The Experiment¹

To illustrate the benefit of an adaptive volatility strategy through various risk environments, we analyze its risk profile relative to short-term and long-term measures of volatility and how the strategy reacts to different magnitudes of market drawdowns across indexes.

The results are clear: adaptive volatility strategies outperform their benchmarks over the long term by providing significant downside protection when short and long term market volatility is high, and drawdowns in the markets are significant. When market risk is low and drawdowns are mild and short-lived, the strategies’ risk profiles are not very different from that of the index, allowing them to keep up with equity markets.

Short-Term Volatility

When we test the strategy measuring short-term -- or a quarterly period -- of volatility against the index, be it the S&P 500 or the MSCI ACWI, the adaptive volatility strategies demonstrate less volatility, particularly when index volatility increases.

Take the example seen in Figure 1: when the S&P 500 index shows short-term market volatility of around 70%, the U.S. Adaptive Volatility strategy shows around 50% volatility, that’s remarkably less than the index. We observe similar volatility reduction when testing the MSCI ACWI benchmark against the Global All Country Adaptive Volatility strategy in a short-term period.

In a risk-on environment, when market volatility is low, the strategy’s risk is similar to that of the index. This allows the adaptive volatility strategy to keep up with the market even during times of strong economic growth.

Long-Term Volatility

When looking at 36-month measurements of risk, we can see from the simulations that as index volatility increases, the strategy adapts, showing less volatility (see Figure 2). To illustrate this point, we see that when the MSCI All Country World Index shows long-term volatility of around 25%, the Global All Country Adaptive Volatility strategy shows around 14% volatility during the same market conditions.

Like the short-term volatility scenario, when the benchmark exhibits lower volatility, the adaptive volatility strategy’s risk is similar to that of the index. This allows the strategy to keep up with the market.

In these two cases, short- and long-term volatility for both U.S. and Global All Country Adaptive Volatility, the approach adapts to varying volatility levels – doing what it’s supposed to do.

Drawdown Risk

By measuring monthly rolling drawdown against the indexes we see that adaptive volatility strategies’ participation in market drawdowns decreases with larger market declines, from peak to trough.

Figures 3 shows that as the market drawdown becomes larger, the strategy’s drawdown becomes smaller relative to the index, outperforming the market. During the global financial crisis, the S&P 500 Index showed volatility levels of more than 50% while the U.S. Adaptive Volatility strategy only reached 35%. Drawdown isn’t a measure of volatility per se – it’s a measure of negative return.

Conclusion

In current market conditions, when the U.S. economy maintains a solid pace of growth but with some concerns of a slowdown in 2019, softening inflation and uncertainty related to trade, monetary policy, and fiscal policy, having an equity strategy that adjusts to the volatility created by these different market forces has attractive benefits.

Adaptive volatility strategies are designed to not overreact to sudden increases or drops in volatility, but to adjust its levels of risk reduction to regimes of high or low market volatility. Therefore, to achieve success, an adaptive volatility strategy should identify a change in the market volatility structure as early and reliably as possible, and trade the portfolios to these new target weights as inexpensively as possible.

Intech’s adaptive volatility strategies represent a natural extension -- and application -- of reducing portfolio volatility and generating a better risk-reward tradeoff than a capitalization-weighted equity index. The increased downside protection and volatility efficiency can provide numerous benefits to investors over time given uncertainty associated with equity markets. These strategies are adaptive as they tap into a proven alpha source through systematic rebalancing and dynamic risk reduction by adapting to varying volatility conditions. 

¹Based on simulations for the Intech U.S. Adaptive Volatility strategies for the period from January 1, 1968 to March 31, 2018 and Global All Country Adaptive Volatility strategies for the period from January 1, 1995 to March 31, 2018. 

