capturing interest rate risk. The so-called Stochastic Volatility Nelson-Siegel (SVNS) model allows for stochastic volatility in … evidence for time-varying volatility in the yield factors. This is mostly true for the level and slope volatility revealing … also the highest persistence. It turns out that the inclusion of stochastic volatility improves the model's goodness …

In this paper, we study the dynamic interdependencies between high-frequency volatility, liquidity demand as well as …. Liquidity is causal for future volatility but not vice versa. Furthermore, trade sizes are negatively driven by past trading …

direction of company-specific news. Information-implied reactions in returns, volatility as well as liquidity demand and supply … London Stock Exchange (LSE), we find market-wide robust news-dependent responses in volatility and trading volume. However …

direction of company-specific news. Information-implied reactions in returns, volatility as well as liquidity demand and supply … London Stock Exchange (LSE), we find market-wide robust news-dependent responses in volatility and trading volume. However …

does not require the specification and estimation of the economic agent's information flows or the identification and … estimation of the structural parameters and the noninvertible roots. Moreover, the proposed test statistic uses all lags in the …

-step state-space estimation approach the four-factor model produces accurate forecasts and outperforms competitor models across …

inference compared to frequentist estimation techniques, and model uncertainty by combining forecasts from individual models …

outperforms the other models in model estimation and daily out-of-sample volatility forecasting of the two indices. This study is … for forecasting the volatility of both the TASI and the TIPISI in the context of petrochemical industries, as this model …