• ISSN: 2010-023X
    • Frequency: Bimonthly
    • DOI: 10.18178/IJTEF
    • Editor-in-Chief: Prof.Tung-Zong (Donald) Chang
    • Executive Editor: Ms. Cherry L. Chen
    • Abstracting/ Indexing: Engineering & Technology Digital Library, ProQuest, Crossref, Electronic Journals Library, DOAJ , EBSCO, and Ulrich's Periodicals Directory
    • E-mail: ijtef@ejournal.net
IJTEF 2017 Vol.8(3): 175-178 ISSN: 2010-023X
DOI: 10.18178/ijtef.2017.8.3.558

Predicting Market Response to Monetary Policy in Economic Crisis Phase and Deriving a Decision Support System with Artificial Neural Network

Vyom Shrivastava
Abstract—Economic bubbles are the inevitable part of our Economic system and are responsible for various past turbulence, which had a deep impact for several years. It is a very well established fact that the prediction of the economic bubbles is an extremely tough job because of the involvement of a lot of non-linear factors, therefore it could be extremely useful to have some kind of a decision support system which could throw some light on the market movements. Another challenge that I intend to solve through this paper is pre-determining the response of the market to various variables, directly or indirectly controlled by the federal reserve bank and the central government. This paper attempts to present a clubbed variable which could be used in assessing the response of the market to the prevailing monetary policy. The research involves developing of an Artificial Neural Network Model to access the monetary policy response to the market and to create an ANN decision support mechanism for assisting traders, academicians and even the central bank for pre-determining the potential impact of the given monetary policy based on the historic data. These models will not only reduce the uncertainty but the ANN algorithm will also capture complex trends and relationships which are impossible for an unaided trader to extract.

Index Terms—Artificial neural network, decision support system, economic bubbles, monetary policy.

Vyom Shrivastava is with department of Mechanical Engineering, IIT Kharagpur, India (e-mail: vyomiitkgp@gmail.com).

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Cite: Vyom Shrivastava, "Predicting Market Response to Monetary Policy in Economic Crisis Phase and Deriving a Decision Support System with Artificial Neural Network," International Journal of Trade, Economics and Finance vol.8, no.3, pp. 175-178, 2017.

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