A New Approach to Improving Hedging Performance in the OLS Model

The sensitivity of VIX futures to market movements changes over time with changes in market risk. Accordingly, in the case of using the OLS (ordinary least squares) model to hedge S&P 500 exposure with VIX futures, hedge ratios are affected by changes in risk appetite, which in turn contributes to the overall hedging performance as well as the asymmetry of the performance distribution. The conventional OLS approach does not effectively reflect this phenomenon in the model. In this study, the authors explore a new approach to improving hedging performance in the OLS model. They introduce an interaction term between the VIX and VIX futures returns into the OLS model. They find that the hedge ratios derived by the new approach provide better hedging results compared to the univariate OLS model in terms of mean return and downside risk protection, and also improve the asymmetry of the performance distribution. They extend their research to compare it with the performance of the dynamic conditional correlation (DCC)-generalized autoregressive conditional heteroskedasticity (GARCH) model. The new approach also shows better results than the DCC-GARCH approach. They obtain the same results in case studies of the Global Financial Crisis and the COVID-19 pandemic, and also in applying a trading strategy to each hedging methodology.

Asymmetric volatility spillover among global oil, gold, and Chinese sectors in the presence of major emergencies

The volatility of international crude oil and gold markets has affected stock markets through several economic channels, and the impact tends to be more evident with the appearance of emergencies. However, the volatility linkages between commodities and Chinese sector stocks in the presence of emergencies are understudied. To examine the asymmetric relationship and time-varying connectedness between commodities and Chinese sector stocks, this paper first employs GJR-GARCH to capture the realized volatility of international oil, gold, and Chinese sector stocks. Secondly, we decompose the realized volatility of international oil and gold into bad and good volatility and then employ the TVP-VAR-DY approach to obtain the connectedness index. The final result shows asymmetric volatility spillover among oil, gold, and Chinese sector stocks. During the COVID-19 outbreak, the gold good volatility transmission is intenser than bad volatility. Thirdly, the analysis is also carried out under different subperiods. They include three international events: the global financial crisis and the European debt crisis, the oil crisis, and COVID-19. The result reveals heterogeneity exists in the impact of international oil and gold on the Chinese sector stocks under different emergencies. These findings are of great significance for policymakers to improve the sector management under the impact of different emergencies and for investors to design diversified portfolios according to the commodity-sector risk spillover effects. © 2023 Elsevier Ltd

Asymmetric effects and volatility transmission from metals markets to solar energy stocks: Evidence from DCC, ADCC, and quantile regression approach

Detrimental environmental repercussions have recently given rise to an interest in green investments. Although solar energy stocks are appealing assets for ethical investors, little is known about their dynamic correlations and linkages with metal (silicon, lithium, and rare earth) markets, particularly during economic events which is essential for hedging effectiveness and asset allocation. This study investigates the nexus between metal markets, oil price volatility (OVX), market sentiments (VIX), and solar energy markets using DCC, ADCC models, and the quantile regression approach. The results show both symmetric and asymmetric shock spillover between metals markets, VIX, OVX, and solar energy markets which are more prominent during COVID-19 pandemic, US-China trade frictions, and Russian invasion of Ukraine. For portfolio management, the hedging effectiveness of lithium stocks is highest, followed by silicon and rare earth metals. However, the hedge ratios are time-varying, and the variability is highest during US-China trade frictions. The quantile regression estimates reveal that lithium market is the most persistent determinant of solar energy stocks followed by silicon market even after segregating the periods into Paris Agreement and COVID-19 pandemic. Thus, lithium and silicon are driving markets of solar energy markets and can be a cause of omitted variable bias if stay unobserved. Nonetheless, there is little influence of VIX, rare earth metals, and OVX on solar energy stocks. Lastly, the estimations of threshold regression suggest that market sentiments change the association between metal markets and solar energy markets after the VIX reaches a certain threshold level. © 2023

On the Risk Spillover from Bitcoin to Altcoins: The Fear of Missing Out and Pump-and-Dump Scheme Effects

