Negative Return Shocks Research Articles

Double Asymmetric Impacts, Dynamic Correlations, and Risk Management Amidst Market Risks: A Comparative Study between the US and China

Extreme shocks, including climate change, economic sanctions, geopolitical conflicts, etc., are significant and complex issues currently confronting the global world. From the US–China perspective, this paper employs the DCC-DAGM model to investigate how diverse market risks asymmetrically affect return volatility, and extract correlations between stock indices and hedging assets. Then, diversified and hedging portfolios, constructed by optimal weight and hedge ratio, are investigated using multiple risk reduction measures. The empirical results highlight that, first, diverse risks exhibit an asymmetric effect on the return volatility in the long term, while in the short term, the US stock market is more sensitive to negative return shocks than the Chinese market. Second, risks impact correlations differently across time horizons and countries. Short-term correlations are stronger than long-term ones for the US market, with the Chinese stock market displaying more stable correlations. Third, the hedging strategy is more effective in reducing volatility and risk for US stocks, while the diversification strategy proves more effective for Chinese stocks. These findings have implications for market participants striving to make their portfolios robust during turbulent times.

Return-volatility relationships in cryptocurrency markets: Evidence from asymmetric quantiles and non-linear ARDL approach

Implied volatility has consistently demonstrated its reliability as a superior estimator of the expected short-term volatility of underlying assets. In this study, we employ the newly constructed robust model-free implied volatility (MFIV) indices for Bitcoin and Ethereum (BitVol and EthVol) to explore the asymmetric return-volatility relationship of these cryptocurrencies through the lens of behavioral finance theories. Utilizing the asymmetric quantile regression model (QRM) and the Non-linear ARDL (NARDL) approach, our results reveal a notable difference from equities. Both positive and negative return shocks in the cryptocurrency market lead to an increase in volatility. However, during high volatility regimes, positive (negative) return shocks exert a more substantial impact on positive innovations of volatility for Bitcoin (Ethereum) compared to negative (positive) return shocks. The degree of asymmetry steadily intensifies as we progress from medium to uppermost quantiles of the volatility distribution. These observed phenomena can be attributed to behavioral aspects among market participants, including noise trading, behavioral biases, and fear of missing out (FOMO). Our findings hold significant implications for various aspects of cryptocurrency trading, portfolio hedging strategies, volatility derivatives pricing, and risk management.

A quantile-based analysis of risk-return dynamics in the South African equity market

ABSTRACT This paper employs quantile autoregression to investigate the influence of ‘market size’ and ‘industry’ effects on the South African equity market volatility response to return shocks. It is now well documented that equity market volatility exhibits asymmetric response to positive and negative return shocks. This paper provides empirical evidence which shows that the South African equity market asymmetric volatility response is significantly a large company phenomenon and with the exception of the Resources 10 and Financials 15 Indices, there is generally no volatility asymmetric response heterogeneity at the sector level. These results have important implications for investors and fund managers in relation to portfolio construction, risk management and optimal equity risk premium determination.

Optimal futures hedging by using realized semicovariances: The information contained in signed high‐frequency returns

AbstractThis paper proposes a realized semicovariance‐based generalized autoregressive conditional heteroskedasticity (GARCH) model for optimal futures hedging in which realized semicovariances are computed from signed high‐frequency returns. The model enables flexible, continuous leverage for equity indices and exhibits stronger responses to jointly negative return shocks than do traditional threshold‐based asymmetric GARCH models. Our results indicate that the proposed model outperforms simpler models in model fit, covariance prediction, and portfolio variance reduction and can help achieve pronounced economic gains for hedgers. The findings demonstrate that signed high‐frequency returns contain valuable information for explaining covariance asymmetries and provide managerial implications for market participants to improve risk management.

Product market competition and stock return dependence

We model the spillover effect between competing firms’ daily idiosyncratic stock returns, using spatial econometric techniques. Contagion effect from rival firms dominates competitive effect, and the net effect is larger from negative return shocks of rival firms than from positive ones. The net effect is strong for firms in product markets with low concentration and high product market fluidity.

