Embedding Four Medium-Term Technical Indicators to an Intelligent Stock Trading Fuzzy System for Predicting: A Portfolio Management Approach

Konstandinos Chourmouziadis (), Dimitra K. Chourmouziadou () and Prodromos Chatzoglou
Additional contact information
Konstandinos Chourmouziadis: Democritus University of Thrace
Dimitra K. Chourmouziadou: Democritus University of Thrace

Computational Economics, 2021, vol. 57, issue 4, No 10, 1183-1216

Abstract: Abstract This paper utilizes a small number of coherent trend-following technical indicators with similar characteristics, but constructed with a different philosophy, in order to predict the movement of a stock market (the Athens Stock Exchange—ASE). Each one of them produces independent buy/sell signals which are used by a previously strict classic trading strategy that has been transformed appropriately to promote the subjectivity and fuzziness. These signals act as inputs to an appropriately designed fuzzy system, which makes a medium-term prediction regarding the optimum level (percent) of the investor’s portfolio which should be invested. The performance of the model for the 1997–2012 period is excessively superior from the buy and hold (B&H) strategy and the interest gained from saving bank accounts, even after the subtraction of the trading costs. The results are very convincing, even when the testing period is divided into a number of bull and bear market sub periods.

Keywords: Stock market; Technical analysis; Prediction; Trading strategy; Portfolio management; Fuzzy system (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://link.springer.com/10.1007/s10614-020-10016-2 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

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:kap:compec:v:57:y:2021:i:4:d:10.1007_s10614-020-10016-2

Ordering information: This journal article can be ordered from
http://www.springer. ... ry/journal/10614/PS2

DOI: 10.1007/s10614-020-10016-2

Access Statistics for this article

Computational Economics is currently edited by Hans Amman

More articles in Computational Economics from Springer, Society for Computational Economics Contact information at EDIRC.
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().