Development of an intelligent method based on fuzzy technical indicators for predicting and trading the euro-dollar exchange rate

Subject Areas : Financial engineering

alireza sadeghi ¹ ( Department of financial management , science and research branch, Islamic Azad university, tehran, iran )
amir Daneshvar ² ( Department of information technology, Electronic Campus, Islamic Azad university, tehran, iran )
Mahdi Madanchi Zaj ³ ( Department of Financial Management, Electronic Campus, Islamic Azad University, Tehran, Iran )

Received: 2020-10-08 Accepted : 2020-11-13 Published : 2020-12-21

Keywords: Genetic Algorithm, Support vector machine, Forex, fuzzy technical indicators,

Abstract :

Today, the Forex market is the largest financial market in the world. Determining the right strategy for buying or selling in the Forex market is based on predicting the price trend. Therefore, to choose a suitable strategy in Forex, complex meta-heuristic models are used. In this research, by predicting the market trend and based on trading rules based on fuzzy technical indicators, a new method for investing in the Forex market is presented. For forecasting, a combination of hyper support vector machine (HSVM) algorithm is used and for market classification in three different classes (uptrend, downtrend, sideway) and a dynamic genetic algorithm is used to optimize trading rules. Five fuzzy technical indicators have been used to determine the trading rules. Euro-dollar pair data is used as daily training and test data for a daily period between 2010 and 2019. The results obtained compared to traditional methods have had promising results.

References:

 [1]. درگاهی حسین،انصاری رضا،بهبود مدل­سازی شبکه­های عصبی در پیش­بینی نرخ ارز با بکارگیری شاخص­های تلاطم،تحقیقات اقتصادی، 1384 ،تابستان،شماره 69، صفحات 181-216

[2] سمنانی خطیب، هادی­نژاد، خشوعی رکسانا،مقایسه قدرت شبکه عصبی مصنوعی و شبکه عصبی پویا در پیش­بینی نرخ ارز:کاربردی از تبدیل موجک، فصل­نامه آینده پژوهی مدیریت، 1393،شماره 100،صفحه 35-49

[3] سینایی حسن­علی، مرتضوی سعیدالله،تیموری اصل یاسر، ،پیش­بینی شاخص بورس اوراق بهادار با استفاده از شبکه­های عصبی مصنوعی،بررسی­های حسابداری و حسابرسی،1384،شماره 41،صفحه 83-59

[4] . شریف مقدم، شفق ، هاشمی، سید ذبیح­اله، پیش­بینی نرخ ارز یورو به دلار با تکنیک شبکه عصبی مصنوعی، فصلنامه مهندسی مالی و مدیریت اوراق بهادار،1397، زمستان ،شماره سی و هفتم، صفحات 413-399

[5].حاجی غیاثی­فر محمد حسین،نیکومرام هاشم، آسیب­شناسی مکانیزم انجام معاملات در یازار ارز جهانی و ارائه مدل پیشنهادی بازار متشکل ارزی مبتنی بر واقعیت اقتصاد، مجله مهندسی مالی و مدیریت اوراق بهادار،1398،تابستان،شماره سی و نهم، صفحات 135-169

[6] طیبی، سید کمیل،معینی،شهرام،زمانی،زهرا،مدلسازی اجتناب ناپذیری زیان اکثر معاملا­گران در بازار فارکس با استفاده از فرایند تصادفی، تحقیقات مدل­سازی اقتصادی،1392،بهار، شماره 11،صفحات100-121

[7]. غفاری، مهدی و یوسفی، راحله، مدلسازی پیش­بینی قیمت ارز با استفاده از شبکه­های عصبی، مجله مهندسی مالی و مدیریت اوراق بهادار،1390 ، شماره هشتم، پاییز، صفحات 119-99

[8] مورفی، جان، تحلیل تکنیکال در بازار سرمایه، چاپ پانزدهم،تهران، نشر چالش، 1398

[9] .مهدی پور، علیرضا، الگوها و نمودارهای اسرار آمیز در بازارهای مالی، چاپ اول ،تهران، نشر آراد، 1398

[10]. Available data on https://www.investing.com

[11]Achchab, Said, Bencharef Omar (B), and Ouaarab Aziz , A Combination of Regression,Techniques and Cuckoo Search Algorithm for FOREX Speculation, Springer International Publishing AG 2017 ,Advances in Intelligent Systems and Computing ,p.225-237

[12]. Bank for International Settlements(BIS),Foreign exchange turnover in April 2019, Issue: 16.Sep.2019

[13] Bernardo J. de A., Rui Ferreira N., Nuno Horta, Combining Support Vector Machine with Genetic Algorithms to optimize investments in Forex markets with high leverage, Applied Soft Computing ,2018,64, pp. 596–613

[14]Brito ,R.F.B. de, Oliveira, A.L.I., Comparative study of forex trading systems built with SVR+GHSOM and genetic algorithms optimization of technical indicators, in: Proceedings of the 2012 24th IEEE International Conference on Tools with Artificial Intelligence, IEEE, 2012, pp. 351–358.

[15]Galeshchuk s, Mukherjee s,FOREX Trading Strategy Optimization,14th International Conference Computing and Artificial Intelligence,2018, pp 69-76

[16]Hirabayashi,. Aranha C,. Iba H, Optimization of the trading rule in foreign exchange using genetic algorithm, in: Proceedings of the 11th Annual Conference on Genetic and Evolutionary Computation (GECCO ’09), Montreal, Canada, New York USA : ACM, 2009, pp. 1529–1536.