Bond Fund Fragility: Flow Reactions to Extremely Negative Return Shocks

Nous étudions la forme de la relation entre les flux des fonds obligataires français et leurs performances. Nous trouvons que les fonds présentant des rentabilités brutes de court-terme très négatives doivent faire face à des flux sortants plus importants (cet effet apparaît lors du dernier quintile de rentabilités négatives). Par ailleurs, les investisseurs semblent sensibles aux périodes de stress financier. Des résultats complémentaires montrent que pour les investisseurs institutionnels, l’effet non-linéaire des rentabilités brutes de court-terme apparaît plus fréquemment, en commençant avec le deuxième quintile de performances négatives. Cela confirme la fragilité des fonds obligataires face à des chocs négatifs sur les rentabilités.

Risk spillovers between cryptocurrencies and traditional currencies and gold under different global economic conditions

This paper applies a Diagonal BEKK model to investigate the risk spillovers of three major cryptocurrencies to ten leading traditional currencies and two gold prices (Spot Gold and Gold Futures). The daily data used are from 7 August 2015 to 15 June 2020. The dataset is analyzed in its entirety and is also subdivided into four distinct subsets in order to study and compare the patterns of spillover effects during economic turmoil, such as the 2018 cryptocurrency crash and the COVID-19 pandemic. The results reveal significant co-volatility spillover effects between cryptocurrency and traditional currency or gold markets, especially during the whole sample period and amid the uncertainty raised by COVID-19. The capabilities of cryptocurrency are time-varying and related to economic uncertainty or shocks. There are significant differences between normal and extreme markets with regard to the capabilities of cryptocurrency as a diversifier, a hedge or a safe haven. We find the significant co-volatility spillover effects are asymmetric in most cases especially during the COVID-19 pandemic period, which means the negative return shocks have larger impacts on co-volatility than positive return shocks of the same magnitude. Evidently, cryptocurrencies and traditional currencies or gold can be incorporated into financial portfolios for financial market participants who seek effective risk management and also for optimal dynamic hedging purposes against economic turmoil and downward movements.

On a Bivariate Hysteretic AR-GARCH Model with Conditional Asymmetry in Correlations

This paper investigates a conditionally dynamic asymmetric structure in correlations when multivariate time series follow a hysteretic autoregressive GARCH process that exhibits nonlinear switching in mean, volatility, and correlation. The hysteresis variable in the proposed model controls regime switching and time-varying delay. This new model allows for distinct responses to negative return shocks, as it can flexibly explore the possibility of asymmetry in the conditional correlation of two target variables. We employ an adaptive Bayesian MCMC method for the parameter estimation and quantile forecasting, which includes value-at-risk and volatility. We conduct backtesting to measure the effectiveness of value-at-risk forecasting, illustrate the proposed methods by using both simulated and real examples, and jointly measure for industry downside tail risk. Lastly, we evaluate the accuracy of the volatility forecast and determine whether there is persistence of conditional asymmetry in conditional correlation in the target time series.

Multivariate leverage effects and realized semicovariance GARCH models

We propose new asymmetric multivariate volatility models. The models exploit estimates of variances and covariances based on the signs of high-frequency returns, measures known as realized semivariances, semicovariances, and semicorrelations, to allow for more nuanced responses to positive and negative return shocks than threshold “leverage effect” terms traditionally used in the literature. Our empirical implementations of the new models, including extensions of widely-used bivariate GARCH specifications for a number of individual stocks and the aggregate market portfolio as well as larger dimensional dynamic conditional correlation type formulations for a cross-section of individual stocks, provide clear evidence of improved model fit and reveal new and interesting asymmetric joint dynamic dependencies.

Equity Risk Premium Puzzle: Evidence from Indonesia and Sri Lanka

This paper investigates the equity risk premium puzzle in the Indonesian and Sri Lankan stock markets in order to identify the relationship between the volatility of excess returns and the equity risk premium. The asymmetric impact of negative shocks on the equity risk premium is also examined using threshold and exponential GARCH-M models. We analyse data on the excess returns of the Indonesian and Sri Lankan stock markets from 2004 to 2013, and we find that the impact of the conditional volatility of excess returns on the equity risk premium is not significant in either country. Instead, we find an impact from negative return shocks on the equity risk premium only in Sri Lanka. Therefore, we conclude that investors are not compensated for the conditional volatility of the excess returns in these two markets, while Sri Lankan investors are compensated for the risk of negative shocks.

