The Predictive Power of Price Patterns

@article{Caginalp1998ThePP,
  title={The Predictive Power of Price Patterns},
  author={Gunduz Caginalp and Henry Laurent},
  journal={FEN: Behavioral Finance (Topic)},
  year={1998}
}
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… 
Can 1-day candlestick patterns be profitable on the 30 component stocks of the DJIA?
ABSTRACT We set out in this study to conduct a comprehensive analysis of the profitability of every possible 1-day candlestick pattern using data on the 30 component stocks of the Dow Jones
Tests for Two-Day Candlestick Patterns in the Emerging Equity Market of Taiwan
Using the Taiwan 50 Index component stocks for the period from January 2, 2002, to December 31, 2009, this study examines the predictive power of candlestick trading strategies. A four-digit numbers
Pinpoint and Synergistic Trading Strategies of Candlesticks
The candlestick trading strategy is a very popular technical method to convey the growth and decline of the demand and supply in the financial market. In this paper, we aim to investigate the
CandlestiCK Charting in European stock markets
The purpose of this study is to investigate whether an old Japanese trading technique can function in a Western context. This paper employs a 1 4 vector to categorise two-day candlestick patterns
Is candlestick continuation patterns applicable in Malaysian stock market
Technical analysis is deemed to be an anathema to the modern finance theory as it contradicts with the efficient market hypothesis, typically the weak form market efficiency which forbids the
...
...

References

SHOWING 1-10 OF 20 REFERENCES
Simple Technical Trading Rules and the Stochastic Properties of Stock Returns
This paper tests two of the simplest and most popular trading rules--moving average and trading range break--by utilizing the Dow Jones Index from 1897 to 1986. Standard statistical analysis is
Statistical Inference and Modelling of Momentum in Stock Prices
The following results are obtained, (i) It is possible to obtain a time series of market data {y(t)} in which the fluctuations in fundamental value have been compensated for. An objective test of the
The Use of Volatility Measures in Assessing Market Efficiency
My initial motivation for considering volatility measures in the efficient markets models was to clarify the basic smoothing properties of the models to allow an understanding of the assumptions
Market Statistics and Technical Analysis: The Role of Volume
The authors investigate the informational role of volume and its applicability for technical analysis. They develop a new equilibrium model in which aggregate supply is fixed and traders receive
Trend-based asset flow in technical analysis and securities marketing
This article generalizes the asset flow model of the dynamics of equity prices to multiple groups of investors with distinct strategies and assessments of value. Applications include the closed-end
Economic prediction using neural networks: the case of IBM daily stock returns
  • H. White
  • Economics
    IEEE 1988 International Conference on Neural Networks
  • 1988
TLDR
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
In "Using Technical Analysis" author Clifford Pistolese shows average investors how they too can reap the benefits of technical analysis. Well-organized and easy-to-understand, this book explains a
Stock price pattern recognition-a recurrent neural network approach
TLDR
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.
Price theory and its uses
TLDR
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
...
...