Volatility Timing Research Articles

Volatility timing, sentiment, and the short-term profitability of VIX-based cross-sectional trading strategies

This paper explores the profitability of simple short-term cross-sectional trading strategies based on the implied volatility index (VIX), often referred to as an “investor fear gauge” in the stock market. These strategies involve holding sentiment-prone stocks when VIX is low and sentiment-immune stocks when VIX is high and generate significantly higher excess returns than the benchmark long–short portfolios that do not condition on VIX. We show that the profitability of our trading strategies is not subsumed by the well-known risk factors or transaction cost adjustments. Our findings are consistent with the theory of delayed arbitrage and the synchronization problem of Abreu and Brunnermeier (2002).

Quantitative Evaluation Methods of Cluster Wind Power Output Volatility and Source-Load Timing Matching in Regional Power Grid

The quantitative evaluation of cluster wind power output volatility and source-load timing matching is vital to the planning and operation of the future power system dominated by new energy. However, the existing volatility evaluation methods of cluster wind power output do not fully consider timing volatility, or are not suitable for small sample data scenarios. Meanwhile, the existing source-load timing matching evaluation indicator ignores the impact of wind power permeability on the timing matching degree between wind power output and load. Therefore, the authors propose quantitative evaluation methods of cluster wind power output volatility and source-load timing matching in regional power grid. Firstly, the volatility-based smoothing coefficient is defined to quantitatively evaluate the smoothing effect of wind-farm cluster power output. Then, the source-load timing matching coefficient considering wind power permeability is proposed to quantitatively evaluate the timing matching degree of regional wind power output and load, and the corresponding function model of volatility-based smoothing coefficient and source-load timing matching coefficient is established. Finally, the validity and applicability of the proposed methods are verified by MATLAB software based on the actual power output of 10 wind farms and actual grid load in a certain grid dispatching cross-section of northeast China. The results demonstrated that the proposed volatility-based smoothing coefficient can accurately represent the smoothing effect of wind farm cluster power output while maintaining the volatility continuity of wind power output time series and without affect from the data sample size. The source-load timing matching coefficient can accurately characterize the difference in the timing matching degree between wind power output and grid load under different wind power permeability and the influence degree on grid load.

Is there a green fund premium? Evidence from twenty seven emerging markets

The popularity of green energy-based investments has spurred, notably during the last decade. This is mainly due to the positive socio-economic externalities and an increase in the financing flow. This paper assesses the financial performance and managerial abilities of green funds and their conventional peers. Using a comprehensive data set of 2339 funds across twenty-seven emerging markets, we report that traditional energy funds outperform renewable funds. Further, while conventional fund managers exhibit market and volatility timing, we cannot deduce any support for the same in the case of renewables. These results indicate disincentives for investors who would like to go green. Finally, the performance of renewable funds degraded during Covid-19, highlighting the additional investment drag. We propose that immediate legislative, governance, and regulatory interventions are warranted to promote a sustainable financial system.

The impact of carbon neutrality on the investment performance: Evidence from the equity mutual funds in BRICS

The promotion of carbon-neutral investments is among the primary constituents of developing a carbon-neutral economy. This is even more important for emerging economies that have constrained financial markets. In this paper, using monthly data between 2011 and 2019, we study 6519 actively managed mutual funds in BRICS after sorting them into black, brown, and green categories based on their investment holdings. Our comparative performance shows that green funds outperform their counterparts for the entire sample and within-country assessment. We also document the volatility and market timing ability of green funds, mainly absent in high emission funds. The results remained robust for various definitions of performance. Our findings also indicate Chinese green funds perform better than those of other countries. This is attributed to the multiple ecologically friendly economic policies that China has adopted over the years. Based on the results, we propose various interventions that could foster the adaptability of a carbon-neutral investment landscape.

Human capital efficiency, performance, market, and volatility timing of asian equity funds during COVID-19 outbreak

Despite its relevance for financial services, the impact of human capital efficiency on mutual fund performance has remained unexplored. In this paper, we attempt to explore this gap in the context of the outbreak of COVID-19 that provides us a unique opportunity to assess human capital's importance during economic pressures. We employ data on 2044 equity funds across sixteen COVID-19 affected Asian countries to analyze the performance, market, and volatility timing after sorting these funds as per their human capital efficiency. Our results show that funds with better human capital efficiency outperform their counterparts that rank lower on human capital efficiency. The outperformance as measured by adjusted Sharpe and Sortino’s ratios, Jensen’s alpha, stochastic dominance, market, and volatility timing remained consistent for the pre-COVID period as well as through the outbreak during which the impact of human capital efficiency became even more significant. These findings have important strategic implications for mutual funds.

