Optimizing MACD Parameters via Genetic Algorithms for Soybean Futures
Author(s) -
Phoebe S. Wiles,
David Enke
Publication year - 2015
Publication title -
procedia computer science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.334
H-Index - 76
ISSN - 1877-0509
DOI - 10.1016/j.procs.2015.09.157
Subject(s) - computer science , futures contract , volatility (finance) , profit (economics) , futures market , supply and demand , algorithm , economics , econometrics , microeconomics , financial economics
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
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