scholarly journals Volatility Spillovers Between Oil Prices And Stock Returns: A Focus On Frontier Markets

2014 ◽  
Vol 30 (2) ◽  
pp. 509 ◽  
Author(s):  
Mathieu Gomes ◽  
Anissa Chaibi
Keyword(s):  
Stock Returns ◽  
Spillover Effect ◽  
Oil Prices ◽  
Portfolio Allocation ◽  
Transmission Mechanism ◽  
Volatility Transmission ◽  
Volatility Spillovers ◽  
Market Participants ◽  
The Mean ◽  
Allocation Decisions

Frontier markets are increasingly sought by investors in search of higher returns and low correlation with traditional assets. As such, it is important for financial market participants to understand the volatility transmission mechanism across these markets in order to make better portfolio allocation decisions. This paper employs a bivariate BEKK-GARCH(1,1) model to simultaneously estimate the mean and conditional variance between equity stock markets (twenty-one national frontier stock indices and two broad indices the MSCI Frontier Markets and the MSCI World) and oil prices. We examine weekly returns from February 8, 2008 to February 1, 2013 and find significant transmission of shocks and volatility between oil prices and some of the examined markets. Moreover, this spillover effect is sometimes bidirectional.

scholarly journals Oil price effect on sectoral stock returns: A conditional covariance and correlation approach for Mexico

2020 ◽  
Vol 16 (1) ◽  
pp. 1-15
Author(s):  
Rodrigo A. Morales Fernández Rafaelly ◽  
Roberto J. Santillán-Salgado
Keyword(s):  
Stock Returns ◽  
Stock Exchange ◽  
Spillover Effect ◽  
Oil Prices ◽  
Oil Price ◽  
Price Effect ◽  
Stock Market Performance ◽  
Original Contribution ◽  
Bivariate Garch Model ◽  
The Relationship

This paper analyzes the relationship between the volatility of oil price and selected sectoral stock returns in Mexico (industrials, materials, financials and consumer discretionary) by implementing a Diagonal VECH-type bivariate GARCH model in order to estimate conditional covariances and correlations. The econometric results suggest that there exists a statistically significant relationship between sector indices, as well as between Mexico’s aggregate stock exchange returns, and variations in oil prices. Conditional correlations suggest that during most of the analyzed period, the relationship between oil price fluctuations and sectoral stock returns is positive. The recommendation, supported by these results, is that investors should take into consideration the interaction between the analyzed variables in order to generate more robust risk-hedge strategies. An important limitation for this work is information availability at sector level in the country. The original contribution of this paper lies mainly in the analysis of the influence of oil prices over sectoral indices of the Mexican Stock Exchange. These results provide more support to the current that suggests that a price increase in oil has a direct spillover effect on stock market performance.

Shock and Volatility Spillovers Among Equity Sectors of the National Stock Exchange in India

2017 ◽  
Vol 19 (1) ◽  
pp. 227-240 ◽  
Author(s):  
Sayantan Bandhu Majumder ◽  
Ranjanendra Narayan Nag
Keyword(s):  
Global Financial Crisis ◽  
Stock Exchange ◽  
Debt Crisis ◽  
Portfolio Allocation ◽  
Volatility Spillover ◽  
Hedging Strategy ◽  
Volatility Transmission ◽  
Volatility Spillovers ◽  
Daily Data ◽  
Indian Stock Market

The basic thrust of this article is to examine how shocks and volatility are transmitted across sector indices. This article employs the autoregressive asymmetric BEKK-GARCH model. The study is based on daily data from the National Stock Exchange (NSE) of India from January 2004 to January 2014. Volatility spillover was found to be bidirectional among the two pro-cyclical sectors: Finance and IT. But, there was a unidirectional shock and volatility spillover from the non-cyclical FMCG sector to both the pro-cyclical sectors. The FMCG sector has remained almost unaffected by the spillover from the other sectors. Moreover, the evidence of asymmetric spillover has been found to be present in most of the case. Second, correlations between the sectors were found to be higher during the period of global financial crisis. But no such evidence was found in the context of the Euro zone debt crisis. Understanding the dynamics of shocks and volatility transmission is necessary for risk management in general and for optimal portfolio allocation and hedging strategy in particular. To the best of our knowledge, this is the first study on Indian stock market which has analysed the dynamics of shock and volatility transmission across sector indices.

scholarly journals Investor Protection, Equity Returns, and Financial Globalization

2009 ◽  
Vol 45 (1) ◽  
pp. 135-168 ◽  
Author(s):  
Mariassunta Giannetti ◽  
Yrjö Koskinen
Keyword(s):  
Stock Returns ◽  
Stock Price ◽  
Investor Protection ◽  
Portfolio Allocation ◽  
Equity Returns ◽  
Expected Returns ◽  
Home Equity ◽  
Controlling Shareholders ◽  
Home Equity Bias ◽  
Allocation Decisions

AbstractWe study the effects of investor protection on stock returns and portfolio allocation decisions. In our theoretical model, if investor protection is weak, wealthy investors have an incentive to become controlling shareholders. In equilibrium, the stock price reflects the demand from both controlling shareholders and portfolio investors. Due to the high demand from controlling shareholders, the price of weak corporate governance stocks is not low enough to fully discount the extraction of private benefits. Thus, stocks have lower expected returns when investor protection is weak. This has implications for domestic and foreign investors’ stockholdings. In particular, we show that portfolio investors’ participation in the domestic stock market and home equity bias are positively related to investor protection and provide original evidence in their support.