Discovering the Drivers of Market Volatility: Asset Allocation Applications

This study investigates the economic and financial drivers of volatility changes and integrates them into stock market volatility forecasting. We first collect a diverse set of predictor variables and analyze them within a unified framework. We discover that only a small number of variables contain significant predictive information, and that the Chinese stock market return significantly predicts U.S. stock market volatility. Using the HAR-LASSO procedure, we integrate the drivers’ predictive information and forecast short-term, medium-term, and long-term market volatilities. Through various volatility timing strategies, we verify that HAR-LASSO-based portfolios lead to outstanding investment performance, regardless of the strategies and forecasting horizons. These results not only economically justify our procedure, but also provide meaningful financial implications of accurate volatility forecasting.

Do fund managers time implied tail risk? — Evidence from Chinese mutual funds

This study shows that fund managers can time the market-wide implied tail risk using mutual fund data from China. Managers tend to decrease the market exposure when the market-implied tail risk increases. Furthermore, the implied tail risk timing ability brings significant economic value to investors. The top timer outperforms the bottom timer by approximately 2.77%–3.53% annually on excess returns with 30-day holding periods. Also, our findings are reliable when controlling market timing, volatility timing, and implied tail risk factor. Moreover, we discover that funds exhibiting implied tail risk timing ability tend to have long histories and higher flows. However, managers' financial derivatives background would not help in better timing the implied tail risk.

Can Market Regimes Really be Timed with Historical Volatility?

Recent research findings suggest long-term investor utility benefits through scaling expected returns by recent realized volatility. We test for utility gains to volatility timing using a utility regime-based methodology to classify investor-specific market investment regimes based solely on recent realized volatility levels. Under this framework we find limited informational content in using recent realized volatility to forecast utility regimes for the market index. To reconcile our findings we replicate work by Moreira and Muir (2017) and find that their reported Sharpe ratio gains through volatility-managing the US market factor do not appear to be statistically significant. We find that their scheme under-performs buy and hold in terms of Sharpe ratio over 30 of the 70 twenty year sub-periods in our sample (58 out of 70 for an un-leveraged investor). Furthermore, the historical out-performance of volatility management for the market index is highly sensitive to the timing of re-balancing within a month, suggesting that the strategy may not be robust to the precise timing of key market events relative to volatility changes. Strategy adopters should be aware that this timing is not guaranteed to line up favorably over future investment periods.

It’s all in the timing again: simple active portfolio strategies that outperform naïve diversification in the cryptocurrency market

ABSTRACT This article analyzes whether cryptocurrencies’ inclusion improves stock portfolios’ performance and whether the application of portfolio selection methodologies would bring gains to investors in the digital currency market. Volatility Timing and Reward-to-Risk Timing methodologies were applied to a base containing only S&P 100 stocks, another containing only cryptocurrencies, and one mixing the previous two. The results suggest that the inclusion of cryptocurrencies has not brought performance gains to the stock portfolios and that the investor in the cryptocurrency market can benefit from the use of portfolio selection.

The Resilience of Islamic Equity Funds during COVID-19: Evidence from Risk Adjusted Performance, Investment Styles and Volatility Timing

This paper analyses the risk-adjusted performance of Islamic and conventional equity funds during three stages of the COVID-19 pandemic. We show that Islamic equity funds demonstrated differentials in risk-adjusted performance, investment styles, and volatility timing compared to their conventional counterparts. Specifically, the results revealed that Islamic equity funds are more resilient to COVID-19 shock, since they outperformed non-Islamic counterparts during the peak months of the pandemic. These findings confirm the safe haven properties of Islamic equity funds, which is useful for investors aiming to hedge pandemic risks. The style analysis reveals investment drift from riskier styles to more prudent options in response to the uncertainties underlying each stage. The results suggest policy makers should further investigate Islamic financial assets and their underlying principles to improve the resilience of financial systems in any future black swan events.

Who Wants to Be a Volatility Timer?

The exact conditions under which volatility timing strategies yield value are documented. These conditions include: the ability to correctly forecast next period stochastic variance, and violation of Merton's ICAPM. Using reasonable parameter values plugged into the derived formulae, the results show that extreme leverage is often required for success. A method of tempering leverage is proposed, which is somewhat able to loosen the requirement of high leverage while still maintaining a good performance level.

Do Mutual Fund Managers Time Market Sentiment?

This paper examines whether fund managers can adjust the exposure of portfolio to time market sentiment, thus expanding the new dimension of the study of mutual fund managers’ timing ability. Using the data of Chinese open-end equity funds from January 2010 to December 2019, based on the CICSI sentiment index developed by Yi and Mao (2009), we find strong evidence that Chinese mutual fund managers have sentiment ability during the sample period. In addition, the funds with positive sentiment timing ability outperforms those without such by 2.20% per year, and the longer the fund survives, the more likely for it to have sentiment timing ability. Our findings remain robust even after controlling the impact of bull and bear market on China’s A-share market in 2015, market timing, volatility timing and liquidity timing, and after using three new sentiment indicators to verify the finding, three indicators being the net buying amount of northward capital, the net buying amount of financing, and the net ratio of limit up.

