کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
1136422 1489130 2013 18 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Utilizing artificial neural networks and genetic algorithms to build an algo-trading model for intra-day foreign exchange speculation
موضوعات مرتبط
مهندسی و علوم پایه سایر رشته های مهندسی کنترل و سیستم های مهندسی
پیش نمایش صفحه اول مقاله
Utilizing artificial neural networks and genetic algorithms to build an algo-trading model for intra-day foreign exchange speculation
چکیده انگلیسی

The Foreign Exchange Market is the biggest and one of the most liquid markets in the world. This market has always been one of the most challenging markets as far as short term prediction is concerned. Due to the chaotic, noisy, and non-stationary nature of the data, the majority of the research has been focused on daily, weekly, or even monthly prediction. The literature review revealed that there is a gap for intra-day market prediction. Identifying this gap, this paper introduces a prediction and decision making model based on Artificial Neural Networks (ANN) and Genetic Algorithms. The dataset utilized for this research comprises of 70 weeks of past currency rates of the 3 most traded currency pairs: GBP∖USD, EUR∖GBP, and EUR∖USD. The initial statistical tests confirmed with a significance of more than 95% that the daily FOREX currency rates time series are not randomly distributed. Another important result is that the proposed model achieved 72.5% prediction accuracy. Furthermore, implementing the optimal trading strategy, this model produced 23.3% Annualized Net Return.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Mathematical and Computer Modelling - Volume 58, Issues 5–6, September 2013, Pages 1249–1266
نویسندگان
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