Portfolio Volatility Research Articles

An Empirical Assessment of Low Volatilty Portfolio Construction Techniques in the South African Environment

Portfolios constructed to have low volatility characteristics have received increasing interest in recent years. This is due to the fact that these portfolios returning higher risk-adjusted returns than market-capitalization weighted portfolios in both international markets and the South African domestic market. The outperformance of the portfolios are particularly fascinating given that economic theory suggests that higher risk is typically expected to be compensated by higher expected return. In this study, we analyze the performance of low volatility portfolios using a variety of construction techniques in South African markets using the stocks listed on the JSE. Our results compare the performance of the different techniques and show substantial outperformance of these portfolios in the South African environment relative to their market capitalization-weighted equity benchmark counterpart (ALSI). In addition, the low volatility portfolios are also blended with typical portfolios (SWIX index) in order to establish their effectiveness as useful portfolio strategies.

From Currency Volatilities to Global Equity Correlations

We derive and empirically test a theoretical link between exchange rate volatility and global equity correlations. Starting with option-implied currency volatilities, we use variants of existing currency models, global capital flows, international parity, the Taylor rule, and some simplifying assumptions to theoretically link foreign exchange options-implied volatilities and future global equity correlations. Using data from January 1999 to June 2015, we test our hypothesis and find that exchange rate implied volatilities — coupled with one-period ex-post correlations — more accurately predict subsequent equity market correlations than other models. Our findings have implications for portfolio diversification, forecast of overall equity portfolio volatility, and portfolio optimization.

Identifying Portfolio-Based Risk Factors in Foreign Exchange Markets

This paper shows that a link between the conditional mean and conditional volatility of any factor-mimicking portfolio in the foreign exchange (FX) market must exist if the proposed portfolio-based currency factor is priced and the pricing kernel has a linear factor structure. Thereby, this paper tests whether the carry risk factor and currency momentum are priced risk factors. Surprisingly, the carry risk factor does not meet the necessary conditions consistent with being a priced risk factor, whereas currency momentum indeed meets those criteria. The findings also indicate that the relation between the conditional mean and conditional risk is moreover economically reasonable for the currency momentum portfolio.

CoAnomaly: Correlation Risk in Stock Market Anomalies

I propose a simple time-series risk measure in trading stock market anomalies, CoAnomaly, the time-varying average pairwise correlation among 34 anomalies, which helps to explain both the time-series and the cross-sectional anomaly return patterns. Since correlations among underlying assets determine the portfolio variance, CoAnomaly is an important state variable for arbitrageurs who hold diversified portfolios of anomalies to boost their performance. Empirically, I show that, first, CoAnomaly is persistent and forecasts long-run aggregate volatility of the diversified anomaly portfolio. Second, CoAnomaly positively predicts future average anomaly returns in the time series. Third, in the cross-section of these 34 anomaly portfolios, CoAnomaly carries a negative price of risk. These return patterns suggest that arbitrageurs take the time-varying correlation into account and their intertemporal hedging demand plays an important role in setting asset prices.

Low Volatility Needs Little Trading

The author shows that an efficient low-volatility strategy only needs a little amount of trading. The empirical literature on low-volatility investing reveals a concave relation between the amount of trading and the risk reduction. Portfolio simulations confirm this non-linear pattern in which each increase in turnover results in smaller marginal reductions in volatility. In general a moderate trading level of 30% is enough to reduce portfolio volatility by 25% compared with the market index. In addition, low-volatility stocks are relatively liquid and cheap to trade, primarily because they are much larger than the average stock. The law of diminishing returns also applies to other alpha factors such as value and momentum and integrating them into a multi-factor low-volatility strategy is an efficient way to increase factor exposure at low trading costs. <b>TOPIC:</b>Analysis of individual factors/risk premia

Volatility-Managed Portfolios of Mutual Funds

Performance evaluation of mutual funds using factor pricing models is usually distorted by the existence of a volatility anomaly and correlated residuals. By augmenting the Fama-French five-factor model with an active peer benchmark, we eliminate the measurement errors caused by these distortions. We find that the APB-augmented five-factor model can select mutual fund portfolios with superior out of sample alphas. However, the excess portfolio returns are volatile and subject to crash risk. A risk management strategy which uses the past volatility of the mutual fund portfolio returns to scale the investment positions can help reduce the volatility of the portfolio returns and avoid extreme losses. Previous studies on stock and currency portfolios find that such a risk management technique also increases the Sharpe ratio of the portfolios. However, we find that the net impact of the risk management on the Sharpe ratio of mutual fund portfolios depends on the investment style of the mutual funds in the fund portfolios. Similar to the stock and currency portfolios, the Sharpe ratios of the mutual fund portfolios can be increased by the risk management if the portfolios are formed in mutual funds which specialize in large cap stocks. By contrast, risk management reduces the Sharpe ratios of portfolios which include small stocks-focused funds. The reason is that the mutual funds which specialize in small stocks relies more on their abilities to take on more factor risks when the factor returns are high to generate returns. Volatility timing reduces the premium of those funds’ market timing skills. Compared to investors in mutual funds which specialize in value stocks, investors in growth stocks-focused mutual funds can better enhance their market timing skills by the risk management technique. More specifically, after volatility timing, the growth stocks-focused mutual fund investors are able to take on more factor risks when the factor returns are high and gain higher average returns.

