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Pricing kernels implicit in option prices play a key role in assessing the risk aversion over equity returns. We deal with nonparametric estimation of the pricing kernel (Empirical Pricing Kernel) given by the ratio of the risk-neutral density estimator and the subjective density estimator. The...
Persistent link: https://www.econbiz.de/10003952791
In der Literatur wurden verschiedene parametrische Modelle zur Analyse der Heteroskedastie in Zeitreihen von Finanzmarktdaten entwickelt. Eine Möglichkeit, die bedingte Volatilität nichtparametrisch zu erfassen, ist die Kernschätzung von bedingten Quantilen. In diesem Aufsatz werden einige...
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In diesem Aufsatz wird die nichtparametrische Autoregression auf die Prognose von Quantilen angewendet. Verfahren der Kernregression werden benutzt, um zu autoregressiven Quantiisschätzern zu gelangen. Da die üblichen Maße zur Beurteilung der Prognose, wie etwa der mittlere quadratische...
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Equity basket correlation is an important risk factor. It characterizes the strength of linear dependence between assets and thus measures the degree of portfolio diversification. It can be estimated both under the physical measure from return series, and under the risk neutral measure from...
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For over a decade, nonparametric modelling has been successfully applied to study nonlinear structures in financial time series. It is well known that the usual nonparametric models often have less than satisfactory performance when dealing with more than one lag. When the mean has an additive...
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A major application of rescaled adjusted range analysis (RS analysis) is the study of price fluctuations in financial markets. There, the value of the Hurst constant, H, in a time series may be interpreted as an indicator of the irregularity of the price of a commodity, currency or similar...
Persistent link: https://www.econbiz.de/10009581110
Let a process SI , ... ,ST obey the conditionally heteroskedastic equation St = Vt Et whcrc Et is a random noise and Vt is the volatility coefficient which in turn obeys an autoregression type equation log v t = w + a S t- l + nt with an additional noise nt. We consider the situation which the...
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