Foreign-exchange-rate forecasting with artificial neural networks

Author(s)

    • Yu, Lean
    • Wang, Shouyang
    • Lai, Kin Keung

Bibliographic Information

Foreign-exchange-rate forecasting with artificial neural networks

Lean Yu, Shouyang Wang and Kin Keung Lai

(International series in operations research & management science, 107)

Springer, c2007

Available at  / 7 libraries

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Note

Includes bibliographical references (p. [291]-310) and index

Description and Table of Contents

Description

This book focuses on forecasting foreign exchange rates via artificial neural networks (ANNs), creating and applying the highly useful computational techniques of Artificial Neural Networks (ANNs) to foreign-exchange rate forecasting. The result is an up-to-date review of the most recent research developments in forecasting foreign exchange rates coupled with a highly useful methodological approach to predicting rate changes in foreign currency exchanges.

Table of Contents

Preface.- Are foreign exchange rates predictable? An anatomy of a survey from artificial neural networks perspective.- Basic principles of ANN algorithms.- Data preparation in neural network data analysis.- Forecasting foreign exchange rates using an adaptive back-propagation algorithm with optimal learning rate and momentum factor.- An online learning algorithm with adaptive forgetting factors for BP neural network in foreign exchange rate forecasting.- An improved BP algorithm with adaptive smoothing momentum terms for foreign exchange rate prediction.- Hybridizing BPNN and exponential smoothing for foreign exchange rate prediction.- A nonlinear combined model integrating ANN and GLAR for exchange rate forecasting.- A hybrid GA-based SVM model for foreign exchange market trends exploration.- Forecasting foreign exchange rates with a multistage neural network ensemble model.- Foreign exchange rate ensemble forecasting with neural network meta-learning.- A confidence-based neural network ensemble model for predicting foreign exchange market movement direction.- Foreign exchange rates forecasting with multiple candidate models: selecting or combining?.- Developing an intelligent Forex rolling forecasting and trading decision support system I: conceptual framework, modeling techniques and system implementation: developing an intelligent Forex rolling forecasting and trading decision support system II-An empirical and comprehensive assessment.- References.- Subject index.- Author index.

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Details

  • NCID
    BA83418730
  • ISBN
    • 9780387717197
  • LCCN
    2007926588
  • Country Code
    us
  • Title Language Code
    eng
  • Text Language Code
    eng
  • Place of Publication
    New York
  • Pages/Volumes
    xxiii, 313 p.
  • Size
    25 cm
  • Classification
  • Parent Bibliography ID
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