Downside Risk in Emerging Markets

This paper investigates the relation between downside risk and expected returns on the aggregate stock market in an international context. Nonparametric and parametric value at risk are used as measures of downside risk to determine the existence of a risk-return trade-off. For emerging markets, fixed effects panel data regressions provide evidence for a significantly positive relationship between monthly expected market returns and downside risk. This result is robust after controlling for aggregate dividend yield and price-to-fundamental ratios. The relationship between expected returns and downside risk is weaker for developed markets and vanishes when control variables are included in the specification.     

Volatility as an Asset Class: European Evidence

Abstract

Volatility movements are known to be negatively correlated with stock index returns. Hence, investing in volatility appears to be attractive for investors seeking risk diversification. The most common instruments for investing in pure volatility are variance swaps, which now enjoy an active over-the-counter (OTC) market. This paper investigates the risk-return tradeoff of variance swaps on the Deutscher Aktienindex and Euro STOXX 50 index over the time period from 1995 to 2004. We synthetically derive variance swap rates from the smile in option prices. Using quotes from two large investment banks over two months, we validate that the synthetic values are close to OTC market prices. We find that variance swap returns exhibit an option-like profile compared to returns of the underlying index. Given this pattern, it is crucial to account for the non-normality of returns in measuring the performance of variance swap investments. As in the US, the average returns of selling variance swaps are found to be strongly positive and too large to be compatible with standard equilibrium models. The magnitude of the estimated risk premium is related to variance uncertainty and past index returns. This indicates that the variance swap rate does not seem to incorporate all past information relevant for forecasting future realized variance.     

Are idiosyncratic volatility and MAX priced in the Canadian market?

The negative relationship between realized idiosyncratic volatility (RIvol) and future returns uncovered by Ang et al. (2006) for the U.S. market has been attributed to return reversals. For the Canadian market where return reversals are considerably less important, we find that RIvol is positively related to future returns, even after controlling for risk loadings, illiquidity and reversals. Unlike the findings of Bali et al. (2001) for the U.S. market, we find that the relationship between extreme positive returns (MAX) and future returns for the Canadian market is positive and that idiosyncratic volatility continues to be consistently positively related to future returns after controlling for MAX. We find evidence that suggests that reversals for stocks with extreme daily returns are confined to (typically small) stocks with low institutional holdings.     

Have European Stocks become More Volatile? An Empirical Investigation of Idiosyncratic and Market Risk in the Euro Area

We examine the dynamics of idiosyncratic risk, market risk and return correlations in European equity markets using weekly observations from 3515 stocks listed in the 12 euro area stock markets over the period 1974–2004. Similarly to Campbell et al. (2001) , we find a rise in idiosyncratic volatility, implying that it now takes more stocks to diversify away idiosyncratic risk. Contrary to the US, however, market risk is trended upwards in Europe and correlations are not trended downwards. Both the volatility and correlation measures are pro‐cyclical, and they rise during times of low market returns. Market and average idiosyncratic volatility jointly predict market wide returns, and the latter impact upon both market and idiosyncratic volatility. This has asset pricing and risk management implications.     

Conditional risk–return relationship in a time-varying beta model

We investigate the asymmetric risk–return relationship in a time-varying beta CAPM. A state space model is established and estimated by the Adaptive Least Squares with Kalman foundations proposed by McCulloch. Using S&P 500 daily data from 1987:11–2003:12, we find a positive risk–return relationship in the up market (positive market excess returns) and a negative relationship in the down market (negative market excess returns). This supports the argument of Pettengill et al., who use a constant beta model. However, our model outperforms theirs by eliminating the unexplained returns and improving the accuracy of the estimated risk price.     

