基于AC均线预测的股票交易策略及实证

Stock Trading Strategies Based on the AC Algorithm Moving Average Line Forecast and Empirically Study

摘要: 预测股价的趋势和拐点，特别是预测个股股价的拐点，一直是投资者和学术界十分关注的焦点问题，也是投资者短期投资成功的关键。本文利用均线的特点，结合相似体合成(AC)算法的优势，尝试对股价短期走势和拐点进行预测。在此基础上，提出一套短期股票投资的智能交易策略。任选30只股票进行实证说明交易策略的有效性，结果表明：基于AC算法均线预测的股票交易策略取得了显著的超额收益，小盘股投资效果优于大盘股。

Abstract: Forecasting the trends and inflection point of the price, especially stock price, is the focus of the investors and the academic, and the key issues whether the short-term investment will success or not. This paper attempts to predict the trends and inflection point of the short-term stock price by the Analogy Com- plexion (AC) algorithm, taking advantage of the moving average’s features and superiority. Based on it, we propose a set of intelligent trading strategy used to short-term stock investment. To illustrate the effect- tiveness of the strategy, we randomly selected 30 stocks. The empirical result shows that the trading strategy based on the AC moving average forecasting receives a significant excess return and the performance of small- cap stocks is better than the large-cap stocks’.