This article examines the asymmetric volatility spillover effects between Bitcoin and alternative coin markets at the disaggregate level. We apply a frequency connectedness approach to the daily data of 11 major cryptocurrencies for the period from 1 September 2017 to 2 March 2022. We try to uncover the existence of the "fear of missing out” psychological effect and "pump-and-dump schemes” in the crypto markets. To do that, we estimate the volatility spillovers from Bitcoin to altcoin and the cryptos' own risk spillovers during bull and bear markets. The spillover results from Bitcoin to altcoin provide mixed results regarding the presence of this theory for major cryptocurrencies. However, the empirical findings carried out by the cryptos' own spillover effects fully confirm the existence of a fear-of-missing-out effect and pump-and-dump schemes in all cryptocurrencies except for USDT.

Covid-19 Pandemisi Döneminde Asimetrik Volatilite Bulguları: BIST Sektör Endekslerinde Bir Ínceleme

Asimetrik volatilite negatif dalgalanmaların varyans üzerinde pozitif dalgalanmalara göre daha yüksek etki yaratması olarak tanımlanabilir. Bu olgu finansal serilerin yapısal bir özelliği olmakla birlikte kriz dönemlerinde daha da derinleştiği düşünülmektedir. Bu çalışmada 2020 başlarında uzak doğu ülkelerinde görülmeye başlayan daha sonra hızla tüm dünyaya yayılan pandemi kaynaklı küresel krizin etkisi sonucu asimetrik volatilite varlığı test edilmiştir. Pandemi kaynaklı krizin BIST birincil sektör endeksleri üzerinde yarattığı asimetrik volatilite etkisi incelenmiştir. Çalışmada GJR-GARCH (1,1) istatistiksel modeli kullanılmıştır. Bulunan sonuçlara göre asimetrik volatilite hem pandemi öncesi hem de pandemi dönemi için BIST sektör endekslerinin karakteristik bir özelliği olmakla birlikte bütün alt sektörler kriz sonrası dönemde daha anlamlı derecede sonuçlar vermiştir. Ayrıca asimetri katsayısının kriz sonrası dönemlerin tamamında daha yüksek olduğu görülmüştür.Alternate :Asymmetric volatility can be defined as negative fluctuations having a higher effect on the variance than positive fluctuations. Although this phenomenon is a structural feature of financial series, it is thought to strengthen even more during crisis periods. In this study, the presence of asymmetric volatility was tested as a result of the effect of the global crisis caused by the pandemic, which started to be seen in the Far East countries at the beginning of 2020 and then spread rapidly all over the world. The asymmetric volatility effect of the crisis on BIST primary sector indices has been examined. GJR-GARCH (1,1) statistical model is applied. Based on findings, although asymmetric volatility is a characteristic feature of BIST sector indices for both the pre-pandemic and pandemic periods, all sectors gave more significant results in the pandemic period. In addition, it is observed that the asymmetry coefficient is higher in all pandemic periods.

Investigating the impact of COVID-19 pandemic on volatility patterns and its global implication for textile industry: An empirical case study for Shanghai Stock Exchange of China

This research paper aims to examine the impact of the COVID-19 pandemic on volatility patterns and its global implication for the textile industry in China. The COVID-19 pandemic has generated a global health crisis with profound economic, social and financial implications, but also has triggered a ruthless global recession. The global economic recovery as a result of the COVID-19 pandemic can also generate significant investment opportunities for the textile industry in China. In this paper, the application of empirical methods could explain historical prices, the movement dynamics of financial assets, and investigate various important characteristics of asset pricing that explore details of the Chinese stock market. The econometric framework includes the following: symmetric Generalize Autoregressive Conditional Heteroscedastic GARCH (1, 1) model, asymmetric GARCH models such as EGARCH and GJR models. The main aim is to identify the asymmetric volatility effect, and impact of news on the SSE Composite Index and investigate long memory properties in volatility using daily data for the sample period from 19th December 1990 to 31st December 2020. This empirical study contributes to the existing literature on the impact of the COVID-19 pandemic on international stock markets, by investigating symmetric and asymmetric volatility patterns in the case of the Shanghai Stock Exchange from China.

