forecasting technique with respect to various volatility estimators. The methodology of volatility estimation included Close … variations in returns. Forecasting volatility has been a stimulating problem in the financial systems. This study examined the …, Garman-Klass, Parkinson, Roger-Satchell, and Yang-Zhang methods and forecasting was done through the ARIMA technique. The …

forecasting technique with respect to various volatility estimators. The methodology of volatility estimation includes Close … variations in returns. Forecasting volatility had been a stimulating problem in the financial systems. The study examined the …, Garman-Klass, Parkinson, Roger-Satchell and Yang-Zhang methods and forecasting is done through ARIMA technique. The study …

inputs within the investment process. It is this estimation step which is ultimately key in transforming raw financial data … into useful investment information. Therefore, having a flexible and robust estimation process is of crucial importance to … different forms of time-conditioning and market state-conditioning into any estimation procedure. This framework allows one to …

conditional quantile estimation. Specifically, we model the conditional standard deviation as a realized GARCH model and employ … proposed dynamic quantile models. We devise a two-step estimation procedure to estimate the conditional quantile parameters …. The first step applies a quasi-maximum likelihood estimation procedure, with the realized volatility as a proxy for the …

This paper introduces a unified multivariate overnight GARCH-Ito model for volatility matrix estimation and prediction … weighted least squares estimation procedure for estimating model parameters with open-to-close high-frequency and close … the proposed estimation and prediction methods.The empirical analysis is carried out to compare the performance of the …