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A class of semiparametric fractional autoregressive GARCH models (SEMIFAR-GARCH), which includes deterministic trends, difference stationarity and stationarity with short-and long-range dependence, and heteroskedastic model errors, is very powerful for modelling financial time series. This paper...
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this markets. Numerical evaluations of varinace, volatility, covarinace and correlations swaps with semi-Markov volatility … are presented as well. The novelty of the paper lies in pricing of volatility swaps in closed form, and pricing of …
Persistent link: https://www.econbiz.de/10013106136
To capture mean and variance asymmetries and time-varying volatility in financial time series, we generalize the … threshold stochastic volatility (THSV) model and incorporate a heavy-tailed error distribution. Unlike existing stochastic … volatility models, this model simultaneously accounts for uncertainty in the unobserved threshold value and in the time …
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effects, i.e., it is possible that the structure of the volatility surface changes without a change in the volatility level … state, I show that this superior performance is directly linked to a third volatility factor which is unrelated to the … volatility level. The second chapter studies the price of the smile, which is defined as the premia for individual option risk …
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Stochastic Volatility in Financial Markets presents advanced topics in financial econometrics and theoretical finance … changes: the occurrence of sudden and persistent changes of financial markets volatility. This phenomenon, technically termed … `stochastic volatility', or `conditional heteroskedasticity', has been well known for at least 20 years; in this part, further …
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