Comparison of Forex Market Forecasting Tools Based on Evolino Ensemble and Technical Analysis Indicators

Nijolė Maknickienė (), Jelena Stankevičienė () and Algirdas Maknickas ()
Additional contact information
Nijolė Maknickienė: Vilnius Gediminas Technical University, Saulėtekio al. 11, LT-10223 Vilnius, Lithuania. (corresponding author).
Jelena Stankevičienė: Vilnius Gediminas Technical University, Saulėtekio al. 11, LT-10223 Vilnius, Lithuania.
Algirdas Maknickas: Vilnius Gediminas Technical University, Saulėtekio al. 11, LT-10223 Vilnius, Lithuania.

Journal for Economic Forecasting, 2020, issue 3, 134-148

Abstract: Financial markets are an important mechanism for allocating funds to the economy. Traders in finance markets use different strategies to increase their probability of success, and artificial intelligence is already often integrated into the investor support system. The purpose of this article is to compare the possibilities of different trading strategies to detect and predict exchange rate changes. Our model, based on an Evolino ensemble, provides two histograms based on high and low data. Probability estimation, the rejection of unlikely values, is the basis of these strategies, in which two known indicators are compared with strategies based on an Evolino ensemble prediction. Bollinger bands and Ichimoku Kinko Hyo indicators were selected because their lines determine the extreme points of fluctuation regarding exchange rates. Our findings indicate that high and low distributions received by an Evolino ensemble allow the investor to increase the probability of success and can be successfully used to robotize trading in the currency market or to develop new fintech services for investors.

Keywords: Bollinger bands; Ichimoku Kinko Hyo; Evolino; prediction; extreme values; high-low strategy (search for similar items in EconPapers)
JEL-codes: G15 G17 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://www.ipe.ro/rjef/rjef3_20/rjef3_2020p134-148.pdf

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:rjr:romjef:v::y:2020:i:3:p:134-148

Access Statistics for this article

Journal for Economic Forecasting is currently edited by Lucian Liviu Albu and Corina Saman

More articles in Journal for Economic Forecasting from Institute for Economic Forecasting Contact information at EDIRC.
Bibliographic data for series maintained by Corina Saman ( this e-mail address is bad, please contact ).