[17]Kamruzzaman j,sarker r,ahmad e,SVM based models for predicting foreign currency exchange rates, Third IEEE International Conference,2003

 [. [18] Macedo, Lobato ,Luís, Godinho, Pedro  ·Alves, Maria João, A Comparative Study of Technical Trading Strategies Using a Genetic Algorithm, Springer Science+Business,2016,

[19]Lam Thu. B., Van Truong Vua,⁎, Thi Thu Huong Dinh, A novel evolutionary multi-objective ensemble learning approach for forecasting currency exchange rates, Data & Knowledge Engineering,2017

 [20]. Sermpinis G.,. Stasinakis, C Theofilatos K., Karathanasopoulos A., Modeling, forecasting and trading the EUR exchange rates with hybrid rolling genetic algorithms – support vector regression forecast combinations, Eur. J. 2015, 247 (3) , pp.831–846.

[21] Shin, K.S., Lee, T.S., Kim, H.J. An application of support vector machinesin bankruptcy prediction model., Expert Systems with Applications, 2005,28(1),127-135.

 

[1]. Dargahi Hossein, Ansari Reza, Improvement of Neural Networks Modeling in Forecasting Exchange Rate Using Turbulence Indexes, Economic Research, 2014, Summer, No. 69, Pages 181-216
[2] Semnani Khatib, Hadi-Nejad, Roxana Khashoui, Comparison of the power of artificial neural network and dynamic neural network in forecasting exchange rates: an application of wavelet transformation, Future Management Research Quarterly, 2013, number 100, pages 35-49
[3] Sinaii Hasan-Ali, Mortazavi Saeedullah, Timuri Asal Yaser, Forecasting Stock Exchange Index Using Artificial Neural Networks, Accounting and Auditing Reviews, 2014, No. 41, Pages 59-83
[4] Sharif Moghadam, Shafaq, Hashemi, Seyyed Zabihalah, forecasting the euro to dollar exchange rate with artificial neural network technique, financial engineering and securities management quarterly, 2017, winter, number 37, pages 399-413
[5]. Haji Ghiashifar Mohammad Hossein, Nikumram Hashim, Pathology of the mechanism of doing transactions in the global currency exchange and presenting a proposed model of the currency market based on economic reality, Journal of Financial Engineering and Securities Management, 2018, Summer, Number 3 and IX, pages 135-169
[6] Tayibi, Seyed Kamil, Moeini, Shahram, Zamani, Zahra, Modeling the inevitability of the losses of most traders in the forex market using a stochastic process, Economic Modeling Research, 2013, Spring, No. 11, Pages 100-121
[7]. Ghafari, Mehdi and Yousefi, Rahela, currency price forecasting modeling using neural networks, Journal of Financial Engineering and Securities Management, 2018, No. 8, Autumn, pages 99-119
[8] Murphy, John, Technical analysis in the capital market, 15th edition, Tehran, Challenge Publishing, 2018
[9] Mehdipour, Alireza, mysterious patterns and charts in financial markets, first edition, Tehran, Arad Publishing House, 2018
[10]. Available data on https://www.investing.com
[11] Achchab, Said, Bencharef Omar (B), and Ouaarab Aziz, A Combination of Regression, Techniques and Cuckoo Search Algorithm for FOREX Speculation, Springer International Publishing AG 2017, Advances in Intelligent Systems and Computing, p.225-237
[12]. Bank for International Settlements (BIS), Foreign exchange turnover in April 2019, Issue: 16.Sep.2019
[13] Bernardo J. de A., Rui Ferreira N., Nuno Horta, Combining Support Vector Machine with Genetic Algorithms to optimize investments in Forex markets with high leverage, Applied Soft Computing, 2018, 64, pp. 596–613
[14] Brito, R.F.B. de, Oliveira, A.L.I., Comparative study of forex trading systems built with SVR+GHSOM and genetic algorithms optimization of technical indicators, in: Proceedings of the 2012 24th IEEE International Conference on Tools with Artificial Intelligence, IEEE, 2012, pp. 351–358.
[15] Galeshchuk s, Mukherjee s, FOREX Trading Strategy Optimization, 14th International Conference Computing and Artificial Intelligence, 2018, pp 69-76
[16] Hirabayashi, Aranha C,. Iba H, Optimization of the trading rule in foreign exchange using genetic algorithm, in: Proceedings of the 11th Annual Conference on Genetic and Evolutionary Computation (GECCO ’09), Montreal, Canada, New York USA: ACM, 2009, pp. 1529–1536.
[17] Kamruzzaman j, Sarker r, Ahmad e, SVM based models for predicting foreign currency exchange rates, Third IEEE International Conference, 2003
 [. [18] Macedo, Lobato, Luís, Godinho, Pedro · Alves, Maria João, A Comparative Study of Technical Trading Strategies Using a Genetic Algorithm, Springer Science+Business, 2016,
[19] Lam Thu. B., Van Truong Vua, ⁎, Thi Thu Huong Dinh, A novel evolutionary multi-objective ensemble learning approach for forecasting currency exchange rates, Data & Knowledge Engineering, 2017
 [20]. Sermpinis G. Stasinakis, C Theofilatos K., Karathanasopoulos A., Modeling, forecasting and trading the EUR exchange rates with hybrid rolling genetic algorithms – support vector regression forecast combinations, Eur. J. 2015, 247 (3), pp.831–846.
[21] Shin, K.S., Lee, T.S., Kim, H.J. An application of support vector machines in bankruptcy prediction model., Expert Systems with Applications, 2005, 28(1), 127-135.