The benefit of information reduction for trading strategies

Schittenkopf, Christian and Tino, Peter and Dorffner, Georg (2000) The benefit of information reduction for trading strategies. Report Series SFB "Adaptive Information Systems and Modelling in Economics and Management Science", 45. SFB Adaptive Information Systems and Modelling in Economics and Management Science, WU Vienna University of Economics and Business, Vienna.


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Motivated by previous findings that discretization of financial time series can effectively filter the data and reduce the noise, this experimental study compares the trading performance of predictive models based on different modelling paradigms in a realistic setting. Different methods ranging from real-valued time series models to predictive models on a symbolic level are applied to predict the daily change in volatility of two major stock indices. The predicted volatility changes are interpreted as trading signals for buying or selling a straddle portfolio on the underlying stock index. Profits realized by this trading strategy are tested for statistical significance taking into account transaction costs. The results indicate that symbolic information processing is a promising approach to financial prediction tasks undermining the hypothesis of efficient captial markets. (author's abstract)

Item Type: Paper
Keywords: Volatilität / Optionspreis / Information / Kapitalmarkteffizienz
Divisions: Departments > Informationsverarbeitung u Prozessmanag. > Produktionsmanagement > Taudes
Departments > Finance, Accounting and Statistics > Statistics and Mathematics
Departments > Marketing > Service Marketing und Tourismus
Departments > Informationsverarbeitung u Prozessmanag. > Informationswirtschaft
Depositing User: Repository Administrator
Date Deposited: 08 Mar 2002 10:40
Last Modified: 22 Oct 2019 00:41


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