Volatility spillovers from the Chinese stock market to the U.S. stock market: The role of the COVID-19 pandemic.

The COVID-19 pandemic, which originated in Wuhan, China, precipitated the stock market crash of March 2020. According to published global data, the U.S. has been most affected by the tragedy throughout this outbreak. Understanding the degree of integration between the financial systems of the world's two largest economies, particularly during the COVID-19 pandemic, necessitates thorough research of the risk transmission from China's stock market to the U.S. stock market. This study examines the volatility transmission from the Chinese to the U.S. stock market from January 2001 to October 2020. We employ a variant form of the EGARCH (1,1) model with long-term control over the excessive volatility breakpoints identified by the ICSS algorithm. Since 2004, empirical evidence indicates that the volatility shocks of the Chinese stock market have frequently and negatively affected the volatility of the U.S. stock market. Most importantly, we explore that the COVID-19 pandemic vigorously and positively promoted the volatility infection from the Chinese equity market to the U.S. equity market in March 2020. This precious evidence endorses the asymmetric volatility transmission from the Chinese to the U.S. stock market when COVID-19 broke out. These experimental results provide profound insight into the risk contagion between the U.S. and China stock markets. They are also essential for securities investors to minimize portfolio risk. Furthermore, this paper suggests that globalization has carefully driven the integration of China's stock market with the international equity markets.

Dynamic dependence and hedging strategies in BRICS stock markets with oil during crises

This paper discusses the asymmetric volatility spillovers between these two markets of BRICS’ countries during different financial and economic circumstances from 2010 until 2021, using the ARFIMA-FIAPARCH to model the dynamics of the marginal distribution. We study the feasibility of hedging stocks with oil, risk measurement functions allow financial practitioners to calculate the optimal hedge ratios and the corresponding to hedge portfolio returns. A dual long memory model is adopted to estimate the conditional mean and the conditional variance. Thereafter, a VaR, CVaR and ΔCVaR are applied to assess oil price exposure. Furthermore, to evaluate the optimal portfolio, we adopted the optimal portfolio weight, the optimal hedge ratio and the hedge effectiveness oil. Our results show that there are distinct economic benefits from hedging stocks with oil, although the effectiveness of hedging is both time-varying and market-state-dependent. We determine that the volatility transmission was time-varying and that influence from the Asian crisis, the bursting of the dot com bubble, the 2008 global financial crisis, the recent oil-price crash, and COVID 19 alternated between negative and positive values, over the entire studied period. During times of global financial uncertainty, investors reduce stock positions more than commodity positions, thus crude oil prices shock negatively affect the portfolio returns of stock-oil hedges. all stock market -oil pairs display the highest hedging effectiveness during the COVID-19 pandemic, which proved that the oil market can assist as a hedge for stock market in a portfolio.

CONTAGION ACROSS FINANCIAL MARKETS DURING COVID-19: A LOOK AT VOLATILITY SPILLOVERS BETWEEN THE STOCK AND FOREIGN EXCHANGE MARKETS IN SOUTH AFRICA

The onset of the novel coronavirus pandemic (COVID-19) and previous financial and currency crises have heightened interest in understanding the nature of the interaction of stock market and exchange rate volatility. This paper aims to investigate the interdependence and volatility transmissions between the stock and foreign exchange markets for South Africa over the period of 1979:01–2021:08, including the effect the COVID-19 pandemic has had on the interdependence and volatility transmissions. Through the use of bivariate Exponential Generalized Autoregressive Conditional Heteroscedasticity (EGARCH) modeling, the empirical outcomes from this study provide strong evidence in support of the “stock-orientated” approach, where significant price and volatility spillovers propagate from the stock market into the foreign exchange market, whilst evidence of the “flow-orientated” approach is seen in the second moment and significant shock and asymmetric spillovers from the exchange to stock market are found. The results support the asymmetric and long-range persistence volatility spillover effect and show strong evidence of contagion between stock and foreign exchange markets. These spillovers became more pronounced during the COVID-19 pandemic, confirming heightened contagion in these markets during the periods of crisis. The results heed important implications for not only policymakers who are concerned by the contagion across financial markets and better regulations of these markets to promote economic growth, but also investors and fund managers who seek to hedge investment risks in South Africa.