Shape-constrained semiparametric additive stochastic volatility models

ABSTRACTNonparametric stochastic volatility models, although providing great flexibility for modelling the volatility equation, often fail to account for useful shape information. For example, a model may not use the knowledge that the autoregressive component of the volatility equation is monotonically increasing as the lagged volatility increases. We propose a class of additive stochastic volatility models that allow for different shape constraints and can incorporate the leverage effect – asymmetric impact of positive and negative return shocks on volatilities. We develop a Bayesian fitting algorithm and demonstrate model performance on simulated and empirical datasets. Unlike general nonparametric models, our model sacrifices little when the true volatility equation is linear. In nonlinear situations we improve the model fit and the ability to estimate volatilities over general, unconstrained, nonparametric models.

Multivariate Leverage Effects and Realized Semicovariance GARCH Models

We propose new asymmetric multivariate volatility models. The models exploit estimates of variances and covariances based on the signs of high-frequency returns, measures known as realized semivariances, semicovariances, and semicorrelations, to allow for more nuanced responses to positive and negative return shocks than threshold “leverage effect” terms traditionally used in the literature. Our empirical implementations of the new models, including extensions of widely-used bivariate GARCH pecifications for a number of individual stocks and the aggregate market portfolio as well as larger dimensional dynamic conditional correlation type formulations for a cross-section of individual stocks, provide clear evidence of improved model fit and reveal new and interesting asymmetric joint dynamic dependencies.

An Examination of Asymmetric Relation between Implied Volatility Index and Its Underlying Asset

The volatility index is the measure of 30-day expected volatility. Its association with stock index returns provides an insight to the volatility traders to launch derivatives products so that it can be used as a hedging tool. The aim of the present study is to empirically examine the relationship between the implied volatility indices and its underlying asset in context of developed and developing markets (like U.S., Japan, Germany, and China). The empirical findings report the asymmetric behaviour which indicates that a larger impact on implied volatility indices are from negative return shocks as compared to positive returns. This evinced that the investors and traders respond highly to negative returns in low volatile period by demanding more options at high premium which makes the implied volatility high. Therefore, the negative relationship between IVIX and stock index returns makes the index relevant for investors to diversifying their portfolio so that they can mitigate the investment risk associated with the volatility.

Stock Return Dependence and Product Market Linkages

We model the immediate responses of firms’ daily idiosyncratic stock returns to the idiosyncratic returns of the firms’ rivals and major customers, using spatial econometric techniques. We show that ignoring firms’ response to rivals results in non-negligible overestimation of firms’ response to major customers while ignoring customer-supplier interactions leads to overestimation of response to rivals. We relate the immediate price comovement to several firm and industry characteristics. Contagion effect of rivals dominates competition effect and the net effect is larger when firms respond to negative return shocks of rival firms than to positive ones. The net effect is strong for firms in product markets with low concentration and high product market fluidity. Suppliers with lower product uniqueness and higher customer concentration are more sensitive to the shocks from their customers.

Asymmetry in spillover effects: Evidence for international stock index futures markets

The paper investigates the asymmetry in return and volatility spillovers across futures markets with non-overlapping stock exchange trading hours. The transmission of positive and negative return and volatility shocks is analysed for 104 channels of information conveyance identified by combining 9 developed and 11 emerging markets in markets pairs with non-overlapping trading hours. The asymmetric causality test is employed to daily stock index futures returns and volatilities for the period from 03 October 2010 to 03 October 2014. The paper sheds light on the relatively little explored concept of asymmetry in return and volatility spillovers across markets, providing novel evidence on stabilizing and destabilizing spillover effects.

Capital structure and corporate reaction to negative stock return shocks

This study investigates firms’ capital structure decisions around significant drops in stock price. We present evidence that firms usually repurchase equity to boost stock prices following these shocks, rather than retiring debt to rebalance their capital structures, even though buybacks cause their capital structures to deviate farther from the previous levels. We also show that managerial incentives and firms’ historical financial policies (e.g., high cash holdings or almost zero leverage) play more important roles in determining how firms react to stock price shocks than do managers’ desires to maintain optimal leverage.

