بررسی‌های حسابداری و حسابرسی (Aug 2023)

The Role of Financial Distress Factor in Explaining Profitability of Value and Size Premiums

  • Negar Khosravipour,
  • Ali Esmaeilzade,
  • Mohamad Rouhi

DOI
https://doi.org/10.22059/acctgrev.2023.351045.1008757
Journal volume & issue
Vol. 30, no. 2
pp. 239 – 261

Abstract

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Objective: This study aims to elucidate the profitability of value premium and size premium anomalies by employing the CHS score by Campbell et al. (2008) as the market-based financial distress indicator and Ohlson's O score (1980) as the accounting-based financial distress indicator.CHS‌ score is a reduced-form econometric model to predict financial distress at short and long horizons. Among the market anomalies, value and size premiums have attracted more attention. Previous research noticed the existence of value premiums in stocks and found that value stocks have higher average returns compared to growth stocks. A value stock refers to shares of a company that appears to trade at a lower price relative to its fundamentals. Common characteristics of value stocks include high dividend yield, high book value to market value ratio, and a low P/E ratio. However, growth stocks often look expensive, trading at a low book value to market value ratio. In addition, researchers highlighted the existence of size premium where small stocks perform better than large stocks. These phenomena led to the formation of investment strategies based on value and size premiums. Value premium strategy involves buying value stocks and selling growth stocks, while size premium strategy entails buying small stocks and selling big stocks. Methods: In this study, the required data was collected from a sample consisting of 168 companies listed on the Tehran Stock Exchange and Iran Farabourse during the period from October 22, 2011, to September 22, 2021. To investigate the relationship between stock excess returns and risk factors, a total of three models were used: 1) Fama and French three-factor model, 2) the augmented three-factor model including the CHS score, and 3) the augmented three-factor model including the O score. Results: According to the findings of this study, the inclusion of the financial distress factor in the Fama and French three-factor model, regardless of the criterion that is used to measure this factor, improves the performance of this model in explaining the fluctuations in the average returns of companies listed on Tehran Stock Exchange and Iran Farabourse. In the meantime, the CHS score, compared to the O score, has a greater contribution to increasing the explanatory power of the mentioned model. Additionally, it is found that both in the original model of Fama and French and the augmented versions of this model, the value premium is mainly seen among value stocks, both small and big ones. The size effect, which is seen in all groups of stocks before the inclusion of the financial distress variable in the mentioned model, after augmenting this model, although loses its importance among big-value stocks, is still an influential factor in explaining the fluctuations of the average returns of small value stocks, small growth stocks, and big growth stocks. Conclusion: The results prove the existence of a negative and highly significant relationship between the financial distress risk and the excess returns of portfolios formed based on size and book value to market value, confirming that in the long run, financially distressed companies compared to healthy companies, realize lower excess returns. This finding can be of interest to the Securities and Exchange Organization (SEO), audit institutions, investors, and creditors.‌ It is suggested that researchers use more dynamic versions of asset pricing models and other indicators of financial distress to analyze and explain fluctuations in stock returns in future research. In this regard, researchers can refer to Fama and French five-factor model (2015) and the newer versions of the capital asset pricing model (CAPM), and by including the factor of financial distress in these models, compare the power of the mentioned models in explaining the fluctuations of stock returns

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