How to Develop Better Low Volatility Stock Strategies

The role of low volatility strategies in investment portfolios

Low volatility equity strategies are attractive to investors for a lot of reasons. First, they assist keep our portfolios invested in stocks during times of market turbulence. Second, when well designed, they often have higher risk-adjusted returns than their higher volatility counterparts.

While general surveys of low volatility strategies show that they do indeed protect investors from market-related risks, what is commonly ignored is that these same strategies is probably not sufficiently diversified or risk controlled. To this end, we’ll examine the critical components of an efficient, low-volatility portfolio construction process. These elements enable the development of low-volatility portfolios with greater diversification and significantly higher risk-adjusted returns than the usual low-volatility strategy.

Low Volatility Strategies: Three Possible Drawbacks

Low volatility stocks can offer a premium over the long term. And while they’ll provide each volatility reduction and capital protection in bear markets in comparison with cap-weighted indices, not all low volatility strategies achieve this to the identical extent. In fact, many commercially available low volatility strategies share common disadvantages.

1. Lack of diversification

Inverse volatility and minimum variance optimization are two common methods in low volatility strategies. In inverse volatility portfolios, a stock’s portfolio weight is proportional to its risk. Such portfolios penalize high-volatility stocks and reward their low-volatility counterparts. They may also be highly concentrated. The same criticism applies to the strategy of minimum variance optimization, which, without various restrictions, may result in an excessive overweighting of the portfolio in a number of stocks.

2. Negative exposure to other rewarded aspects

In particular, value, momentum, high profitability and low investments are among the many aspects which have rewarded investors over time. However, low volatility strategies may underweight these aspects and impact long-term risk-adjusted performance.

3. Excessive risk from sector and regional exposures

Low volatility portfolios can have sustained sector or regional exposures, which may open them as much as eliminating macroeconomic risks.

A greater solution to construct low volatility portfolios

There are several remedies for these diversification and risk-related challenges in low volatility portfolios. To address the chubby problem, we are able to construct more diversified, low volatility portfolios by choosing weights based on multiple optimization frameworks and introducing robust weight constraints. Due to its special architecture, each model carries risks when estimating parameters. By averaging across multiple models, we are able to reduce much of the model risk related to using a single framework. Furthermore, a given model can operate with no significant amount of intermittent ad hoc restrictions, comparable to: B. Min-Max weights for stocks or sectors, can result in overly concentrated or otherwise insufficiently diversified portfolios. To address this problem, We use so-called standard weight restrictions, which avoid concentrations higher than ad hoc, sample-dependent restrictions. (We also use principal component evaluation—PCA, a statistical technique—to denoise the covariance matrices we use to create our portfolios.)

Another solution to diversify in a low volatility strategy is to extend the factor intensity of a portfolio. When applied to a person stock, this measure is just the sum of the person factor exposures, or betas, in a portfolio. So after we select stocks for a low volatility portfolio, we prefer those with high exposure to the low volatility factor, but we also wish to filter out stocks with significant negative exposure to other reward aspects. By implementing such filtering, our low volatility stocks can be positively biased towards value, momentum and other rewarded aspects to the best extent possible. As a result, in environments where the Low Volatility Factor underperforms, the opposite aspects may have the option to “pick up the slack” and protect the portfolio from among the damage which may occur to the portfolio without such filtering.

Each rewarded stock factor is exposed to macroeconomic aspects. Which factor bears the best macroeconomic risk depends, after all, on the macroeconomic environment or regime. Country or region-specific drivers explain much of a portfolio’s macro risk. Therefore, we are able to mitigate this risk by constructing portfolios which are geographically neutral in comparison with a capitalization-weighted benchmark. Because macroeconomic risks are sometimes sector-dependent, choosing low-volatility stocks inside sectors can mitigate macroeconomic risk. Sectors are necessary considerations as low volatility strategies can chubby certain sectors, comparable to: B. Utilities which are sensitive to rates of interest and other types of risk.

In terms of empirical results, the figure below shows that a low-volatility portfolio with factor intensity filters delivers significant risk-adjusted returns in comparison with capitalization-weighted and standard low-volatility indices. This applies to low volatility strategies in each the US and developed markets.

Performance and risk metrics of the low volatility equity strategy

US statistics

Developed market statistics

The process described above leads to significantly higher factor intensities for each US and developed market portfolios, because the charts below show.

Factor intensity in low volatility equity strategies

US factor intensities

Factor intensities in developed markets

This approach also reduces macro risk across all regions, because the tables below show.

Macro exposures in low volatility strategies

US commitments

Commitments in developed markets

Diploma

Low volatility stock portfolios could be a priceless addition to investor portfolios. They allow asset owners to stay invested in stocks even during market turbulence. However, not all low volatility strategies are created equal. Many lack the diversification and risk controls needed to guard against concentration and macro risks.

To this end, the investment process described here uses various measures to make sure the vital risk control. Of the 2 techniques highlighted, the primary reduces concentration risk through model averaging and the second applies a filter to weed out stocks with low factor intensity.

By using these two methods, we are able to increase diversification and reduce the risks within the portfolio from different market and macro environments compared to straightforward low volatility benchmarks, making an allowance for regional and sectoral risks.

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