A NOVEL mechanism for forecasting based on pattern recognition

DOI

10.2991/wartia-16.2016.298How to use a DOI?

Keywords

Pattern recognition, Trend forecasting, Stock market

Abstract

Trend prediction is an attractive topic, because determining the buy and sell points is one of the most important issues for investors in the stock market. The main purpose of this paper is to find an effective mechanism to identify the buy and sell signals. Based on the principle of pattern recognition, we establish a novel mechanism to recognize up or down patterns and the pinpoint for buying or selling. Using all stocks listed on the US NASDAQ, which includes 4460 companies for the period Jan. 1st 2010 to Dec. 31th 2010, our empirical study examines the predictive power of our trading strategies. The results indicate that our new strategies are profitable and that the accuracy rate of our predictions is above 67%.The main contribution of our study is that we find the trend to be more important than the isolated price. We first propose the novel pattern of “uptrend” or “downtrend”, while a continuous unidirectional trend may forecast the uptrend or downtrend in the future, two continuous unidirectional trends could verify the uptrend or down trend. That is, when a stock is on the rise, there must appear continuous up lines on the chart, and if the stock is falling, two down lines appear. We named this strategy as the “Two-line Strategy”

Copyright

© 2016, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Hong Zhou
AU  - Yuxiang Jin
AU  - Yu He
PY  - 2016/05
DA  - 2016/05
TI  - A NOVEL mechanism for forecasting based on pattern recognition
BT  - Proceedings of the 2016 2nd Workshop on Advanced Research and Technology in Industry Applications
PB  - Atlantis Press
SP  - 1459
EP  - 1465
SN  - 2352-5401
UR  - https://doi.org/10.2991/wartia-16.2016.298
DO  - 10.2991/wartia-16.2016.298
ID  - Zhou2016/05
ER  -