Download Statistical Tools for Finance and Insurance, First Edition by Pavel Čížek, Wolfgang Karl Härdle, Rafał Weron, Editors PDF

By Pavel Čížek, Wolfgang Karl Härdle, Rafał Weron, Editors

Written in an available and fascinating type, this self-instructional publication makes an exceptional use of in depth examples and entire motives. The digital version, permitting the reader to run, regulate, and improve all quantlets instantaneous, could be downloaded for free of charge through the hooked up license registration card.

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Additional resources for Statistical Tools for Finance and Insurance, First Edition

Example text

We present here the results obtained for Frank copula. 4 for pairs of stock indices. 3 is that one pair, namely USD/PLN and EUR/USD, shows negative dependence, whereas the other two show positive dependence. This is particularly important for the entities that are exposed to exchange rate risk and they want to decrease it by appropriate management of assets and liabilities. There is positive extreme dependence between all stock indices. As could have been expected, there is strong dependence between indices of the WSE and much lower between WSE and the other exchanges, with weaker dependence between WSE and NYSE than between WSE and large European exchanges.

2: The estimates of the parameters of GEV distributions, for the exchange rates. xpl The analysis of the results for the exchange rates leads to the following conclusions. Three different distributions were obtained, for USD/PLN – a Gumbel distribution, for EUR/PLN – a Fr´echet distribution, for EUR/USD – a Weibull distribution. This suggests very different behavior of underlying observations. The location and scale parameters are almost the same. The scale parameters are considerably lower for the exchange rates than for the stock indices.

Simple consistent estimators of stable distribution parameters, Communications in Statistics – Simulations 15: 1109–1136. McCulloch, J. H. (1996). Financial applications of stable distributions, in G. S. Maddala, C. R. ), Handbook of Statistics, Vol. 14, Elsevier, pp. 393–425. McCulloch, J. H. (1997). Measuring tail thickness to estimate the stable index α: A critique, Journal of Business & Economic Statistics 15: 74–81. , and Chenyao, D. (1999). Computing the probability density function of the stable Paretian distribution, Mathematical and Computer Modelling 29: 235–240.

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