REFINING PRICE TO BOOK VALUE MODEL FOR VALUING INDIAN BANK STOCK - AN ARTIFICIAL NEURAL NETWORK APPROACH CHARUMATHI, B
Material type: TextPublication details: JAIPUR DR. PRAVEEN JAIN - RESEARCH DEVELOPMENT ASSOCIATION SEPTEMBER 2015Description: 15-25Subject(s): In: JOURNAL OF ACCOUNTING AND FINANCEItem type | Current library | Call number | Vol info | Status | Notes | Date due | Barcode | Item holds | |
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Journal Article | Main Library | VOL. 29, NO. 2/5555125JA2 (Browse shelf(Opens below)) | Available | 5555125JA2 | |||||
Journals and Periodicals | Main Library On Display | JOURNAL/FIN/Vol 29, No 2/5555125 (Browse shelf(Opens below)) | Vol 29, No 2 (01/07/2015) | Not for loan | April - September, 2015 | 5555125 |
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THIS STUDY PERFORMS AND COMPARES THE ACCURACY OF PRICE TO BOOK VALUE MODEL AND REFINED PRICE TO BOOK VALUE MODEL USING ARTIFICIAL NEURAL NETWORK (ANN) FOR VALUING BANK STOCKS. PREDICTION ACCURACY MEASURING PROCEDURES ARE USED TO COMPARE THE PERFORMANCE OF THESE MODEL. THIS STUDY ALSO FOCUSED ON COMPARING THE PREDICTIVE POWER OF PRICE TO BOOK VALUE MODEL & REFINED PRICE TO BOOK VALUE MODEL (USING ANN) USING COEFFICIENT OF DETERMINATION. THE RESULTS OF EMPIRICAL ANALYSIS SUPPORT THAT REFINED PRICE TO BOOK VALUE MODEL USING ANN CAN BE USED AS A VALUATION TOOL TO PROVIDE BETTER AND MORE ACCURATE ESTIMATION OF EQUITY STOCK PRICES OF BANKS.
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