The Stochastic Character of Japanese Exchange Rates

2004 ◽  
Vol 5 (1) ◽  
pp. 77-90
Author(s):  
Nikiforos Laopodis
Keyword(s):  
Exchange Rate ◽  
Exchange Rates ◽  
Exchange Rate Volatility ◽  
Transmission Mechanism ◽  
Good News ◽  
Volatility Transmission ◽  
Volatility Spillovers ◽  
The Us ◽  
Us Dollar ◽  
Multivariate Exponential

The paper explores the stochastic character of six yen exchange rates with respect to the Canadian dollar, French franc, Italian lira, German mark, British pound and the US dollar for the 1973-2002 periods. The methodological design is the multivariate Exponential GARCH model, which is capable of capturing asymmetries in the exchange rate volatility transmission mechanism. The results point to significant reciprocal and positive volatility spillovers after the Plaza Accord of 1985. Furthermore, the finding of absence of asymmetry in the same period implies that bad and/or good news in a particular market positively and equally affects volatility in the next market.

scholarly journals Structural Breaks and Volatility Spillovers: The Case of the US and Canadian Stock Markets

2019 ◽  
Vol 11 (2) ◽  
pp. 30
Author(s):  
Chikashi Tsuji
Keyword(s):  
Stock Returns ◽  
Structural Breaks ◽  
Structural Break ◽  
Spillover Effect ◽  
Spillover Effects ◽  
Dummy Variables ◽  
Volatility Spillovers ◽  
Dummy Variable ◽  
The Us ◽  
Parameter Values

This paper investigates the relations of structural breaks and volatility spillovers by using the US and Canadian stock return data. Specifically, applying spillover MGARCH models without and with structural break dummy variables to the two stock returns, this study derives the following interesting evidence. (1) First, we reveal that for both the US and Canadian stock returns, the volatility persistence parameter values in our spillover MGARCH models decline when structural break dummy variables are incorporated. (2) Second, we further clarify that when we do not take structural breaks into account, the spillover effect was unidirectional from Canada to the US. However, when we take structural breaks into consideration, the results from our spillover MGARCH model with structural break dummies demonstrate that the volatility spillover effects between the US and Canada become bidirectional. (3) Third, we furthermore reveal that around the Lehman Brothers bankruptcy in 2008, the time-varying volatilities derived from our spillover MGARCH model with structural break dummy variables show slightly higher values than those volatilities from our spillover MGARCH model with no structural break dummy variable.

scholarly journals Dynamic Spillover Between The Oil And Stock Markets Of Emerging Oil-Exporting Countries

2013 ◽  
Vol 30 (1) ◽  
pp. 51 ◽  
Author(s):  
Frederic Teulon ◽  
Khaled Guesmi
Keyword(s):  
Stock Market ◽  
Stock Returns ◽  
United Arab Emirates ◽  
Stock Markets ◽  
Oil Prices ◽  
Multivariate Garch ◽  
Time Varying ◽  
Global Business ◽  
Stock Market Returns ◽  
Volatility Spillovers

<p>The paper investigates the time-varying correlations between stock market returns and oil prices in oil-exporting countries. A multivariate GARCH-DCC process is employed to evaluate this relationship based on data from Venezuela, the United Arab Emirates, Saudi Arabia and Kuwait. The results show that there are time-varying correlations between the oil and stock markets in emerging, oil-producing countries, indicating that they are affected by conditions in world markets. In addition, the relationship between oil prices and stock returns is found to be influenced by the origin of shocks to oil prices, with stock market responses being stronger to demand-side shocks caused by political turmoil or fluctuations in the global business cycle than to supply-side shocks caused by cuts in oil production. The results also provide evidence of volatility spillovers between the oil and stock markets.</p>

scholarly journals Idiosyncratic risk and the cross-section of stock returns: the role of mean-reverting idiosyncratic volatility

2018 ◽  
Vol 294 (1-2) ◽  
pp. 419-452 ◽  
Author(s):  
Stanislav Bozhkov ◽  
Habin Lee ◽  
Uthayasankar Sivarajah ◽  
Stella Despoudi ◽  
Monomita Nandy
Keyword(s):  
Stock Returns ◽  
Risk Premium ◽  
Empirical Studies ◽  
Idiosyncratic Risk ◽  
Risk Tolerance ◽  
Idiosyncratic Volatility ◽  
Market Participants ◽  
The Mean ◽  
The Difference ◽  
Risk Metric

Abstract A key prediction of the Capital Asset Pricing Model (CAPM) is that idiosyncratic risk is not priced by investors because in the absence of frictions it can be fully diversified away. In the presence of constraints on diversification, refinements of the CAPM conclude that the part of idiosyncratic risk that is not diversified should be priced. Recent empirical studies yielded mixed evidence with some studies finding positive correlation between idiosyncratic risk and stock returns, while other studies reported none or even negative correlation. We examine whether idiosyncratic risk is priced by the stock market and what are the probable causes for the mixed evidence produced by other studies, using monthly data for the US market covering the period from 1980 until 2013. We find that one-period volatility forecasts are not significantly correlated with stock returns. The mean-reverting unconditional volatility, however, is a robust predictor of returns. Consistent with economic theory, the size of the premium depends on the degree of ‘knowledge’ of the security among market participants. In particular, the premium for Nasdaq-traded stocks is higher than that for NYSE and Amex stocks. We also find stronger correlation between idiosyncratic risk and returns during recessions, which may suggest interaction of risk premium with decreased risk tolerance or other investment considerations like flight to safety or liquidity requirements. We identify the difference between the correlations of the idiosyncratic volatility estimators used by other studies and the true risk metric the mean-reverting volatility as the likely cause for the mixed evidence produced by other studies. Our results are robust with respect to liquidity, momentum, return reversals, unadjusted price, liquidity, credit quality, omitted factors, and hold at daily frequency.

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