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[HBK10a] Risk reduction using Wavelets-PCR models: Application to Application to market dataConférence Internationale avec comité de lecture : August 2010, pp.398,
motcle:
Résumé:
In this paper, we set out a hybrid data analysis method based on the
combination of wavelet techniques and Principal Components Regression (PCR).
Our purpose is to study the dynamics of the stock returns within the French Stock
Market. Wavelet-based thresholding techniques are applied to the stock price series
in order to obtain a set of explanatory variables that are practically noise-free.
The PCR is then carried out on the new set of regressors. The empirical results
show that the suggested method allows extraction and interpretation of the factors
that influence the stock price changes. Moreover, the Wavelet-PCR improves the
explanatory power of the regression model as well as its forecasting quality.
Equipe:
msdma
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