Risk-Return Trade-off and Volatility Characteristics in the Indian Stock Market

The study examines the volatility characteristics of Indian stock markets and their tradeoff between the risk and return. It finds a positive but insignificant association between the risk and returns during the subsample (the pre-COVID and COVID pandemic outbreak) and whole sample periods. The study also shows that the weak form of Indian stock markets is not sustainable. Consistent with the GARCH literature, persistent and asymmetric effects are evidenced, and the magnitude of the negative shocks has a larger immediate impact than the positive shocks. These results would help measure the volatility in the Indian stock markets and provide investors and regulators with necessary information about the market efficiency, persistency (long-memory process) and asymmetric effects. © 2022 Manickam Tamilselvan et al;published by UIKTEN. This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 License

Measuring Leverage Effect of Covid 19 on Stock Price Volatility of Energy Companies Using High Frequency Data

The uprising of the pandemic COVID-19 has paralysed the whole Indian economy, and as a result the Indian stock market is severely affected too. The widely inclusive lockdown articulated on 24th March 2020 by the Prime Minister as a careful step against COVID-19, trailed by ensuing augmentations, has brought about a halt of all financial movement in the country. The objective of the study is to frame different asymmetric price volatility models for Selected Companies under Energy Sector using 1-minute closing price from 15th October 2019 to 15th May 2020 to captivate the leverage effect of the pandemic. The asymmetric terms in the selected asymmetric models are providing sufficient proof that the stock price volatility of three companies out of six under NIFTY Energy i.e., BPCL, Power grid and Indian Oil Corporation are unfavourably influenced by the pandemic. The forecasting graphs for volatility of four companies have been plotted, reveals that there is consistency in the stock price returns of all these four companies but the graph of predicted variance of Indian Oil Corporation reveals that the volatility has been fluctuating drastically with many high peak variances or fluctuations during the two days of forecasted period.

Time-frequency domain analysis of investor fear and expectations in stock markets of BRIC economies.

The purpose of this study is to provide insight into the lead-lag relationships between the BRIC stock index and its constituents. In addition, we assess the comovements between the US volatility index (VIX) as a measure of investor uncertainty and fear and stock returns of BRIC economies. Therefore, the bi-wavelet and wavelet multiple correlations approaches are utilised. Findings from the bi-wavelet technique indicate that there are high interdependencies between the BRIC index and its constituents throughout the time-frequency domain. In addition, comovements between the BRIC index and its constituents was positive and significant. Notwithstanding, we find the BRIC index to be the first variable to respond to shocks when all the study variables were considered in the wavelet multiple cross-correlations. Similarly, the stock market of Brazil is the next to respond to shocks. On the other hand, the stock market of Russia lags in the long-term when the BRIC index was excluded from the wavelet multiple cross-correlations. We also find a uni-directional causality between the VIX and the BRIC stocks in the medium-, and long-terms. Specifically, the US VIX significantly drives the BRIC stocks and considered to be negative. Findings from the study imply that global investors can select any of the stock markets in BRIC to allocate their investments due to their strong interdependencies which may facilitate trade and investments. However, portfolio diversification, safe haven or hedge benefits within this region may be minimal due to their high integration with the BRIC index which demonstrates positive significant comovements. The findings present relevant inferences for portfolio diversification, policy decisions, and risk management schemes. It is recommended that investors hedge against volatilities in the BRIC stock markets using the US VIX.