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Statistical Inference from Financial Data with Mathematica

Jan Hurt
Organization: Charles University of Prague

Wolfram Technology Conference 2012
Conference location

Champaign, Illinois, USA

In the contribution financial data (mainly profits/losses, P&L) are analyzed using both new built-in statistical functions and own procedures. Selected parametric P&L distributions that seem to be suitable for modelling but are not easily analytically tractable are investigated. It is shown that in many cases the mixture of three symmetric distributions is sufficiently flexible to fit the data successfully. For the estimation purposes the Expectation-Maximization algorithm (EM algorithm) is used. The results and efficiency is compared with the built-in EstimatedDistribution function. The statistical tests include tests of independence and tests for symmetry, among others. The influence on risk measures is also studied.

*Wolfram Technology

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WTC2012_Jan_Hurt_Statistical_Inference_SlideShow.nb (1.2 MB) - Mathematica Notebook
WTC2012_Jan_Hurt_Statistical_Inference_Working.nb (1.2 MB) - Mathematica Notebook