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The stochastic volatility in mean model
Koopman, Siem Jan; Hol Uspensky, Eugenie - 2000
In this paper we present an exact maximum likelihood treatment forthe estimation of a Stochastic Volatility in Mean(SVM) model based on Monte Carlo simulation methods. The SVM modelincorporates the unobserved volatility as anexplanatory variable in the mean equation. The same extension...
Persistent link: https://www.econbiz.de/10011303314
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Stock index volatility forecasting with high frequency data
Hol Uspensky, Eugenie; Koopman, Siem Jan - 2002
for longer horizon volatility forecasts. In this paper we explore the forecasting value of these high fre-quency series in … Volatility (SV) and Generalised Autoregressive Conditional Heteroskedasticity (GARCH) models which are both extended to include … the intraday volatility measure. For forecasting horizons ranging from one day to one week the most accurate out …
Persistent link: https://www.econbiz.de/10011326944
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Forecasting the variability of stock index returns with stochastic volatility models and implied volatility
Hol Uspensky, Eugenie; Koopman, Siem Jan - 2000
-of-sample, for daily returns on the Standard & Poor's100 index. Similar studies have been undertaken with GARCH models where … returns and intradaily squared returns for forecasting horizons rangingfrom 1 to 10 days. For the daily squared returns we …
Persistent link: https://www.econbiz.de/10011304384