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Titlebook: Genetic Algorithms and Genetic Programming in Computational Finance; Shu-Heng Chen Book 2002 Springer Science+Business Media New York 2002

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https://doi.org/10.1007/978-981-19-3593-0asting. The novelty of FGP-2 is that, as a forecasting tool, it provides the user with a handle for tuning the precision against the rate of missing opportunities. This allows the user to pick investment opportunities with greater confidence.
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Wolfgang Dunkel,Margit Weihrich JPY/USD markets. GARCH(1,1) models serve used as a benchmark. While the GARCH model outperforms the genetic program at short horizons using the mean-squared-error (MSE) criterion, the genetic program often outperforms the GARCH at longer horizons and consistently returns lower mean absolute forecast errors (MAE).
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Eddie for Financial Forecastingasting. The novelty of FGP-2 is that, as a forecasting tool, it provides the user with a handle for tuning the precision against the rate of missing opportunities. This allows the user to pick investment opportunities with greater confidence.
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Forecasting Market Indices Using Evolutionary Automatic Programming trading rules for market indices. A number of markets are analysed; these are the UK’s FTSE, Japan’s Nikkei, and the German DAX. The preliminary findings indicate that the methodology has much potential.
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Using a Genetic Program to Predict Exchange Rate Volatility JPY/USD markets. GARCH(1,1) models serve used as a benchmark. While the GARCH model outperforms the genetic program at short horizons using the mean-squared-error (MSE) criterion, the genetic program often outperforms the GARCH at longer horizons and consistently returns lower mean absolute forecast errors (MAE).
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https://doi.org/10.1007/978-1-4615-0835-9Arbitrage; Finance; Sage; Simulation; agents; algorithms; automatic programming; cash flow; genetic programm
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Customer Relationship Management applications, such as forecasting, trading, and portfolio management. We then trace the recent extensions to cash flow management, option pricing, volatility forecasting, and arbitrage. The direction then turns to agent-based computational finance, a bottom-up approach to the study of financial mar
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