Predicting the Stock Market
نویسنده
چکیده
This paper presents a tuturial introduction to predictions of stock time series. The various approaches of technical and fundamental analysis is presented and the prediction problem is formulated as a special case of inductive learning. The problems with performance evaluation of near-random-walk processes are illustrated with examples together with guidelines for avoiding the risk of data-snooping. The connections to concepts like "the bias/variance dilemma", overtraining and model complexity are further covered. Existing benchmarks and testing metrics are surveyed and some new measures are introduced.
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Stock Price Forecasting
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