Disclaimer
The information expressed herein is subject to change based on market and other conditions. The views presented are for general informational purposes only and are not intended as investment advice, as an offer or solicitation of an offer to sell or buy, or as an endorsement, recommendation, or sponsorship of any company, security, advisory service, or fund nor do they purport to address the financial objectives or specific investment needs of any individual reader, investor, or organization. This information should not be used as the sole basis for investment decisions. All content is presented by the date(s) published or indicated only, and may be superseded by subsequent market events or other reasons. Past performance is no guarantee of future results. Investing involves risk, including possible loss of principal and fluctuation of value.

Important Information Regarding Simulations
The simulations shown have been compiled solely by Intech and have not been independently verified. Simulations can be used to evaluate an investment process by seeing how an investment product would have performed hypothetically during certain time periods. This material is provided for illustrative and educational purposes only and should not be construed as an offer to sell, or the solicitation of offers to buy, or a recommendation for any security, strategy, investment product or advisory service. Although the information contained herein has been obtained from sources believed to be reliable, its accuracy and completeness cannot be guaranteed.

Simulated results are hypothetical, not real. They do not reflect the results or risks associated with actual trading or the actual performance of any account. Simulated results are prepared with the benefit of hindsight and we continually attempt to enhance our process. As a result, the simulated results are derived using the most current version of the investment process as of the date shown, and not the process in place during prior periods, typically resulting in more favorable results. As a result, the simulations may be theoretically changed from time to time to obtain results that are more favorable. Simulation results do not reflect material, economic, and market factors that may have impacted trading or decision-making in the actual management of an account. A mathematical optimization process was applied to historical data to produce the simulations.

Intech’s simulated performance results have inherent limitations, including, among other things: 1) no price-based or volume-based deleted list; 2) no posted list; 3) index constituent changes done as a group at the beginning of the month (typically done once or twice a year based on the index changes); 4) simulated trades take place at the closing price (+40 bps for developed countries), while Intech actually trades intra-day (historically, Intech's domestic trading costs have been below the 40 bps used in the simulations); and 5) six trading tranches are simulated with the average of the six tranches being reported as the result for the period.

Past performance of simulated data is no guarantee of future results. Therefore, there are no assurances that future performance will be profitable, or equal to either the simulated performance results shown or any corresponding historical index. In particular, simulations do not reflect actual trading in an account, so there is no guarantee that an actual account would have achieved the results shown. In fact, there may be differences between simulated performance results and the actual results subsequently achieved.

In no circumstances should simulated returns be regarded as a representation, warranty, or prediction that investors will achieve or are likely to achieve the results displayed, or that losses can be avoided. Investing involves risk, including fluctuation in value, the possible loss of principal and total loss of investment. There are numerous other factors related to the markets in general or to the implementation of any specific trading strategy, which cannot be fully accounted for in the preparation of simulated results, all of which can adversely affect actual trading results.

The simulations include the reinvestment of all dividends, interest, and capital gains, but do not reflect deduction of investment advisory fees. Simulated returns will be reduced by advisory fees and any other expenses such as custodial fees, odd-lot differentials, transfer taxes, foreign exchange transaction fees, wire transfer and electronic fund fees, as well as other fees, taxes, and governmental charges, that may be incurred in the management of an account, which will materially lower returns over time.

An index is unmanaged, is not available for direct investment, and does not reflect the deduction of management fees or other expenses. There is a risk/reward tradeoff that comes with investing in adaptive volatility strategies. These risk strategies are likely to underperform the index during periods of strong up markets and may not achieve the desired level of protection in down markets.

Data Source: The Center for Research in Security Prices ("CRSP") Deciles are market value weighted benchmarks of common stock performance provided by the CRSP at the University of Chicago Booth School of Business. The CRSP universe includes common stocks listed on the NYSE, AMEX, and the NASDAQ National Market excluding the following: preferred stocks, unit investment trusts, closed-end funds, real estate investment trusts, Americus Trusts, foreign stocks and American Depositary Receipts.

MSCI makes no express or implied warranties or representations and shall have no liability whatsoever with respect to any MSCI data contained herein, if shown. The MSCI data may not be further redistributed or used as a basis for other indices or any securities or financial products. This report has not been approved, reviewed, or produced by MSCI.