An Analysis of Mutual Fund Managers’ Timing Abilities - Evidence From Chinese Equity Funds

This paper examines Chinese mutual fund managers’ market, volatility, and liquidity abilities. Using a daily frequency sample of Chinese open-end equity funds from 2015 to 2019, we find evidence that mutual fund managers can time the market. Among the funds with different investment styles, the active funds have better market and liquidity timing ability, whereas the steady funds have better volatility timing ability. In different investment periods, there are more funds with timing ability in the fall period than in the rise period. We find the same results in the market (T-M), volatility, and liquidity timing models. It is especially for the active funds, nearly half of which have liquidity timing ability in the fall period. Among the funds with stock selection ability, the funds with market timing ability can outperform than the funds with other timing ability.

Price reaction, volatility timing and funds’ performance during Covid-19

In this paper we assess the price reaction, performance and volatility timing of European investment funds during the outbreak of Covid-19. We analyze the time period between January and June 2020 and demonstrate that while most of the investment funds exhibit stressed performance, social entrepreneurship funds endured resilience. This performance remained robust during the various stages of evolution of this contagion. The social funds also demonstrated volatility timing that was absent for most of their counterparts. We attribute the overall stability of these funds to their niche investments in social enterprises that specialize in providing innovative solutions for social issues.

Mutual fund managers’ market timing abilities: Indian evidence

In this paper, apart from traditional return timing, we examine the timing abilities of Indian mutual fund managers from two new perspectives, i.e., liquidity timing and volatility timing. Using a sample of 183 equity-oriented funds from April 2000 to March 2018, we find evidence of liquidity timing ability among fund managers at both portfolio and individual level. Our result is robust to different liquidity measure, sub-period test, excluding the crisis period and at the individual fund level analysis. No strong evidence is observed regarding market return timing and volatility timing of fund managers.

Volatility forecasts embedded in the prices of crude‐oil options

AbstractThis paper evaluates the ability of alternative option‐implied volatility measures to forecast crude‐oil return volatility. We find that a corridor implied volatility measure that aggregates information from a narrow range of option contracts consistently outperforms forecasts obtained by the popular Black–Scholes and model‐free volatility expectations, as well as those generated by a realized volatility model. This measure ranks favorably in regression‐based tests, delivers the lowest forecast errors under different loss functions, and generates economically significant gains in volatility timing exercises. Our results also show that the Chicago Board Options Exchange's “oil‐VIX” index performs poorly, as it routinely produces the least accurate forecasts.

Macroeconomic fundamentals, jump dynamics and expected volatility

In this paper, we develop a new volatility model capturing the effects of macroeconomic variables and jump dynamics on the stock volatility. The proposed GARCH-Jump-MIDAS model is applied to the S&P 500 index. Our in-sample results indicate that macroeconomic activities have important impacts on aggregate market volatility. Out-of-sample evidence suggests that our model with macroeconomic variables significantly outperform a wide range of competitors including the original GARCH(1,1), GARCH-MIDAS and GJR-A-MIDAS models. The volatility timing results also show that the information from jumps and macroeconomic activity is helpful for improving the portfolio performance.

Heterogeneous beliefs and return volatility around seasoned equity offerings

We investigate the dynamics of heterogeneous beliefs and link them to the volatility pattern throughout the seasoned equity offering (SEO) event window. In sync with a reduction in information asymmetry related to management information releases around the SEO event, belief heterogeneity declines. Moreover, heterogeneity in beliefs, proxied by either analyst- or institutional-trade-based measures, is a robust and salient determinant of SEO firm volatility, which provides an explanation for the volatility timing “puzzle” identified in the SEO market. Furthermore, the relation between heterogeneous beliefs and return volatility weakens as short sale constraints tighten, suggesting a potential causal link.

Volatility Forecasts Embedded in the Prices of Crude-Oil Options

This paper evaluates and compares the ability of alternative option-implied volatility measures to forecast the monthly realized volatility of crude-oil returns. We find that a corridor implied volatility measure that aggregates information from a narrow range of option contracts consistently outperforms forecasts obtained by the popular Black-Scholes and model-free volatility expectations, as well as those generated by a high-frequency realized volatility model. In particular, this measure ranks favorably in all regression-based tests, delivers the lowest forecast errors under either symmetric or asymmetric loss functions, and generates economically significant gains in volatility timing exercises. Our results also show that the CBOE's oil-VIX (OVX) index performs poorly, as it routinely produces the least accurate forecasts.

Momentum Turning Points

Turning points are the Achilles' heel of time-series momentum portfolios. Slow signals fail to react quickly to changes in trend while fast signals are often false alarms. We examine theoretically and empirically how momentum portfolios of various intermediate speeds, formed by blending slow and fast strategies, cope with turning points. Our model predicts a mean-variance optimal dynamic speed selection strategy. We apply this strategy across domestic and international equity markets and document efficient out-of-sample performance. We also propose a novel decomposition of momentum strategy alpha, highlighting the role of volatility timing.