Abstract
To create profits, traders must time the market correctly and enter and exit positions at ideal times. Finding the optimal time to enter the market can be quite daunting. The soybean market can be volatile and complex. Weather, sentiment, supply, and demand can all affect the price of soybeans. Traders typically use either fundamental analysis or technical analysis to predict the market for soybean futures' contracts. Every agricultural future's contract or security contract is different in its nature, volatility, and structure. Therefore, the purpose of this research is to optimize the moving average convergence divergence parameter values from traditionally used integers, to values that optimize the profit of the soybean market.
Recommended Citation
P. S. Wiles and D. L. Enke, "Optimizing MACD Parameters via Genetic Algorithms for Soybean Futures," Procedia Computer Science, vol. 61, pp. 85 - 91, Elsevier, Nov 2015.
The definitive version is available at https://doi.org/10.1016/j.procs.2015.09.157
Meeting Name
Complex Adaptive Systems (2015: Nov. 2-4, San Jose, CA)
Department(s)
Engineering Management and Systems Engineering
Keywords and Phrases
Adaptive systems; Agriculture; Algorithms; Commerce; Genetic algorithms; Integer programming; Profitability; Agricultural futures; Fundamental analysis; MACD; Moving averages; Optimal time; Soybean futures; Technical analysis; Technical trading; Electronic trading
International Standard Serial Number (ISSN)
1877-0509
Document Type
Article - Conference proceedings
Document Version
Final Version
File Type
text
Language(s)
English
Rights
© 2015 The Authors, All rights reserved.
Creative Commons Licensing
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.
Publication Date
01 Nov 2015