The Relation between Return and Volatility in ETFs Traded in Borsa Istanbul : Is There Any Difference between Islamic and Conventional ETFs ?

In this study, we aim to analyze the relation between return and volatility in different types of exchange-traded funds (ETFs) traded in the Borsa Istanbul. The types we examine are Islamic stock index, conventional stock index, bond, commodity, and U.S. dollar ETFs. We employ the following battery of causality analysis methods that have different statistical advantages to each other: Toda-Yamamoto (1995); bootstrap based Hatemi-J (2005); volatility spillover, which allows investigating causality in variance; frequency domain, which decomposes causality due to different time frequencies; and asymmetric causality, developed by Hatemi-J, which enables finding causation linkages for different types of shocks in each variable. Although the results obtained from our analyses show that a negative relationship between return and volatility is valid for most ETF types, an asymmetric relation running from negative return shocks to positive volatility shocks is valid for only some conventional stock ETFs and U.S. dollar ETFs. On the other hand, Islamic ETFs and commodity ETFs have an asymmetric relation running from positive return shocks to negative volatility shocks. Our results show that the hypotheses investigated in this study vary with the ETF type included in the model.

On the relationship between implied volatility index and equity index returns

Purpose – The purpose of this paper is to analyze the asymmetric contemporaneous relationship between implied volatility index (India VIX) and Equity Index (S & P CNX Nifty Index). In addition, the study also analyzes the seasonality of implied volatility index in the form of day-of-the-week effects and option expiration cycle. Design/methodology/approach – This study employs simple OLS estimation to analyze the contemporaneous relationship among the volatility index and stock index. In order to obtain robust results, the analysis has been presented for the calendar years and sub-periods. Moreover, the international evidenced presented for other Asian markets (Japan and China). Findings – The empirical evidences reveal a strong persistence of asymmetry among the India VIX and Nifty stock index, at the same time the magnitude of asymmetry is not identical. The results show that the changes in India VIX occur bigger for the negative return shocks than the positive returns shocks. The similar kinds of results are recorded for the Japan and China volatility index. Particularly, the analysis also supports that India VIX holds seasonality, on the market opening VIX observed to be at its high level, and on the subsequent days it remains low. The results on the options expiration unfold the facts that India VIX remains more normal on the day of expiration. Practical implications – The asymmetric relation and seasonal patterns are quite useful to the volatility traders to price the financial assets when market trades in the high- and low-volatility periods. Originality/value – There is a lack of studies of this kind in the context of emerging markets like India; hence, this is an attempt in this direction. The study provides an insight to the NSE to launch some derivative products (i.e. F & Os) on India VIX that can generate more liquidity in the market for the volatility traders.

The Relation between Return and Volatility in ETFs Traded in Borsa Istanbul: Is There any Difference between Islamic and Conventional ETFs?

In this study, we aim to analyze the relation between return and volatility in different types of exchange-traded funds (ETFs) traded in the Borsa Istanbul. The types we examine are Islamic stock index, conventional stock index, bond, commodity, and U.S. dollar ETFs. We employ the following battery of causality analysis methods that have different statistical advantages to each other: Toda-Yamamoto (1995); bootstrap based Hatemi-J (2005); volatility spillover, which allows investigating causality in variance; frequency domain, which decomposes causality due to different time frequencies; and asymmetric causality, developed by Hatemi-J, which enables finding causation linkages for different types of shocks in each variable. Although the results obtained from our analyses show that a negative relationship between return and volatility is valid for most ETF types, an asymmetric relation running from negative return shocks to positive volatility shocks is valid for only some conventional stock ETFs and U.S. dollar ETFs. On the other hand, Islamic ETFs and commodity ETFs have an asymmetric relation running from positive return shocks to negative volatility shocks. Our results show that the hypotheses investigated in this study vary with the ETF type included in the model.

Asymmetry with respect to the memory in stock market volatilities

The empirically most relevant stylized facts when it comes to modeling time-varying financial volatility are the asymmetric response to return shocks and the long memory property. Up till now, these have largely been modeled in isolation. To capture asymmetry also with respect to the memory structure, we introduce a new model and apply it to stock market index data. We find that although the effect on volatility of negative return shocks is higher than for positive ones, the latter are more persistent and relatively quickly dominate negative ones.