Neural Networks to Predict Financial Time Series in a Minority Game Context
AbstractIn this paper we consider financial time series from U.S. Fixed Income Market, S&P500, Exchange Market and Oil Market. It is well known that financial time series reveal some anomalies as regards the Efficient Market Hypotesis and some scaling behavior is evident such as fat tails and clustered volatility. This suggests to consider financial time serie as "pseudo"-random time series. For this kind of time series the power of prediction of neural networks has been shown to be appreciable. We first consider the financial time serie from the Minority Game point of view and than we apply a neural network with learning algorithm in order to analyze its prediction power. We show that Fixed Income Market presents many differences from other markets in terms of predictability as a measure of market efficiency.
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Bibliographic InfoPaper provided by Dipartimento di Scienze Economiche, Matematiche e Statistiche, Universita' di Foggia in its series Quaderni DSEMS with number 14-2005.
Date of creation: Jun 2005
Date of revision:
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More information through EDIRC
Minority Game; Learning Algorithms; Neural Networks; Financial Time Series; Efficient Market Hypotesis;
Find related papers by JEL classification:
- C45 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Neural Networks and Related Topics
- C70 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - General
- C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models &bull Diffusion Processes
- G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
This paper has been announced in the following NEP Reports:
- NEP-ALL-2005-06-14 (All new papers)
- NEP-CMP-2005-06-14 (Computational Economics)
- NEP-ETS-2005-06-14 (Econometric Time Series)
- NEP-FIN-2005-06-14 (Finance)
- NEP-GTH-2005-06-14 (Game Theory)
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
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For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Luca Grilli).
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