Accounting report
Fahime Ebrahimi; Mohammad Hosein Setayesh; Hamidreza Zareifard
Abstract
Prospect theory explains how individuals’ feelings and preferences influence their decision-making. The purpose of this research was to investigate earnings manipulation incentives within companies listed in Tehran Stock Exchange using fourfold pattern of risk attitudes provided by the cumulative ...
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Prospect theory explains how individuals’ feelings and preferences influence their decision-making. The purpose of this research was to investigate earnings manipulation incentives within companies listed in Tehran Stock Exchange using fourfold pattern of risk attitudes provided by the cumulative prospect theory. The period of this research was 6 years, from 2013 to 2018 and included 695 observations. Hypothesis testing using logistic regression, with the average competitor performance within the industry as the reference point, revealed a significant positive (vs. negative) effect of management’s loss (vs. gain) estimates relative to the reference point on earnings manipulation. In other words, when management’s estimate of the likelihood of loss relative to the reference point is high (vs. low), the likelihood of earnings manipulation increases (vs. decreases). Furthermore, when management’s estimate of the likelihood of gain relative to the reference point is low (vs. high), the likelihood of earnings manipulation increases (vs. decreases). The findings of research also provided evidence for loss-aversion among managers. Therefore, the evidence suggests that the cumulative prospect theory can be utilized to explain managerial incentives for earnings manipulation.
Ali Saghafi; Roohollah Farhadi; Mohammad Taghi Taghavi Fard
Volume 12, Issue 45 , April 2015, , Pages 9-38
Abstract
According to Prospect Theory, Investors have different behaviors in theprofit and loss situations and indeed their trading behavior is different in bulland bear markets. This study uses quantile regression model (in differentquartiles) and OLS model to estimate beta of 180 firms. Results showed thatfirst, ...
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According to Prospect Theory, Investors have different behaviors in theprofit and loss situations and indeed their trading behavior is different in bulland bear markets. This study uses quantile regression model (in differentquartiles) and OLS model to estimate beta of 180 firms. Results showed thatfirst, equity total risk (standard deviation) increase in Upper quartile andsecond, stocks beta changes in different quartiles and by moving fromquartile 0.25 to quartile 0.75, systematic risk (beta) increases significantly.Linear regression model and Quantile regression model show also thatunexpected variance can explain excess return at least similar to expectedvariance. The results can also be interpreted with both Insight of standardfinance and insight of behavioral finance. In standard finance area, riskreturnpositive relation that exists in upper quintiles is consistent with longrun growth of economy. Moreover, negative relation between return and riskin lower quintiles imply more uncertainty and as a result causing stockreturns to fall. In behavioral finance area, regime-dependent behavior ofslope coefficients is consistent with prediction of Prospect theory ofinvestor’s behaviors around the reference point.
roohollah farhadi
Abstract
According to Prospect Theory, Investors have different behaviors in the profit and loss situations and indeed their trading behavior is different in bull and bear markets. This study uses quantile regression model (in different quartiles) and OLS model to estimate beta of 180 firms. Results showed that ...
Read More
According to Prospect Theory, Investors have different behaviors in the profit and loss situations and indeed their trading behavior is different in bull and bear markets. This study uses quantile regression model (in different quartiles) and OLS model to estimate beta of 180 firms. Results showed that first, equity total risk (standard deviation) increase in Upper quartile and second, stocks beta changes in different quartiles and by moving from quartile 0.25 to quartile0.75, systematic risk (beta) increases significantly. Linear regression model and Quantile regression model show also that unexpected variance can explain excess return at least similar to expected variance. The results can also be interpreted with both Insight of standard finance and insight of behavioral finance. In standard finance area, risk-return positive relation that exists in upper quintiles is consistent with long run growth of economy. Moreover, negative relation between return and risk in lower quintiles imply more uncertainty and as a result causing stock returns to fall. In behavioral finance area, regime-dependent behavior of slope coefficients is consistent with prediction of Prospect theory of investor’s behaviors around the reference point.
