DocumentCode :
2196577
Title :
Exchange Rate Forecasting Method Based on Particle Swarm Optimization and Probabilistic Neural Network Model
Author :
Liu, BingXiang ; Wang, Hua ; Cheng, Xiang
Author_Institution :
Sch. of Inf. Eng., JDZ Ceramic Inst., Jingdezhen, China
Volume :
1
fYear :
2011
fDate :
14-15 May 2011
Firstpage :
288
Lastpage :
292
Abstract :
Foreign exchange market is a complex market, with a high degree of volatility characteristics. Exchange rate formation mechanism and the factors affecting exchange rate volatility is also very complex, is a nonlinear system, it is difficult to accurately forecast, probabilistic neural network is applied to the frontiers of forecast, and aimed at the characteristics of probabilistic neural network to pretreatment the exchange of data and forecast the tendency. And by changing the vector dimensionality experiment obtain the best entry to embed dimensionality, based on the model, particle swarm optimization algorithm applied in the probabilistic neural network to optimize the smoothing factors, tested and improved the precise prediction and valuable.
Keywords :
exchange rates; forecasting theory; neural nets; particle swarm optimisation; probability; exchange rate forecasting method; exchange rate formation mechanism; exchange rate volatility; foreign exchange market; particle swarm optimization algorithm; probabilistic neural network model; vector dimensionality experiment; Accuracy; Artificial neural networks; Exchange rates; Forecasting; Particle swarm optimization; Predictive models; Probabilistic logic; exchange rate; forecast; particle swarm optimization; probabilistic neural network;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Network Computing and Information Security (NCIS), 2011 International Conference on
Conference_Location :
Guilin
Print_ISBN :
978-1-61284-347-6
Type :
conf
DOI :
10.1109/NCIS.2011.65
Filename :
5948735
Link To Document :
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