preferable. An extension of the ARMA model is proposed that takes into account the so-called leverage effect. Finally, the …Nowcasting volatility of financial time series appears difficult with classical volatility models. This paper proposes … a simple model, based on an ARMA representation of the log-transformed squared returns, that allows to estimate current …

autoregressive conditional heteroskedasticity-autoregressive moving average (EGARCH-ARMA) for the defined asset classes. Daily spot … that the EGARCH-ARMA model is superior to the ARMA model in forecasting market returns. Several diagnostic tests were … allocation framework where the empirical results are equity-like returns with volatility, Sharpe ratio and drawdown. In this …

In this paper, we introduce a new approach for volatility modeling in discrete and continuous time. We follow the … stochastic volatility literature by assuming that the variance is a function of a state variable. However, instead of assuming … variance and squared return processes are ARMA and, hence, simple for forecasting and inference purposes; (iv) more importantly …

Chapter written for the Handbook of Volatility Models and their Applications, edited by Luc Bauwens, Christian Hafner …, and Sébastien Laurent, forthcoming in 2012 (John Wiley & sons). This chapter presents an introductory review of volatility …

Estimation of log-GARCH models via the ARMA representation is attractive because it enables a vast amount of already … established results in the ARMA literature. We propose an exponential Chi-squared QMLE for log-GARCH models via the ARMA …