The Predictive Power of Price Patterns

  title={The Predictive Power of Price Patterns},
  author={Gunduz Caginalp and Henry Laurent},
  journal={FEN: Behavioral Finance (Topic)},
Using two sets of data, including daily prices (open, close, high and low) of all S&P 500 stocks between 1992 and 1996, we perform a satistical test of the predictive capability of candlestick patterns. Out-of-sample tests indicate statistical significance at the level of 36 standard deviations from the null hypothesis, and indicate a profit of almost 1% during a two-day holding period. An essentially non-parametric test utilizes standard definitions of three-day candlestick patterns and… 
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Trend-based asset flow in technical analysis and securities marketing
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Economic prediction using neural networks: the case of IBM daily stock returns
  • H. White
  • Economics
    IEEE 1988 International Conference on Neural Networks
  • 1988
Having to deal with the salient features of economic data highlights the role to be played by statistical inference and requires modifications to standard learning techniques which may prove useful in other contexts.
Using Technical Analysis : A Step-by-Step Guide to Understanding and Applying Stock Market Charting Techniques
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Recurrent neural networks were applied to the recognition of stock patterns, and a method for evaluating the networks was developed that is applicable to reducing mismatching patterns.
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This successful and carefully organized text takes the student step by step through the important themes of neoclassical microeconomics, featuring a variety of applications, numerical illustrations and graphs with detailed captions.
Distinguishing random and deterministic systems: Abridged version