced a sudden and for most, unexpected implosion! After years of flawless growth, they had close to a 70% drawdown in several months! (see graph below)

 

 

 

 

 

 

 

In hindsight, ratios such as Sharpe were worthless. They lured many people into the lion’s den!

Although, there was one group of risk analysts who did have an excellent handle on the potential for Ace’s implosion. Who was it? The Chicago Mercantile Exchange that is who.

It was the CME that set the margin requirements, and Ace was trading at the high end of margin to equity ratios of 50% and more. Compare this to many CTAs who trade at less than 20% and some less than 10% margin to equity ratios.

It is my opinion that margin usage is a leading indicator of potential risk and drawdowns, but there is one school of thought that thinks using more margin is not always dangerous because it can add to diversification. To some degree, I agree with this, but traders quickly reach a point of diminishing returns.

In the following graph, I have plotted average margin usage against average drawdowns for several hundred CTAs.

 

 

 

 

 

 

 

 

 

 

Traders can clearly see from the data and trend line that using more margin on average leads to higher drawdowns.

The bottom line is that I think the exchanges know better than most what the potential risks are and set margins accordingly. As ones’ margin to equity ratio rises, so does their potential for risk.

Some of us (including me) wrote publicly before the options writer implosion that we thought they were taking too much risk and were prime for such a catastrophic event.

There is another even more obvious benefit to using less margin to get returns. Specifically, investors can use the excess funds to earn better returns elsewhere. Assume there are two managers, who made a $30,000 return. One manager used an average of $30,000 in the margin required, and the other used an average of $15,000 in the margin required. The investor with the second manager would have earned the same returns AND had an extra $15,000 to invest elsewhere.

In summary, what I am suggesting is that investors use margin to equity ratios as a valuable measure when evaluating CTAs (or systems). It can be a valuable tool for estimating risk. We have learned from hedge funds such as Long Term Capital Management, the option writers like Ace, and the trend followers like Michael Clarke that using past drawdowns or risk-to-reward ratios to predict futures ones is far from reliable.

In all the cases above, had one looked at gearing (leverage) might they have seen that a “black swan” was likely? I think so.

 



By: Dean Hoffman

FUTURES TRADING IS NOT SUITABLE FOR EVERYONE AND PAST PERFORMANCE IS NOT NECESSARILY INDICATIVE OF FUTURE RESULTS. THERE IS RISK OF SUBSTANTIAL LOSS IN FUTURES TRADING OR WITH ANY TRADING SYSTEM OR PROGRAM. CAREFUL EVALUATION OF YOUR PERSONAL FINANCIAL SITUATION MUST BE DONE PRIOR TO DECIDING TO TRADE IN THE FUTURES MARKETS OR ANY GIVEN TRADING SYSTEM OR METHODOLOGY.

From: R Quant

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