Delayed Expected Loss Recognition and the Risk Profile of Banks

This paper investigates the extent to which delayed expected loan loss recognition (DELR) is associated with greater vulnerability of banks to three distinct dimensions of risk: (1) stock market liquidity risk, (2) downside tail risk of individual banks, and (3) codependence of downside tail risk among banks. We hypothesize that DELR increases vulnerability to downside risk by creating expected loss overhangs that threaten future capital adequacy and by degrading bank transparency, which increases financing frictions and opportunities for risk‐shifting. We find that DELR is associated with higher correlations between bank‐level illiquidity and both aggregate banking sector illiquidity and market returns (i.e., higher liquidity risks) during recessions, suggesting that high DELR banks as a group may simultaneously face elevated financing frictions and enhanced opportunities for risk‐shifting behavior in crisis periods. With respect to downside risk, we find that during recessions DELR is associated with significantly higher risk of individual banks suffering severe drops in their equity values, where this association is magnified for banks with low capital levels. Consistent with increased systemic risk, we find that DELR is associated with significantly higher codependence between downside risk of individual banks and downside risk of the banking sector. We theorize that downside risk vulnerability at the individual bank level can translate into systemic risk by virtue of DELR creating a common source of risk vulnerability across high DELR banks simultaneously, which leads to risk codependence among banks and systemic effects from banks acting as part of a herd.     

Asymmetric Volatility,Skewness, and Downside Risk in Different Asset Classes: Evidence from Futures Markets

This study examines the cross‐sectional variation of futures returns from different asset classes. The monthly returns are positively correlated with downside risk and negatively correlated with coskewness. The asymmetric volatility effect generates negatively skewed returns. Assets with high coskewness and low downside betas provide hedges against market downside risk and offer low returns. The high returns offered by assets with low coskewness and high downside betas are a risk premium for bearing downside risk. The asset pricing model that incorporates downside risk partially explains the futures returns. The results indicate a unified risk perspective to jointly price different asset classes.     

Dynamic factor long memory volatility

In this paper, we develop a long memory orthogonal factor (LMOF) multivariate volatility model for forecasting the covariance matrix of financial asset returns. We evaluate the LMOF model using the volatility timing framework of Fleming et al. [J. Finance, 2001, 56, 329–352] and compare its performance with that of both a static investment strategy based on the unconditional covariance matrix and a range of dynamic investment strategies based on existing short memory and long memory multivariate conditional volatility models. We show that investors should be willing to pay to switch from the static strategy to a dynamic volatility timing strategy and that, among the dynamic strategies, the LMOF model consistently produces forecasts of the covariance matrix that are economically more useful than those produced by the other multivariate conditional volatility models, both short memory and long memory. Moreover, we show that combining long memory volatility with the factor structure yields better results than employing either long memory volatility or the factor structure alone. The factor structure also significantly reduces transaction costs, thus increasing the feasibility of dynamic volatility timing strategies in practice. Our results are robust to estimation error in expected returns, the choice of risk aversion coefficient, the estimation window length and sub-period analysis.     

Extreme downside risk spillover from the United States and Japan to Asia-Pacific stock markets

This paper proposes a binary response model approach to measure and forecast extreme downside risks in Asia-Pacific markets given information on extreme downside risks in the U.S. and Japanese markets. The extreme downside risk of a market is measured as the occurrence of extreme downside movement—market returns falling below left-tail Value at Risk in a Markov switching framework. The empirical findings are consistent with the following notions. First, extreme downside movements of the S&P 500 and Nikkei 225 are significantly predictive for the likelihood of extreme downside movements in all the investigated Asia-Pacific markets. Second, the majority of Asia-Pacific markets become more sensitive to Japan's extreme downside risk when the Japanese market switches into high volatility periods, whereas the U.S. spillover effect is intensified only on Taiwan during high volatility periods in the U.S. Third, mainland China is the least sensitive to extreme downside risk in the U.S. and Japan, Australia is the most sensitive to the U.S., and Singapore is the most sensitive to Japan.     

Jump risk premia across major international equity markets

We decompose the non-diversifiable market risk into continuous and discontinuous components and jump systematic risks into positive vs. negative and small vs. large components. We examine their association with equity risk premia across major equity markets. We show that developed markets jumps are more closely linked to the aggregate market index than emerging and frontier ones. The reward for bearing both the continuous and downside jump risks is positive during the pre-crisis period whereas the reward for bearing the upside and large jump risks is negative during the crisis and post-crisis periods. We also provide evidence of significant continuous and discontinuous leverage effects during the pre-crisis period, suggesting that both continuous and discontinuous price and volatility risks share compensations for common underlying risk factors.     

