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Volatility has made headlines in the last few months. Investors often think about volatility as something bad – a foe that needs to be controlled, managed or avoided. However, when viewed correctly, volatility can actually serve as an important resource to help strengthen portfolio resilience by signaling when to reduce risk and when to embrace it.

Volatility is an important component of risk measurement for investors, but the bigger risk threat to long-term performance is typically downside exposure. Not only do negative returns represent a loss in value, but they also require a portfolio to earn even higher returns just to get investors back to a breakeven point. Hence, mitigating or, even better, avoiding drawdowns as much as possible is a key tenet of investment success, since investors don’t want to be set back by losses that need to be recouped before capturing any net gains.

While volatility (i.e., standard deviation) and drawdowns (i.e., absolute loss) represent distinct risk metrics, they historically have also exhibited a clear link. Figure 1 shows rolling 130-day (approximately six months) annualized standard deviations for the MSCI World Index between 1992 and 2017, as well as corresponding drawdowns measured by percentage loss.

Periods of higher volatility have been more apt to experience a drawdown. Volatility spikes have been associated with recoveries as well but have been more frequently connected to declines. This suggests that volatility may serve as an effective signal if a market is potentially entering a period of heightened risk of loss.

 

Figure 1 - Relationship Between Realized Volatility and Drawdowns 

An Experiment

Based on this strong historical relationship between volatility and drawdowns, we test whether volatility on its own offers an effective adapting signal. The premise is simple: as market volatility increases, one should decrease portfolio risk, and vice versa. Doing this consistently across full market cycles should lead to stronger portfolio outcomes.

To test this assumption we back test a simple, rules-based portfolio model using the MSCI World Index:

  • When volatility is ≤ 13.5%, hold the index
  • When volatility is > 13.5%, sell the index and switch to U.S. Treasury bills
  • When volatility moves back to < 13%, switch back to the index

Beginning to translate volatility characteristics into this type of portfolio application requires answering three key questions. First, how do you measure market volatility? For this experiment, volatility refers to the index’s rolling 130-day (approximately six months) standard deviation.

Second, how do you increase or decrease portfolio risk exposure? For simplicity we choose a binary allocation between a broad global equity benchmark and U.S. Treasury bills – full risk exposure or none. The 13.5% to 13% spread is chosen to envelop the 130-day average volatility of the index. It is also a signal that relates to the long-term average in which we see substantial drawdowns likely to occur. The 0.5% buffer reduces trigger events, seeking instead longer-term risk regime changes. 

Finally, how quickly do you adapt to changes? This simple, hypothetical strategy assumes daily, but in a real-world portfolio application this answer could easily be different depending on an individual investor’s pain threshold, available risk management tools, adaptation costs and recovery time.

The results of this experiment are shown in Figure 2. Even this very simple volatility-driven strategy shows significant improvement in returns versus the benchmark over full market cycles by effectively missing most of the downside and participating in some of the upside. Across the entire 25-year period the simple strategy captures higher cumulative return with less volatility. This represents a Sharpe ratio more than double that of the index.

 

Figure 2 - Testing a Simple Volatility-Driven Model 

No Return Forecasts

This naïve, hypothetical strategy’s improved performance is achieved based entirely on observed volatility levels. Rebalancing is prompted strictly by what is actually occurring in the market at any given time, not by trying to forecast volatility increases. Timing the market is notoriously difficult, and this model suggests a repeatable way to lower portfolio risk and strengthen long-term returns that completely avoids the need to try to predict what might happen in the future. While such a simplistic approach may not be realistic in practice, similar optimized approaches to volatility-based equity portfolio management can be used to mitigate equity downside risk without giving up on the upside.

Is Volatility a Friend or a Foe?  Learn more about how volatility can help strengthen portfolio resilience. Download Now

 

This information is intended to be educational and is not tailored to the investment needs of any specific investor, nor is it an endorsement or recommendation for any particular security or trading strategy. You should not rely on this information as the primary basis for your investment, financial, or tax planning decisions. Past performance cannot guarantee future results. Investing involves risk, including the possible loss of principal and fluctuation of value.