An Empirical Investigation of the Ohlson Model–A Panel Cointegration Approach

Lee, Shih-Cheng; Chen, Jiun-Lin; Tsa, Ming-Shann

doi:10.14453/aabfj.v8i2.4

Cited by 14 publications

(17 citation statements)

References 25 publications

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“…Ohlson's model has been used in a variety of scenarios other than bankruptcy. For example, Lee et al (2014) evaluated the predictive power of the Ohlson model for future market value assessment. Noga and Schnader, (2013) expanded on Ohlson's model by investigating the association between abnormal changes in book-tax differences (BTDs) and bankruptcy using a hazard model and out-of-sample testing.…”

Section: Discussionmentioning

confidence: 99%

The Use Of Ohlson's O-Score For Bankruptcy Prediction In Thailand

Lawrence¹,

Pongsatat²,

Lawrence³

2015

JABR

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Business failure is a major concern to all parties involved and can create high costs and heavy losses. If bankruptcy can be predicted with reasonable accuracy ahead of time, firms can better protect their businesses and can take action to minimize risk and loss of business, and perhaps even prevent the bankruptcy itself. Bankruptcy prediction in thailand is important because business in thailand has historically operated on a system of trust where one person doing business trusts the other to perform as agreed upon in written and oral contracts. The threat of bankruptcy tends to diminish that trust and weakens the country's ability to prosper. While research in bankruptcy has been extensive, there has been only limited research on bankruptcy prediction in thailand. This study expands on an earlier study by pongsatat, et al (1994) using ohlson's o-score to determine if there a significant difference in ohlson’s o-score as measured by ohlson’s logit analysis model between bankrupt and non-bankrupt firms in thailand. The results of the independent samples t-test demonstrates that there are significant differences in the population means for one year, two years and three years prior to bankruptcy at the 0.05 level. Therefore the null hypothesis that there is no difference in the mean of ohlson’s o-score as measured by logit analysis between bankrupt and non-bankrupt firms in thailand is rejected.

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Section: Discussionmentioning

confidence: 99%

The Use Of Ohlson's O-Score For Bankruptcy Prediction In Thailand

Lawrence¹,

Pongsatat²,

Lawrence³

2015

JABR

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“…The Ohlson model demonstrates a long-run equilibrium relationship between stock price and the fundamental value of companies and, in the same time, has better ability to predict future stock price for different time horizons (Lee, Chen, & Tsa, 2014).…”

Section: Methodsmentioning

confidence: 99%

The Impact of Esg Factors on Market Value of Companies From Travel and Tourism Industry

Ionescu

Firoiu

Pîrvu

et al. 2019

Technological and Economic Development of Economy

115

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The aim of this paper is to investigate the relationship between environmental, social, and governance (ESG) factors and firm market value for the companies from travel and tourism industry and, in the same time, to investigates the question if the association between good ESG scores for travel and tourism companies and their market value can be used as a performance predictor. The impact of extra-financial ESG performance on market value of the companies was estimated using the modified version of the Ohlson (1995) model, based on a sample of 73 listed companies, worldwide distributed, during the 2010–2015 period. The overall results of this research are consistent with the value enhancing theory (as opposed with the shareholder expense theory). From the ESG factors, the governance factor seems to have the most important influence on the market value of the selected companies, regardless of the geographic region where they are located. Thus, our findings provide new insights into the influence of each ESG factor on the market value of the companies, providing a useful tool for stakeholders to measure economic impact but also for use as a predictor of economic performance.

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“…Omelka et al (2013) compare the financial distress model then Chen et al (1995) and Dolejšová (2015) stated that to obtain appropriate results, it is best to use more than two prediction models. Lee et al (2014) tested the Ohlson model and found that it can forecast future stock price movement with greater accuracy than any other prediction method. Lee et al (2014) findings are supported by Lundholm (1995).…”

Section: Tablementioning

confidence: 99%

FDPM after the global price crisis in the coal industry

Sawitri

2019

IJMEF

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Using the Altman model, the Springate model and the Ohlson model, this study aimed to determine if these financial distress prediction models (FDPM) would perform well in forecasting financial distress in the coal industry companies listed on the Indonesia Stock Exchange (IDX) from 2012 to 2016. Furthermore, this study compared which of these models is the most appropriate for predicting financial distress. The results showed that it is possible to use FDPM to forecast financial distress in relation to the coal companies listed on the IDX. The calculations obtained from the three methods show that some coal companies are experiencing significant financial distress, and the Springate model is the most appropriate FDPM for predicting financial distress.

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An Empirical Investigation of the Ohlson Model–A Panel Cointegration Approach

Cited by 14 publications

References 25 publications

The Use Of Ohlson's O-Score For Bankruptcy Prediction In Thailand

The Use Of Ohlson's O-Score For Bankruptcy Prediction In Thailand

The Impact of Esg Factors on Market Value of Companies From Travel and Tourism Industry

FDPM after the global price crisis in the coal industry

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