Towards Predicting Financial Information Manipulation (Record no. 29006)

MARC details
000 -LEADER
fixed length control field 01772pab a2200205 454500
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 140923b0 xxu||||| |||| 00| 0 eng d
040 ## - CATALOGING SOURCE
Transcribing agency Welingkar Institute of Management Development & Research, Mumbai
Original cataloging agency Welingkar Institute of Management Development & Research, Mumbai
041 ## - LANGUAGE CODE
Language code of text/sound track or separate title ENG
082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number
Item number Akt
100 ## - MAIN ENTRY--PERSONAL NAME
Personal name Aktas Ramazan
245 ## - TITLE STATEMENT
Title Towards Predicting Financial Information Manipulation
250 ## - EDITION STATEMENT
Edition statement 7
260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT)
Place of publication, distribution, etc.
Name of publisher, distributor, etc. Jul 2007
Date of publication, distribution, etc. 0
300 ## - PHYSICAL DESCRIPTION
Extent 38-52 Pp.
490 ## - SERIES STATEMENT
Volume/sequential designation 13
520 ## - SUMMARY, ETC.
Summary, etc. Manipulation is one of the important issues in securities markets because manipulative actions send false signals to the investors and make them buy or sell securities they otherwise would not buy or sell. There are different types of manipulations that can deceive investors. One type of manipulation is financial information manipulation. Manipulators, who use this type of manipulation, distort information in the financial statements in order to give false information about the prospects of the issuing firms. This paper attempts to predict financial information manipulation by using the multivariate statistical techniques and neural networks. A number of financial ratios are used as explanatory variables. The multivariate statistical techniques used are discriminant analysis, logistics regression (logit), and probit. Unlike other studies, the present study takes multicollinearity between financial ratios into account and conclude that the estimated multivariate statistical models rather than the neural networks can be used as early warning systems to detect possible financial information manipulations.
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Financial Information Manipulation,
856 ## - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier <a href="http://192.168.6.13/libsuite/mm_files/Articles/AR9115.pdf">http://192.168.6.13/libsuite/mm_files/Articles/AR9115.pdf</a>
906 ## - LOCAL DATA ELEMENT F, LDF (RLIN)
a 26477
Holdings
Withdrawn status Lost status Damaged status Not for loan Home library Current library Date acquired Cost, normal purchase price Total Checkouts Full call number Barcode Date last seen Cost, replacement price Price effective from Koha item type
        Main Library Main Library 18/09/2007 0.00   Akt AR9115 23/09/2014 0.00 23/09/2014 Articles

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