ON ESTIMATING STOCK MARKET VOLATILITY: AN EXPLORATORY APPROACH

Traditional methods of estimating market volatility use daily return observations from a stock index to calculate monthly variance. We break with tradition and estimate stock market volatility using the daily, cross-sectional standard deviation of returns for all firms trading on the New York Stock Exchange and the American Stock Exchange. We find a significantly positive relation between risk and return. Market volatility is estimated to be about half the volatility level previously reported. The intraday, cross-sectional market volatility measure provides findings consistent with risk-return theory.     

The performance of precious-metal mutual funds: Does uncertainty matter?

We studied the relative risk-adjusted returns and downside risk performance of precious-metal mutual funds (PMFs) in different uncertainty periods (pre-crisis, crisis and post-crisis) using propensity score matching techniques and difference-in-differences matching regression. For a sample of PMFs and global corporate funds quoted in USD over the period January 2005 to June 2015, we found that the relative performance of PMFs differed across uncertainty periods. Thus, they performed similarly to corporate funds in the pre-crisis period, they outperformed corporate funds regarding risk-adjusted returns but underperformed in terms of downside risk in the crisis period and they displayed a similar risk-return performance to corporate funds in the post-crisis period. Difference-in-difference estimates indicate that a shift from low to high uncertainty had a positive impact on risk-adjusted returns for PMFs, whereas this advantage dissipated when uncertainty was reduced. However, fluctuations in uncertainty had mixed effects on the relative downside risk associated with PMFs. This evidence has implications for investors who seek to gain exposure to precious metals using PMFs.     

An accounting analysis of the risk-return relationship in bull and bear markets

This study provides evidence that accounting beta (earnings and cash flow-based) provides information consistent with the risk-return relationship in up- and down-markets. We are not able, however, to provide similar evidence using market beta. Considering that investors' ability to assess the risk-return trade-off in up- and down-markets is central to efficient portfolio formation, the results suggest that accounting data can provide appropriate measures of portfolio upside and downside risk.     

Brand Equity and Firm Risk: An Empirical Investigation in an Emerging Market

The aim of this article is to investigate the relationship between brand equity and firm risk in Turkey using a sample of 254 firm-year observations for the period 2009–2014. Our findings suggest that brand equity is an important determinant of equity risk in addition to conventional firm-specific variables. In particular, after controlling for firm-specific variables, the results reveal that firms with high brand equity experience lower volatility in stock returns. We also find that enhancing brand equity is an important tool for firms in reducing unsystematic and downside systematic risk in their stock prices. Our findings are robust to different valuation models of domestic and global investors as well as different methods of estimations. The results are encouraging for both marketing managers and investors, particularly those in emerging markets where stock price volatility is relatively higher than in developed markets.     

News implied volatility and disaster concerns

We construct a text-based measure of uncertainty starting in 1890 using front-page articles of the Wall Street Journal. News implied volatility (NVIX) peaks during stock market crashes, times of policy-related uncertainty, world wars, and financial crises. In US postwar data, periods when NVIX is high are followed by periods of above average stock returns, even after controlling for contemporaneous and forward-looking measures of stock market volatility. News coverage related to wars and government policy explains most of the time variation in risk premia our measure identifies. Over the longer 1890–2009 sample that includes the Great Depression and two world wars, high NVIX predicts high future returns in normal times and rises just before transitions into economic disasters. The evidence is consistent with recent theories emphasizing time variation in rare disaster risk as a source of aggregate asset prices fluctuations.     

