Asymmetry and Leverage in Realized Volatility

Asymmetry and Leverage in Realized Volatility

Asymmetry and Leverage in Conditional Volatility Models

The three most popular univariate conditional volatility models are the generalized autoregressive conditional heteroskedasticity (GARCH) model of Engle (1982) and Bollerslev (1986), the GJR (or threshold GARCH) model of Glosten, Jagannathan and Runkle (1992), and the exponential GARCH (or EGARCH) model of Nelson (1990, 1991). The underlying stochastic specification to obtain GARCH was demonstr...

Realized stochastic volatility with leverage and long memory

! ! The daily return and the realized volatility are simultaneously modeled in the stochastic volatility model with leverage and long memory. In addition to the stochastic volatility model with leverage for the daily returns, ARFIMA process is jointly considered for the realized volatilities. Using a state space representation of the model, we estimate parameters by Markov chain Monte Carlo met...

Asymmetry and Leverage in Stochastic Volatility Models: An Exposition

The accurate specification and modelling of risk are integral to optimal portfolio and risk management. In this context, a wide variety of conditional and stochastic volatility models has been used to estimate latent volatility (or risk). In both the conditional and stochastic volatility literature, there has been some confusion between the definitions of asymmetry and leverage. This paper exam...

Realized Stochastic Volatility with General Asymmetry and Long Memory∗

The paper develops a novel realized stochastic volatility model of asset returns and realized volatility that incorporates general asymmetry and long memory (hereafter the RSV-GALMmodel). The contribution of the paper ties in with Robert Basmann’s seminal work in terms of the estimation of highly non-linear model specifications (“Causality tests and observationally equivalent representations of...