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Recent research reveals that hedge fund returns exhibit a range of different,possibly non-linear pay-off patterns. It is difficult to qualify all these patternssimultaneously as being rational in a traditional framework for optimal financial decisionmaking. In this paper we present a simple...
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We propose a new class of observation-driven time-varying parameter models for dynamic volatilities and correlations to handle time series from heavy-tailed distributions. The model adopts generalized autoregressive score dynamics to obtain a time-varying covariance matrix of the multivariate...
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We advocate the use of absolute moment ratio statistics in conjunctionwith standard variance ratio statistics in order to disentangle lineardependence, non-linear dependence, and leptokurtosis in financial timeseries. Both statistics are computed for multiple return horizonssimultaneously, and...
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Using a limiting approach to portfolio credit risk, we obtain analyticexpressions for the tail behavior of the distribution of credit losses. We showthat in many cases of practical interest the distribution of these losses haspolynomial ('fat') rather than exponential ('thin') tails. Our...
Persistent link: https://www.econbiz.de/10011316891
Using US data from June 1984 to July 1999, we show that the impact of firm-specificcharacteristics like size and book-to-price on future excess stock returns varies considerably overtime. The impact can be either positive or negative at different times. This time variation ispartially...
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We develop a new model for the multivariate covariance matrix dynamics based on daily return observations and daily realized covariance matrix kernels based on intraday data. Both types of data may be fat-tailed. We account for this by assuming a matrix-F distribution for the realized kernels,...
Persistent link: https://www.econbiz.de/10010364103