The frequency of regime switching in financial market volatility

The mechanism of risk responses to market shocks is considered as stagnant in recent financial literature, whether during normal or stress periods. Since the returns are heteroskedastic, a little consideration was given to volatility structural breaks and diverse states. In this study, we conduct extensive simulations to prove that the switching regime GARCH model, under the highly flexible skewed generalized t (SGT) distribution, is remarkably efficient in detecting different volatility states. Next, we examine the switching regime in the S&P 500 volatility for weekly, daily, 10-minute and 1-minute returns. Results show that the volatility switches regimes frequently, and differences between the distributions of the high and low volatility states become more accentuated as the frequency increases. Moreover, the SGT is highly preferable to the usually employed skewed t distribution.     

The systematic pricing of market sentiment shock

ABSTRACT

We show that market sentiment shocks create demand shocks for risky assets and a systematic risk for assets. We measure a market sentiment shock as the unexpected portion of the University of Michigan Consumer Sentiment Index’s growth. This shock prices stock returns in arbitrage pricing theory framework at 1% after controlling for market, size, value, momentum, and liquidity risk factors. Its premium lowered the implied risk aversion by 97.9% to 11.46 between 1978 and 2009 in our sentiment consumption-based capital-asset-pricing model. Merton’s [1973. “An Intertemporal Capital Asset Pricing Model.” Econometrica 41: 867–887]. intertemporal capital-asset-pricing model reconfirms our finding that this market sentiment shock is a systematic risk factor that provides investment opportunities.     

Surprise volume and heteroskedasticity in equity market returns

Heteroskedasticity in returns may be explainable by trading volume. We use different volume variables, including surprise volume—i.e. unexpected above-average trading activity—which is derived from uncorrelated volume innovations. Assuming weakly exogenous volume, we extend the Lamoureux and Lastrapes () model by an asymmetric GARCH in-mean specification following Golsten et al. (). Model estimation for the US as well as six large equity markets shows that surprise volume provides superior model fit and helps to explain volatility persistence as well as excess kurtosis. Surprise volume reveals a significant positive market risk premium, asymmetry and a surprise volume effect in conditional variance. The findings suggest that e.g. a surprise volume shock (breakdown)—i.e. large (small) contemporaneous and small (large) lagged surprise volume—relates to increased (decreased) conditional market variance and return.     

Intertemporal risk-return trade-off in foreign exchange rates

We investigate the intertemporal risk-return trade-off of foreign exchange (FX) rates for ten currencies quoted against the USD. For each currency, we use three risk measures simultaneously that pertain to that currency; its realized volatility, its realized skewness, and its value-at-risk. We apply monthly FX excess returns and risk measures calculated from daily observations. We find that there is a significant contemporaneous risk-return trade-off for the currencies under investigation. There is no evidence of noncontemporaneous risk-return trade-off. We pay special attention to the risk-return trade-off during the recent financial crisis.     

Portfolio Returns,Market Volatility,and Seasonality

This paper examines three important issues related to the relationship between stock returns and volatility. First, are Duffee's (1995) findings of the relationship between individual stock returns and volatility valid at the portfolio level? Second, is there a seasonality of the market return volatility? Lastly, do size portfolio returns react symmetrically to the market volatility during business cycles? We find that the market volatility exhibits strong autocorrelation and small size portfolio returns exhibit seasonality. However, this phenomenon is not present in large size portfolios. For the entire sample period of 1962–1995, the highest average monthly volatility occurred in October, followed by November, and then January. Examining the two sub-sample periods, we find that the average market volatility increases by 15.4% in the second sample period of 1980–1995 compared to the first sample period of 1962–1979. During the contraction period, the average market volatility is 60.9% higher than that during the expansion period. Using a binary regression model, we find that size portfolio returns react asymmetrically with the market volatility during business cycles. This paper documents a strongly negative contemporaneous relationship between the size portfolio returns and the market volatility that is consistent with the previous findings at the aggregate level, but is inconsistent with the findings at the individual firm level. In contrast with the previous findings, however, we find an ambiguous relationship between the percentage change in the market volatility and the contemporaneous stock portfolio returns. This ambiguity is attributed to strongly negative contemporaneous and one-month ahead relationships between the market volatility and portfolio returns.