The volatility clustering frequently observed in financial/economic time series is often ascribed to GARCH and/or stochastic volatility models. This paper demonstrates the usefulness of reconceptualizing the usual definition of conditional heteroscedasticity as the (h = 1) special case of h-step-ahead conditional heteroscedasticity, where the conditional volatility in period t depends on observ...

Modeling the dependency between stock market returns is a difficult task when returns follow a complicated dynamics. It is not easy to specify the multivariate distribution relating two or more return series. In this paper, a methodology based on fitting ARIMA, GARCH and ARMA-GARCH models and copula functions is applied. In such methodology, the dependency parameter can easily be rendered condi...

This paper presents a model for asset returns incorporating both stochastic volatility and jump e ects. The return process is driven by two types of randomness: small random shocks and large jumps. The stochastic volatility process is a ected by both types of randomness in returns. Speci cally, in the absence of large jumps, volatility is driven by the small random shocks in returns through a G...

In this paper the realized daily variance is obtained from intraday transaction prices of the S&P 500 cash index over the period from January 1993 to December 2004. When constructing realized daily variance, market microstructure noise is taken into account using a technique proposed by Zhang, Mykland and Aı̈t-Sahalia (2005). The time series properties of realized daily variance are compared wit...

This study introduces a novel index based on expectations concordance for explaining stock-price volatility when events that are each somewhat unique cause unforeseeable change and Knightian uncertainty in the process driving outcomes. Expectations measures degree to which KU associated with directionally similar of future returns. Narrative analytics daily news reports allow assessment bullish...

this paper empirically investigates the exchange rate effects of iranian rial against dollar (rial vs.us) on stock prices in iran. the sample period for the study has been taken from march 20, 2004 to march 20, 2010 using daily nominal exchange rate of rial /us and daily closing values of tehran stock exchange. generalized autoregressive conditional heteroskedasticity (garch) model has been use...

This paper empirically investigates the exchange rate effects of Iranian Rial against Dollar (Rial vs.US) on stock prices in Iran. The sample period for the study has been taken from March 20, 2004 to March 20, 2010 using daily nominal exchange rate of Rial /us and daily closing values of Tehran Stock Exchange. Generalized Autoregressive Conditional Heteroskedasticity (GARCH) model has been use...

We examine the performance of volatility models that incorporate features such as long (short) memory, regime-switching and multifractality along with two competing distributional assumptions of the error component, i.e. Normal vs Student-t. Our precise contribution is twofold. First, we introduce a new model to the family of Markov-Switching Multifractal models of asset returns (MSM), namely, ...

This paper tests pair-wise causal relationships between uncertainty, returns and investment using unbalanced panel data of the 13 insurance companies listed in the KSE for the period from 1996 to 2008. Volatility of returns from the daily stock was measured using the GARCH (p, q) for appropriate values of p and q. The study applied panel data models in the lines of common constants, fixed effec...

the purpose of this study is estimation of daily value at risk (var) for total index of tehran stock exchange using parametric, nonparametric and semi-parametric approaches. conditional and unconditional coverage backtesting are used for evaluating the accuracy of calculated var and also to compare the performance of mentioned approaches. in most cases, based on backtesting statistics results, ...