Forecasting directional movement of Forex data using LSTM with technical and macroeconomic indicators

Date

2021-01-01

Author

Yildirim, Deniz Can
Toroslu, İsmail Hakkı
Fiore, Ugo

Metadata

Show full item record

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Item Usage Stats

359
views

0
downloads

Forex (foreign exchange) is a special financial market that entails both high risks and high profit opportunities for traders. It is also a very simple market since traders can profit by just predicting the direction of the exchange rate between two currencies. However, incorrect predictions in Forex may cause much higher losses than in other typical financial markets. The direction prediction requirement makes the problem quite different from other typical time-series forecasting problems. In this work, we used a popular deep learning tool called "long short-term memory" (LSTM), which has been shown to be very effective in many time-series forecasting problems, to make direction predictions in Forex. We utilized two different data sets-namely, macroeconomic data and technical indicator data-since in the financial world, fundamental and technical analysis are two main techniques, and they use those two data sets, respectively. Our proposed hybrid model, which combines two separate LSTMs corresponding to these two data sets, was found to be quite successful in experiments using real data.

URI

https://hdl.handle.net/11511/88640

Journal

FINANCIAL INNOVATION

DOI

https://doi.org/10.1186/s40854-020-00220-2

Collections

Department of Computer Engineering, Article

Suggestions

OpenMETU
Core

Forecasting directional movement of forex data using LSTM with technical and macroeconomic indicators Yıldırım, Deniz Can; Toroslu, İsmail Hakkı; Department of Computer Engineering (2019) Foreign Exchange is known as Forex or FX is a financial market where currencies are bought and sold simultaneously. Forex is the largest financial market with more than $5 trillion volume. It is a decentralized market that is operational 24 hours in a day other than weekends which makes different from other markets. Fundamental and Technical Analysis are the two techniques that are commonly used in predicting the future prices in Forex. Fundamental Analysis concentrates on the economical, social and politic...
Heuristic based trading system on forex data using technical indicator rules Öztürk, Murat; Toroslu, İsmail Hakkı; Fidan, Güven; Department of Computer Engineering (2015) The foreign exchange market, which is widely known as Forex or FX, is the largest financial market with a daily transactional volume of $5 trillion. Due to the huge structure of the market, price analysis on FX market draws attention of many scientists and practitioners. There are 2 main analysis approaches: Fundamental and technical analysis. Fundamental analysis focuses on the macroeconomic factors such as interest rate to explain the market movements. Technical analysis deals with past market price data ...
How does the stock market volatility change after inception of futures trading? Esen, İnci; Danışoğlu, Seza; Department of Financial Mathematics (2007) As the trading volume in TURKDEX, the first and only options and futures exchange in Turkey, increases, it becomes more important to have an understanding of the effect of stock index futures trading on the underlying spot market volatility. In this respect, this thesis analyzes the effect of ISE-National 30 index futures contract trading on the underlying stocks’ volatility. In this thesis, spot portfolio volatility is decomposed into two components and this decomposition is applied to a single-factor retu...
The volatility spillover among a country’s foreign exchange, bond, and stock markets: a multivariate garch analysis Kubilay, Mustafa Murat; Danışoğlu, Seza; Department of Financial Mathematics (2012) The purpose of this study is to examine the volatility spillover among a country’s foreign exchange, bond and stock markets and the volatility transmission from the global bond, stock and commodity markets to these local financial markets. The sample for the study includes data from both emerging and developed economies in the time period between 2004 and 2011. A multivariate GARCH methodology with the BEKK representation is applied for the local financial markets and global variables are included as exogen...
Investigating the effects of illiquidity on credit risks via new liquidity augmented stochastic volatility jump diffusion model Gaygısız Lajunen, Esma; Hekimoglu, Alper (2021-12-01) Liquidity is extremely important not only within the context of financial markets but also in every scale of economic transactions. In this study, within the realm of financial markets, we configure liquidity as an independent stochastic process moderating the fluidity of all transactions and hence dynamically changing asset values. This study's asset value process ignoring liquidity is modelled with a stochastic volatility jump-diffusion (SVJ) model and that model is augmented with the incorporation of a l...

Citation Formats

D. C. Yildirim, İ. H. Toroslu, and U. Fiore, “Forecasting directional movement of Forex data using LSTM with technical and macroeconomic indicators,” FINANCIAL INNOVATION, pp. 0–0, 2021, Accessed: 00, 2021. [Online]. Available: https://hdl.handle.net/11511/88640.