
doi: 10.1111/jtsa.12419
An EGARCH‐M model, in which the logarithm of scale is driven by the score of the conditional distribution, is shown to be theoretically tractable as well as practically useful. A two‐component extension makes it possible to distinguish between the short‐ and long‐run effects of returns on volatility, and the resulting short‐ and long‐run volatility components are then allowed to have different effects on returns, with the long‐run component yielding the equity risk premium. The EGARCH formulation allows for more flexibility in the asymmetry of the volatility response (leverage) than standard GARCH models and suggests that, for weekly observations on two major stock market indices, the short‐term response is close to being anti‐symmetric.
Economic time series analysis, Time series, auto-correlation, regression, etc. in statistics (GARCH), ARCH-in-mean, dynamic conditional score (DCS) model, equity risk premium, Time series analysis of dynamical systems, leverage, two-component model, Statistical methods; risk measures
Economic time series analysis, Time series, auto-correlation, regression, etc. in statistics (GARCH), ARCH-in-mean, dynamic conditional score (DCS) model, equity risk premium, Time series analysis of dynamical systems, leverage, two-component model, Statistical methods; risk measures
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