The Equity Valuation Accuracy among Multiple Screening Models: A study from an Emerging Stock Market
Abstract: Over the past 3 decades, none of valuation models is accepted as the most accurate valuation model. The most common debate in academic area is about Discounted Cash Flow (DCF) and Residual Income Valuation (RIV). Multiple screenings, a valuation model that common for practitioners are seld...
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| 主要な著者: | , |
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| フォーマット: | E-Article |
| 言語: | English |
| 出版事項: |
Medwell Journals
2011
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| 主題: | |
| オンライン･アクセス: | http://ir.unimas.my/id/eprint/9687/1/The%20Equity%20Valuation%20Accuracy%20among%20Multiple%20Screening%20Models%20A%20Study%20from%20an%20Emerging%20Stock%20Market%28abstract%29.pdf http://ir.unimas.my/id/eprint/9687/ http://medwelljournals.com/abstract/?doi=ibm.2011.50.57 |
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| 要約: | Abstract: Over the past 3 decades, none of valuation models is accepted as the most accurate valuation model. The most common debate in academic area is about Discounted Cash Flow (DCF) and Residual Income Valuation (RIV). Multiple screenings, a valuation model that common for practitioners are seldom investigated. This research conducted a test to investigate the best multiple screening models in term of valuation accuracy. Hypothetically, multiple screening models are classified into Price Earnings Ratio (PER) approach, Price to Sales Ratio (PSR) and Price to Book Value (PBV) ratio. After conducting the investigation in pooled data, PER method is superior in term of valuation accuracy compare to PSR and PBV. In industrial classification, PBV outperform the accuracy of PER and PSR approach in 17 industrial categories. Meanwhile PER which outstanding in accuracy of pooled data is only superior in 10 industrial categories. Thus, PER method still can be used in those 17 PBV industrial categories because of the small differences. But, PBV cannot be used as valuation method in 3 industrial categories. This research still needs further discussion, especially, the discussion of using non-linear approach using forecasted value driver and using combination of value drivers. |
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