Tracking federal funds target rate movements using artificial neural networks

Tracking federal funds target rate movements using artificial neural networks

The Federal Reserve determines federal funds target rate (FFTR), which is one of the most publicized and anticipated economic indicator in the financial world. As the decision making process is complex due to unknown functions, it has been a difficult and challenging process for the researcher to...

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Bibliographic Details
Main Author: V Hemamalini
Other Authors: Quah Tong Seng
Format: Theses and Dissertations
Language:English
Published: 2010
Subjects:
DRNTU::Engineering::Electrical and electronic engineering::Computer hardware, software and systems
Online Access:http://hdl.handle.net/10356/41409
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Institution: Nanyang Technological University
Language: English
Description
Summary:The Federal Reserve determines federal funds target rate (FFTR), which is one of the most publicized and anticipated economic indicator in the financial world. As the decision making process is complex due to unknown functions, it has been a difficult and challenging process for the researcher to model the thoughts of the FOMC members using statistical methods and hence predict the changes in FFTR. With artificial neural networks evolving as an efficient and promising methodology, it is possible to emulate the decision making of FOMC.

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