Statistical Properties of Daily Returns: Evidence From European Stock Markets

Corhay, Albert; Rad, Alireza Tourani

doi:10.1111/j.1468-5957.1994.tb00318.x

Cited by 73 publications

(45 citation statements)

References 17 publications

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“…Corhay and Rad (1994) find that GARCH (1, 1) model fits well to the stock market data from France, Germany, Netherlands and UK with the exception of Italy. Hsieh (1989) show that GARCH (1, 1) capture the stochastic dependencies of time series data well.…”

Section: Introductionmentioning

confidence: 85%

Stock Market Volatility in Saudi Arabia: An Application of Univariate GARCH Model

Kalyanaraman¹

2014

ASS

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Study of stock market volatility has been the focus of financial economics. Modelling stock market volatility has great contributions to make in the areas of portfolio management, asset allocation, risk management, etc. We estimate the conditional volatility of Saudi stock market by applying AR (1)-GARCH (1, 1) model to the daily stock returns data spanning from August 1, 2004 to October 31, 2013. We show that a linear symmetric GARCH (1, 1) model is adequate to estimate the volatility of the stock market of the country. We find that Saudi stock market returns are characterised by volatility clustering and follow a non-normal distribution. Saudi stock market returns show a time varying volatility, show persistence and are predictable. Past volatility impacts the current period volatility and past returns play a role in determining the current period return. Saudi stock market is nervous in its reactions to market fluctuations. This finding of the study offer important input into the decisions relating to asset allocation and risk management strategies of investors and treasury managers in Saudi stock market.

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Section: Introductionmentioning

confidence: 85%

Stock Market Volatility in Saudi Arabia: An Application of Univariate GARCH Model

Kalyanaraman¹

2014

ASS

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“…More recently, Corhay and Rad (1994) and Theodossiou and Lee (1995) investigated the behavior of stock market volatility and its relationship to expected returns for major European stock markets. Both studies report the existence of significant conditional heteroskedasticity in stock price behavior.…”

Section: Literature Reviewmentioning

confidence: 99%

The day of the week effect on stock market volatility

2001

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This study tests the presence of the day of the week effect on stock market volatility by using the S&P 500 market index during the period of January 1973 and October 1997. The findings show that the day of the week effect is present in both volatility and return equations. While the highest and lowest returns are observed on Wednesday and Monday, the highest and the lowest volatility are observed on Friday and Wednesday, respectively. Further investigation of sub-periods reinforces our findings that the volatility pattern across the days of the week is statistically different. (JEL G10, G12, C22)

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“…Otherwise, the parameter estimates may be ine cient and any inferences based upon them will be potentially misleading. Other researchers who came to the same conclusion include Akgiray (1989), Connolly (1989), Corhay and Rad (1994), and Brockett et al (1999).…”

Section: Introductionmentioning

confidence: 89%

Stock market reaction to food recalls: a GARCH application

Wang¹,

Salin²,

Hooker³

et al. 2002

Applied Economics Letters

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How food recalls due to bacterial contamination a ect the stock prices of two companies are examined using a version of the ®nancial market model that accounts for Generalized Autoregressive Conditional Heteroscedasticity (GARCH) e ects. GARCH methodology was necessary to uncover the time-varying volatility in the series and it contributed to more e cient econometric results. The initial food recall undertaken by the company is associated with reduced mean returns and higher volatility of the companies studied. Repeated recalls by the same company are not associated with strong reactions. Volatility spillovers across ®rms suggest potential industry-wide repercussions from bacterial contamination incidents.

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Statistical Properties of Daily Returns: Evidence From European Stock Markets

Cited by 73 publications

References 17 publications

Stock Market Volatility in Saudi Arabia: An Application of Univariate GARCH Model

Stock Market Volatility in Saudi Arabia: An Application of Univariate GARCH Model

The day of the week effect on stock market volatility

Stock market reaction to food recalls: a GARCH application

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