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Document Type : Latin Dissertation
Language of Document : English
Record Number : 149784
Doc. No : ET21576
Main Entry : MARK CECCHINI
Title Proper : QUANTIFYING THE RISK OF FINANCIAL EVENTS USING KERNEL METHODS AND INFORMATION RETRIEVAL
Note : This document is digital این مدرک بصورت الکترونیکی می باشد
Abstract : A financial event is any happening which dramatically changes the value of a firm.Examples of financial events are management fraud, bankruptcy, exceptional earningsannouncements, restatements, and changes in corporate structure. This dissertationcreates a method for timely detection of financial events using machine learning methodsto create a discriminant function. As there are a myriad of possible causes for anyfinancial event, the method created must be powerful. In order to increase the power ofcurrent methods of detection text related to the company is analyzed together withquantitative information on the company. The text variables are chosen based on anautomatically created accounting ontology. The quantitative variables are mapped to atested for theQ1 PC1 bus cardBoth these projects mere sofixare des elopment efforts tonards contributing to dlfferentaspects of Roboucs and lZ1echatronics projects m the Controls and Roboucs Group..
Subject : Electericl tess
: برق
electronic file name : TL44750.pdf
Title and statement of responsibility and : QUANTIFYING THE RISK OF FINANCIAL EVENTS USING KERNEL METHODS AND INFORMATION RETRIEVAL [Thesis]
 
 
 
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