Modelling Volatility of Characteristics-Sorted Portfolios: Evidence from Egyptian Stock Exchange

Modelling Volatility of Characteristics-Sorted Portfolios: Evidence from Egyptian Stock Exchange

Volatility Ambiguity, Portfolio Choice and Asset Pricing

Volatility Ambiguity, Portfolio Choice and Asset Pricing

Downside risk control and optimal investment turnover around financial crises

This paper investigates tactical investment strategies for investors to survive financial crises. Compared with the buy-and-hold strategy, the buy-and-sell strategy is much more effective in mitigating downside risk before, during, and after a crisis by restricting the left-tail volatility of portfolio returns through CVaR constraints. The paper also studies investors' optimal turnovers around a crisis under the buy-and-hold strategy. Considering investors' heterogeneous behaviours, we find the wealth-weighted average optimal turnover across all investors during a crisis is much higher than that before or after the crisis. This indicates investors who enter the market before a crisis may be better off by leaving their portfolios untouched during the market downturn. In addition, the downside risk control model can detect a market downturn earlier than the mean-variance model therefore it helps to 'spread out' the required asset adjustments over a longer horizon than the crisis period itself.

Downside risk control and optimal investment turnover around financial crises

This paper investigates tactical investment strategies for investors to survive financial crises. Compared with the buy-and-hold strategy, the buy-and-sell strategy is much more effective in mitigating downside risk before, during, and after a crisis by restricting the left-tail volatility of portfolio returns through CVaR constraints. The paper also studies investors’ optimal turnovers around a crisis under the buy-and-hold strategy. Considering investors’ heterogeneous behaviors, we find the wealth-weighted average optimal turnover across all investors during a crisis is much higher than that before or after the crisis. This indicates investors who enter the market before a crisis may be better off by leaving their portfolios untouched during the market downturn. In addition, the downside risk control model can detect a market downturn earlier than the mean-variance model, therefore it helps to “spread out” the required asset adjustments over a longer horizon than the crisis period itself.

Some preliminary evidence of price discovery in Islamic banks

In this paper using time-series data for a large number of Islamic bank stocks belonging to eight Islamic countries we test for evidence of price discovery. We find that in each of the eight countries there appears a bank that dominates the price discovery process. We then utilize this information on price discovery to form a portfolio of price discovery dominating bank stocks and compare its performance with portfolios of banks characterized by country and volatility. We show that buying a portfolio of price discovery dominant banks and selling most of the country-specific and volatility portfolios allow an investor to maximise profits or minimise loss. Our results are (a) robust to non-Islamic banks and to a larger sample of combined Islamic and non-Islamic banks, and (b) suggest that economic significance of price discovery is stronger for non-Islamic banks.

Empirical Regularities of Nigeria’s Foreign Private Portfolio Investment Return and Volatility

ABSTRACT This paper examined the Empirical Regularities of Nigeria’s Foreign Private Portfolio Investment Return and Volatility. The study covered the periods between 1981 and 2014. An EGARCH model was specified. The analysis involves carrying out the tests for Financial Assets and Risk assumptions. The study revealed that Foreign Private Portfolio Investment Returns show Volatility clustering. Secondly, Foreign Private Portfolio Investment Return and Risk were found to have Thick tail. Variance Ratio Test [VRT] was used to test the weak form efficiency of the efficient market hypothesis and hence the non-predictability of financial markets. The Results showed that changes in one direction are more often followed by similar changes in either direction (volatility clustering). Given that Nigeria’s Foreign Private portfolio investment empirical imperatives is regular like that of the rest of the world, the paper thus recommends that investment decision models used by advanced analyst in developed countries can be applied to developing countries like Nigeria with little modification with respect to Foreign Private Portfolio Investment as their assets and risks display similar characteristics with assets and risks in developed countries.

Tail Risk Mitigation with Managed Volatility Strategies

Managed volatility strategies adjust market exposure in inverse relation to a risk estimate, to stabilize realized portfolio volatility through time. Our paper examines strategy performance from an investment practitioner perspective. Using long-term data from the Standard & Poor’s 500, we show that these strategies offer an improvement in risk-adjusted return compared with a buy-and-hold benchmark, on average, but with some variation. Managed volatility strategies achieve robust tail-risk reduction while also enhancing skewness. These return normalization features are inherently linked to the nature of the volatility stabilization mechanism. We illustrate them via utility-based metrics that reward the tail-risk reduction emanating from volatility stabilization. These enhancements are economically meaningful for many time horizons and holding period combinations, and they remain once transaction costs have been included, suggesting a durable and tangible value-add from managed volatility strategies. They also suggest a more appropriate way to measure the performance improvements of tail-risk-mitigating strategies.

