A new semiparametric estimator for an empirical asset pricing model with general nonparametric risk-return tradeoff and a GARCH process for the underlying volatility is introduced. The estimator does not rely on any initial parametric estimator of the conditional mean function, and this feature...

We extend the fractionally integrated exponential GARCH (FIEGARCH) model for daily stock return data with long memory in return volatility of Bollerslev and Mikkelsen (1996) by introducing a possible volatility-in-mean effect. To avoid that the long memory property of volatility carries over to...

We study the forecasting of future realized volatility in the stock, bond, and foreign exchange markets, as well as the continuous sample path and jump components of this, from variables in the information set, including implied volatility backed out from option prices. Recent nonparametric...

We consider the relation between the volatility implied in an option's price and the subsequently realized volatility. Earlier studies on stock index options have found biases and inefficiencies in implied volatility as a forecast of future volatility. More recently, Christensen and Prabhala...

In analyzing the relation between implied and realized volatility, researchers confront samples that have a high degree of overlap, which quot;telescopesquot; as option maturities are reached. With volatility samples of this nature, we show that the regression coefficients are disperse even in...

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This paper considers estimation of a pure equilibrium search model in which all heterogeneity is endogenous and due to information asymmetries, and of variations that allow better fits to the data. Measurement error and heterogeneity in the productivity levels of firms. The model is fit to a...