Foundations of Technical Analysis（技术分析的基石:算法,统计推论,实证实现）

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Foundations of Technical Analysis：Computational Algorithms, Statistical Inference, and Empirical Implementation


技术分析的基石:算法,统计推论,实证实现
Andrew W. Lo, Harry Mamaysky and Jiang Wang
The Journal of Finance
Vol. 55, No. 4, Papers and Proceedings of the Sixtieth Annual Meeting of the American Finance Association, Boston, Massachusetts, January 7-9, 2000 (Aug., 2000), pp. 1705-1765

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技术分析的基石:算法,统计推论,实证实现
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Conclusion
In this paper, we have proposed a new approach to evaluating the efficacy of technical analysis. Based on smoothing techniques such as nonparametric kernel regression, our approach incorporates the essence of technical analysis: to identify regularities in the time series of prices by extracting nonlinear patterns from noisy data. Although human judgment is still superior to most computational algorithms in the area of visual pattern recognition, recent advances in statistical learning theory have had successful applications in fingerprint identification, handwriting analysis, and face recognition. Technical analysis may well be the next frontier for such methods.

We find that certain technical patterns, when applied to many stocks over many time periods, do provide incremental information, especially for Nasdaq stocks. Although this does not necessarily imply that technical analysis can be used to generate “excess” trading profits, it does raise the possibility that technical analysis can add value to the investment process.

Moreover, our methods suggest that technical analysis can be improved by using automated algorithms such as ours and that traditional patterns such as head-and-shoulders and rectangles, although sometimes effective, need not be optimal. In particular, it may be possible to determine “optimal patterns” for detecting certain types of phenomena in financial time series, for example, an optimal shape for detecting stochastic volatility or changes in regime. Moreover, patterns that are optimal for detecting statistical anomalies need not be optimal for trading profits, and vice versa. Such considerations may lead to an entirely new branch of technical analysis, one based on selecting pattern-recognition algorithms to optimize specific objective functions. We hope to explore these issues more fully in future research.

希望有兴趣的朋友一起用Python将论文实证部分重新实现
PS我曾经用SAS做过，最近几年转用Python


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关键词：Foundations foundation Technical Analysis Analysi

yunnandlg 发表于 2019-5-11 10:22
Foundations of Technical Analysis：Computational Algorithms, Statistical Inference, and Empirical Im ...

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yunnandlg 发表于 2019-5-11 10:22
Foundations of Technical Analysis：Computational Algorithms, Statistical Inference, and Empirical Im ...

非常感谢

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thanks for sharing

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