Financial Risk and Volatility Modeling

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• KAMİL YILMAZ

We provide a simple and intuitive measure of interdependence of asset returns and/or volatilities. In particular, we formulate and examine precise and separate measures of return spillovers and volatility spillovers. Our framework facilitates study of both non‐crisis and crisis episodes, including trends and bursts in…

• KAMİL YILMAZ

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• ŞABAN NAZLIOĞLU

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The Mann-Kendall test, used to detect a trend in a time series, yields an incorrect (too large) rejection rate when applied to an autocorrelated series with no trend. Prewhitening corrects this situation, but reduces the power of the test when a trend exists. A simulation study is performed to determine when prewhiten…

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• AHMET ŞENSOY

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• SİBEL ÇAPRAZ

We investigate the predictive performance of various classes of value-at-risk (VaR) models in several dimensions—unfiltered versus filtered VaR models, parametric versus nonparametric distributions, conventional versus extreme value distributions, and quantile regression versus inverting the conditional distribution f…

• VAHAP BURAK SALTOĞLU

Abstract: We characterize equity return volatility connectedness in the network of major American and European financial institutions, 2004-2014. Our methods enable precise characterization of the timing and evolution of key aspects of the financial crisis. First, we find that during 2007-2008 the direction of connect…

We show that there is an asymmetry in the predictability of the volatilities of large versus small firms. Using both univariate and multivariate ARMA–GARCH-M parameterizations, we find that volatility surprises to large market value firms are important to the future dynamics of their own returns as well as the returns…