دانلود مقاله ISI انگلیسی شماره 52797
عنوان فارسی مقاله

کشف قاعده معاملات سهام با یک روند تکاملی پیرو مدل

کد مقاله سال انتشار مقاله انگلیسی ترجمه فارسی تعداد کلمات
52797 2015 11 صفحه PDF سفارش دهید محاسبه نشده
خرید مقاله
پس از پرداخت، فوراً می توانید مقاله را دانلود فرمایید.
عنوان انگلیسی
Stock trading rule discovery with an evolutionary trend following model
منبع

Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)

Journal : Expert Systems with Applications, Volume 42, Issue 1, January 2015, Pages 212–222

کلمات کلیدی
روند تکاملی پیرو الگوریتم (eTrend) - تمدید سیستم طبقه بندی کننده (XCS) - کشف قاعده معاملات - انحراف مفهوم
پیش نمایش مقاله
پیش نمایش مقاله کشف قاعده معاملات سهام با یک روند تکاملی پیرو مدل

چکیده انگلیسی

Evolutionary learning is one of the most popular techniques for designing quantitative investment (QI) products. Trend following (TF) strategies, owing to their briefness and efficiency, are widely accepted by investors. Surprisingly, to the best of our knowledge, no related research has investigated TF investment strategies within an evolutionary learning model. This paper proposes a hybrid long-term and short-term evolutionary trend following algorithm (eTrend) that combines TF investment strategies with the eXtended Classifier Systems (XCS). The proposed eTrend algorithm has two advantages: (1) the combination of stock investment strategies (i.e., TF) and evolutionary learning (i.e., XCS) can significantly improve computation effectiveness and model practicability, and (2) XCS can automatically adapt to market directions and uncover reasonable and understandable trading rules for further analysis, which can help avoid the irrational trading behaviors of common investors. To evaluate eTrend, experiments are carried out using the daily trading data stream of three famous indexes in the Shanghai Stock Exchange. Experimental results indicate that eTrend outperforms the buy-and-hold strategy with high Sortino ratio after the transaction cost. Its performance is also superior to the decision tree and artificial neural network trading models. Furthermore, as the concept drift phenomenon is common in the stock market, an exploratory concept drift analysis is conducted on the trading rules discovered in bear and bull market phases. The analysis revealed interesting and rational results. In conclusion, this paper presents convincing evidence that the proposed hybrid trend following model can indeed generate effective trading guidance for investors.

خرید مقاله
پس از پرداخت، فوراً می توانید مقاله را دانلود فرمایید.