With Thanksgiving quickly approaching, fund investors can give thanks for the rich returns on their fund portfolios (undiversified MLP turkeys notwithstanding). After, what is looking to be, a very good investment year, it is natural to worry about protecting capital gains, especially in a market that feels increasingly toppy both on the credit and equity side.

While there are many "market-top" investment strategies available to investors, which we will explore in later articles, one strategy that has received some attention, notably from the likes of Andrew Lo as well as the AQR shop crowd, is a risk-control strategy. This strategy sizes the investment portfolio based on the realized volatility of its recent performance. So, a higher volatility of portfolio returns will result in the reduction of the position, thus dialing down risk and vice-versa.

One common criticism of this strategy is that dialing down risk in a period of high volatility is akin to "closing the stable door after the horse has bolted". In other words, reducing risk when volatility is high and, presumably, risky assets have sold off, results in a strategy that is likely to sell low and buy back high. In fact, investors are typically advised to buy assets when prices are low - Buffett's dictum of "be greedy when others are fearful" captures this sentiment. However, this sentiment assumes that assets are mean-reverting which, of course, is not always the case. And most importantly, it is not the case particularly when risky assets have their worst drawdowns and when buy-the-dip strategy no longer works. Examples of 2008 equity market and 2016 energy market come to mind.

With that out of the way, let's take a look at a risk-control strategy as applied to the AUM-weighted closed-end fund population. We construct a total return index for the last 10 years of all closed-end funds currently trading. We then calculate the 1-month rolling volatility of weekly total price returns.

We use this volatility as the signal of whether or not to be invested in the index. The thick blue line below is the total return of a strategy that is always invested in the index. The other lines refer to total returns of strategies that reduce index exposure to zero above a certain level of realized volatility: from 15% to 30%.

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**What do we find?**

Strategies that reduce index position to zero above 25% and 30% volatility outperform the always-invested strategy which, in turn, outperforms the strategies that reduce index position to zero above 15% and 20%.

The basic result here is that strategies that stop out at very high levels of volatility have prevented extreme crashes of portfolio wealth so as to outperform in the long term. However, strategies that stop out at lower levels of volatility miss out on high returns during volatile market periods so as to underperform the always-invested strategy.

All of the risk control strategies have significantly superior Sharpe Ratios to the always-invested strategy which suggests they are more appropriate vehicles for the use of leverage. For example, at the same level of volatility, the worst risk control strategy of (15% volatility trigger) has a 4.3% higher return than the always-invested strategy.

We do need to be careful here and point out that we don't take transaction costs into account (these are generally low for liquid closed-end funds) or leverage (which is no longer cheap with short-term rates heading higher).

1M Vol | Return | Volatility | Sharpe Ratio | % Invested |

All | 7.0% | 16.5% | 0.42 | 100% |

30% | 8.8% | 9.3% | 0.95 | 96% |

25% | 8.6% | 9.2% | 0.93 | 95% |

20% | 6.1% | 8.4% | 0.73 | 92% |

15% | 5.0% | 7.3% | 0.70 | 83% |

Source: ADS Analytics LLC |

**Thoughts on the Results**

- The outperformance of the 25% and 30% strategies is robust to the post-GFC period, so they still outperform the always-invested strategy
- The post-GFC period has been one of generally mean-reverting risky assets, which suggests why the 15% and 20% volatility strategies underperform on a total return basis
- The relationship of volatility to returns appears to be non-linear such that foregoing medium level of volatility is detrimental to portfolio returns, but foregoing high levels of volatility is beneficial to portfolio returns
- We do not include an out-of-sample performance period, given the relatively short time period under examination as well as the lack of high volatility periods in recent history
- Our CEF index includes very different types of assets, so the conclusion may be different for single-sector strategies
- A longer volatility lookback period (3 months over 1 month) has similar results, though the very high volatility strategies do not significantly outperform the always-invested strategy on a total return basis. All risk-control strategies outperform the always-invested strategy on a Sharpe Ratio basis
- The analysis assumes that the investor's utility function is maximizing total returns rather than current level of yield
- The phrase that "one cannot eat Sharpe Ratio" is true enough. However, the distribution rates of many CEF sectors are high enough to justify a moderate amount of leverage, which means that investors do not need to leave yield on the table in order to benefit from risk control

**Where does this leave us?**

The key conclusion of this analysis is that investors should not feel shy in dialing down risk during a period of higher volatility, particularly, when the level of volatility is extreme. As painful as it may be, selling assets after they fall in price can still make sense - investors have to remind themselves that loss aversion is one of the best wealth destroyers. This analysis applies particularly well at the end of credit and economic cycles. And, while it can be difficult to gauge one's precise position in the cycle, a turn in macro indicators and bearish leverage metrics can be a powerful signal to reduce risk when paired when rising market volatility.

Good Luck!

**Disclosure:** I/we have no positions in any stocks mentioned, and no plans to initiate any positions within the next 72 hours.

I wrote this article myself, and it expresses my own opinions. I am not receiving compensation for it (other than from Seeking Alpha). I have no business relationship with any company whose stock is mentioned in this article.