Truncated maximum likelihood, goodness of fit tests and tail analysis
AbstractWe propose a new method of tail analysis for data featuring a high degree of leptokurtosis. Heavy tails can typically be found in financial series, like for example, the stock returns or durations between arrivals of trades. In our framework, the shape of tails can be assessed by fitting some selected pseudo-models to extremely valued observations in the sample. A global examination of the density tails is performed using a sequence of truncated pseudo-maximum likelihood estimators, called the tail parameter function (t.p.f.). In practice, data often exhibit local irregularities in the tail behaviour. To detect and approximate these patterns we introduce the local parameter function (l.p.f.), a method of tail analysis involving a selected interval of extreme observations. An immediate extension of the pseudo-value based approach to density analysis yields a new procedure for testing the goodness of fit. We also develop a new nonparametric estimator of the density function. The method is applied to unequally spaced high frequency data. We study an intradaily series of returns on the Alcatel stock, one among the most frequently traded stocks on the Paris Stock Exchange. --
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Bibliographic InfoPaper provided by Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes in its series SFB 373 Discussion Papers with number 1998,36.
Date of creation: 1998
Date of revision:
Goodness of fit test; tail analysis; truncated maximum likelihood; kernel; Hill estimator;
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- Suárez-García, Pablo & Gómez-Ullate, David, 2013. "Scaling, stability and distribution of the high-frequency returns of the Ibex35 index," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(6), pages 1409-1417.
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