The curious case of negative volatility

In a panel survey of brokerage clients in the United Kingdom, participants mostly perceive their own portfolio as no more volatile than the market portfolio. Taking into account observed portfolio betas, this implies a belief in very low idiosyncratic portfolio volatility, which is even negative for a considerable fraction of the studied investor population. Possible explanations are extreme overconfidence in combination with a misunderstanding of how market and portfolio volatility are related. The identified bias contributes to underdiversification, as a belief in negative idiosyncratic volatility conceals the true benefits of diversification. In an experiment, we confirm the existence of a belief in negative volatility and rule out the underestimation of beta as an alternative explanation.

Mean-Variance Optimization Using Forward-Looking Return Estimates

Despite its theoretical appeal, Markowitz mean-variance portfolio optimization is plagued by practical issues. It is especially difficult to obtain reliable estimates of a stock's expected return. Recent research has therefore focused on minimum volatility portfolio optimization, which implicitly assumes that expected returns for all assets are equal. We argue that investors are better off using the implied cost of capital based on analysts' earnings forecasts as a forward-looking return estimate. Correcting for predictable analyst forecast errors, we demonstrate that mean-variance optimized portfolios based on these estimates outperform on both an absolute and a risk-adjusted basis the minimum volatility portfolio as well as naive benchmarks, such as the value-weighted and equally-weighted market portfolio. The results continue to hold when extending the sample to international markets, using different methods for estimating the forward-looking return, including transaction costs, and using different optimization constraints.

Diversification Strikes Again: Evidence from Global Equity Factors

The benefits of country diversification are well-established. This article shows that the same benefits extend to equity factors, such as value, size, momentum, investment, and profitability. Specifically, country factor portfolios reflect both common variation, which we define as the global factor, and local variation. On average, a US investor could enjoy a 30% reduction in portfolio volatility by investing globally. We also document three other properties of equity factors. Like major asset classes, diversification benefits may not been uniform across regions, and factor portfolios of different countries tend to be more correlated during bear stock markets. However, unlike asset classes, the correlations of factor portfolios across countries have not been increasing over the last two decades, making global equity factors particularly desirable additions to a portfolio.

Asset allocation using option-implied moments

This study uses an option-implied distribution as the input in asset allocation. The computation of risk-neutral densities (RND) are based on the Dow Jones Industrial Average (DJIA) index option and its constituents. Since the RNDs estimation does not incorporate risk premium, the conversion of RND into risk-world density (RWD) is required. The RWD is obtained through parametric calibration using the beta distributions. The mean, volatility, and covariance are then calculated to construct the portfolio. The performance of the portfolio is evaluated by using portfolio volatility and Sharpe ratio.

Interest Rate Exposure of Volatility Portfolios

The authors assess the exposure of stock portfolios sorted by total volatility to interest rate risk and determine whether this nonequity risk can explain differences in risk and risk-adjusted returns between low- and high-volatility portfolios over a 25-year period for U.S. equities. They find that the addition of an interest rate risk factor to the four-factor model reveals a small but positive duration for low-volatility portfolios. However, this new factor fails to improve the explanatory power of the model for both low- and high-volatility portfolios and has no significant impact on the portfolios’ risk-adjusted return. The authors find that interest rate factor loadings are fairly robust across different specifications of the multifactor model for low-volatility portfolios but are unstable for high-volatility portfolios. For all volatility portfolios under study, the significance of the results is highly dependent on the choice of time period. <b>TOPICS:</b>Analysis of individual factors/risk premia, equity portfolio management, volatility measures

Managing Risks Beyond Volatility

Minimum volatility strategies enjoy broad support in the academic literature and have been applied extensively by institutional investors to reduce portfolio volatility. In this article, the authors discuss how such strategies can adapt to address risks beyond price volatility. Specifically, concentration, sustainability, and crowding risks could be mitigated using appropriate but simple optimization constraints. However, adding a diversification constraint increased exposure to residual volatility and had a negative impact on risk reduction and risk-adjusted performance. In contrast, to help manage environmental, social, and governance (ESG) risks, adding a significant sustainability constraint had only a small effect on the risk reduction properties. Finally, introducing constraints on the value exposure ensured the market-relative valuations of the strategy remained attractive for only a small increase in realized volatility. The authors show that simple constraints could be used effectively in minimum volatility strategies to manage risks beyond volatility.

A Study on the Strategic Application of Abnormal Risk-Return Relationship

This paper focuses on the strategic application based on the empirical results of risk-return relationship against the classical concept. Empirical analysis from domestic data, we verify that the traditional concept-‘high risk, high return’ relationship are maintained, however, we confirm the falling pattern in the highest total volatility group. Even though we implies double sorting method to control the well known systematic factor such as BM and size, we still confirm such abnormal risk-return relationship. Furthermore, we perform sub-period analysis before and after the liberalization of Korean capital market and we find such abnormal risk-return relationship is appeared after the liberalization. Based on our empirical results, we establish and verify the new benchmark that evenly allocate highest volatility portfolio to sub-volatility portfolio. Under the new benchmark, we confirm the expansion of the efficient frontier and the improvement of Sharpe ratio. We believe that our results provide an applicability research of smart beta strategy and new benchmark based on such strategy. We expect our research to be used as preliminary study to overcome the era of “new normal” and to reform the investment strategies correspond to segmentation of benchmark.