Optimizing Genetic Algorithm With Momentum Strategy for Technical Trading Rules: Evidence From Futures Markets-Reference-Cited by-同舟云学术

Optimizing Genetic Algorithm With Momentum Strategy for Technical Trading Rules: Evidence From Futures Markets

Published:2024-07-18 Issue:10 Volume:44 Page:1640-1661
ISSN:0270-7314
Container-title:Journal of Futures Markets
language:en
Short-container-title:Journal of Futures Markets

Author:

Li Shihan¹²^ORCID,Li Shuyao³,Liu Qingfu²⁴^ORCID,Tse Yiuman⁵^ORCID

Affiliation:

1. School of Financial Technology Shanghai Lixin University of Accounting and Finance Shanghai China

2. School of Economics Fudan University Shanghai China

3. Business School University of Sydney Sydney New South Wales Australia

4. Yanqi Lake Beijing Institute of Mathematical Sciences and Applications Beijing China

5. Department of Finance and Legal Studies University of Missouri–St. Louis St. Louis Missouri USA

Abstract

ABSTRACTThis paper introduces an innovative genetically optimized dynamic composite strategy for achieving profitability in futures markets. Utilizing daily data from 35 actively traded futures contracts (1984–2022), we highlight the potential advantages of integrating the momentum effect into dynamic moving average strategies. This enhancement can boost the strategy's capability to capture and capitalize on market trends, ensuring consistent and stable returns. The developed dynamically composite technical trading strategy aspires to be a valuable reference for investors and the finance academic community, contributing to advancements in the field.

Publisher

Wiley

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/fut.22543

Reference44 articles.

1. Using genetic algorithms to find technical trading rules1Helpful comments were made by Adam Dunsby, Lawrence Fisher, Steven Kimbrough, Paul Kleindorfer, Michele Kreisler, James Laing, Josef Lakonishok, George Mailath, and seminar participants at Institutional Investor, J.P. Morgan, the NBER Asset Pricing Program, Ohio State University, Purdue University, the Santa Fe Institute, Rutgers University, Stanford University, University of California, Berkeley, University of Michigan, University of Pennsylvania, University of Utah, Washington University (St. Louis), and the 1995 AFA Meetings in Washington, D.C. We are particularly grateful to Kenneth R. French (the referee), and G. William Schwert (the editor) for their suggestions. Financial support from the National Science Foundation is gratefully acknowledged by the first author and from the Academy of Finland by the second and from the Geewax-Terker Program in Financial Instruments by both. Correspondence should be addressed to Franklin Allen, The Wharton School, University of Pennsylvania, Philadelphia, PA 19104-6367.1

2. Technical trading revisited: False discoveries, persistence tests, and transaction costs

3. Profitability of Momentum Strategies in the International Equity Markets

4. The Impacts of Individual Day Trading Strategies on Market Liquidity and Volatility: Evidence from the Taiwan Index Futures Market

5. High-frequency direction forecasting and simulation trading of the crude oil futures using Ichimoku KinkoHyo and Fuzzy Rough Set