of long-term stock market volatility. When long-term volatility is high, stock returns are more sensitive to news, and …-linear present value framework with a two-component volatility model for the conditional variance of cash flow news and allowing for … volatility feedback. In our model, innovations to the long-term volatility component are the most important driver of discount …

Where does new volatility enter the volatility of securities listed in many countries? While literature has focused on … where information enters the price, I develop a framework to study how each market's volatility contributes to the permanent … volatility of the Asset. I build a VECM with an Autoregressive Stochastic Volatility (ASV) framework estimated using the MCMC …

This paper examines the role of information release in explaining return volatility in Australian equities. The study … return volatility. Analyst price targets (PTR) and Morningstar stock star ratings (MSR) were proxies for private information … provide insights into how information disclosures instigate varied volatility within the entire market and across sectors. The …

) The Volatility Puzzle. We offer resolutions of those objections within the rational finance. We do not claim that those …

build a credible counterfactual. The method is used to evaluate the effectiveness of volatility auctions using intraday data … results indicate that the volatility auction mitigates the volatility of the asset, but its effect on liquidity and trading …

predicting stock volatility. This is motivated by the microstructure literature that focuses on the mechanics of price formation … determinant in the volatility estimation for all sample stocks as shown by the panel VAR estimation, which allows us to examine … simultaneously the dynamics of price impact on all sample stocks. Furthermore, when we augment traditional volatility models with the …

We analyze the impact of sentiment and attention variables on volatility by using a novel and extensive dataset that … for realized volatility when controlling for a wide range of economic and financial predictors. Using a penalized … improve volatility forecasts, although the improvements are of relatively small magnitude from an economic point of view …

in the respective literature (OLS, GARCH family) are applied in order to conclude that the TGARCH asymmetry model is the …

This article analyzed the presence of long memory in volatility in 5 Asian equity indices namely SENSEX, CNIA, NIKKEI … ARFIMA-FIGARCH model and ARFIMA-APARCH model and compared them with GARCH (1,1) model and APARACH(1,1) in terms of in …-sample forecast accuracy. The results confirmed the presence of long memory in both the return and volatility series for all the five …