We compare more than 1000 different volatility models in terms of their fit to the historical ISE-100 Index data and … for modeling the ISE-100 return volatility. The t-distribution seems to characterize the distribution of the heavy tailed … model to the historical ISE-100 return data indicates that the return volatility reacts to bad news 24% more than they react …

Rogers-Satchell (RS) measure is an efficient volatility measure. This paper proposes quantile RS (QRS) measure to … on Standard and Poor 500 and Dow Jones Industrial Average indices show that volatility estimates using QRS measures …-of-sample forecast. For return models, the constant mean structure with Student-t errors and QRS volatility estimates provides the best …

Forecasting volatility models typically rely on either daily or high frequency (HF) data and the choice between these … two categories is not obvious. In particular, the latter allows to treat volatility as observable but they suffer from … these two family forecasting-volatility models, comparing their performance (in terms of Value at Risk, VaR) under the …

In this study, we aim to analyze the relation between return and volatility in different types of exchange-traded funds … advantages to each other: Toda-Yamamoto (1995); bootstrap based Hatemi-J (2005); volatility spillover, which allows investigating … results obtained from our analyses show that a negative relationship between return and volatility is valid for most ETF types …

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 …

There is evidence that volatility forecasting models that use intraday data provide better forecast accuracy as … fills this gap in the literature and extends previous studies on forecasting stock market volatility in several important …, we use forecast horizons ranging from 1 day to 6 months. Third, we evaluate the precision of volatility forecast provided …

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 …

This paper investigates the predictive ability of international volatility risk for the daily aggregate Chinese stock … market returns. We employ the innovations in implied volatility indices of seven major international markets as our … international volatility risk proxies. We find that international volatility risks are negatively associated with contemporaneous …