This paper considers spot variance path estimation from datasets of intraday high frequency asset prices in the … microstructure noise has an adverse effect on both spot variance estimation and jump detection. In our approach we can analyze high …

estimation of the state vector and of the time-varying parameters. We use this method to study the time-varying relationship …

estimation of the state vector and of the time-varying parameters. We use this method to study the timevarying relationship …

In this paper we discuss univariate and multivariate statistical properties of volatility with the aim of understanding … stock's volatilities and the volatility clustering. Volatility clustering is related to the memory property of the … volatility time-series and therefore to its predictability. Our results show that there exists a relationship between the level …

strongest during bad economic times. In line with this evidence, we document that stock volatility predictability is also state …-series volatility models, in this paper we comprehensively examine how volatility forecastability varies across bull and bear states of … the stock market. We find that the volatility forecast horizon is substantially longer when the market is in a bear state …

Modeling and forecasting volatility of capital markets has been important area of inquiry and research in financial … economics with the recognition of time-varying volatility, volatility clusturing, and asymmetric response of volatility to … investment in Nepalese stock market, it is important to understand the pattern of stock market volatility. In the paper, the …