All in the family: nesting symmetric and asymmetric GARCH models

Article Abstract:

A new parametric class of generalized autoregressive heteroskedasticity (GARCH) models based on nested versions of existing symmetric and asymmetric GARCH models is introduced. The nesting is achieved by 'treating the variance equation as a law of motion for the Box-Cox transformation of the conditional standard deviation.' The models, which differ from each other in their treatment of asymmetry and in their transformation of the conditional standard deviation, were estimated using daily US stock returns and showed 'a shift in the news input curve.'

Analysis, Analysis of variance, Heteroscedasticity, Standard deviations, Standard deviation

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No news is good news: an asymmetric model of changing volatility in stock returns

Article Abstract:

A quadratic generalized autoregressive conditionally heteroskedastic model describing volatility feedback effects of stocks is analyzed. The model tests the hypothesis that a rise in stock market volatility increases required stock returns and reduces stock prices. The analysis focuses on US stocks covering the period from 1926-88. Results show that volatility feedback has minimal return impact but exhibit vital influence during high volatility periods.

Prices and rates, Stock-exchange, Stock exchanges, Securities, Securities prices

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Efficient tests of stock return predictability

Article Abstract:

Development of bonferroni test to ascertain the predictability of stock returns and dividend yields is discussed.

United States, Product information, Forecasts, trends, outlooks, Dividends, Dividend Policy, Capital Management-Stock Repurchase, Forecasts and trends, Testing, Market trend/market analysis, Return on investment, Stock redemption, Rate of return, Company dividends

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