Search Results (3)

We investigate the importance of bankruptcy risk in discounted cash flow (DCF) equity valuation. Our analyses first show how bankruptcy risk is incorporated in DCF valuation, where investment risk is captured by cash flow certainty equivalents. Within this general setting, we find that bankruptcy risk can be captured by discounting factors incorporating period-specific bankruptcy probabilities, allowing the numerators in a DCF valuation model to follow a binary random walk. Elaborating a model of this kind, we assess the value of the equity holders’ limited liability right (the equity holders’ right to hand over the firm to its creditors if bankruptcy occurs). Two valuation models commonly used in academic research and professional practice—the Dividend Discount Model (DDM) and the Residual Income Valuation (RIV) model—are addressed specifically. Our analyses show that bankruptcy probabilities are important for the estimation of the value drivers in both models. Even if bankruptcy probabilities are as low as 0.02, equity values might be severely exaggerated if bankruptcy risk is ignored in DDM or RIV. In particular, this holds for firms expected to have high future growth (conditioned on firm survival). For the RIV model to properly capture bankruptcy risk, we identify “bankruptcy event accounting principles” and an additional term that must be included in the model. We also show that bankruptcy risk under certain conditions can be handled through a specific calibration of the discounting rate/-s in all DCF models, allowing the value drivers—i.e., future dividends or residual income—to be forecasted conditioned on firm survival. Full article

In this paper, we test whether the short-run econometric conditions for the basic assumptions of the Ohlson valuation model hold, and then we relate these results with the fulfillment of the short-run econometric conditions for this model to be effective. Better future modeling motivated us to analyze to what extent the assumptions involved in this seminal model are not good enough approximations to solve the firm valuation problem, causing poor model performance. The model is based on the well-known dividend discount model and the residual income valuation model, and it adds a linear information model, which is a time series model by nature. Therefore, we adopt the time series approach. In the presence of non-stationary variables, we focus our research on US-listed firms for which more than forty years of data with the required cointegration properties to use error correction models are available. The results show that the clean surplus relation assumption has no impact on model performance, while the unbiased accounting property assumption has an important effect on it. The results also emphasize the uselessness of forcing valuation models to match the value displacement property of dividends. Full article

This study investigates that how investment banks select alternative valuation models to price Initial Public Offerings (IPOs) and examine the value-relevance of each valuation model using the data of 88 IPOs listed on the Pakistan Stock Exchange (PSX) during 2000–2016. This study investigates that investment banks used Dividend Discount Model (DDM), Discounted Cash Flow (DCF) and comparable multiples valuation models on the basis of firm-specific characteristics, aggregate stock market returns and volatility before the IPOs. In this study, a binary logit regression model is used to estimate the cross-sectional determinants of the choice of valuation models by investment banks. The results reveal that underwriters are more likely to use DDM to value firms that have dividends payout trail. The investment banks select DCF when valuing the younger firms, that have more assets-in-tangible, firms that have negative sales growth and positive market returns before the IPO; while comparable multiples are used for mature firms and firms that have less assets-in-tangible. Furthermore, this study also used OLS regressions to examine the value-relevance of each valuation model and Wald-test to examine the predictive power of cross-sectional variation in the market values. The findings unveil that P/B ratio has highest but DCF has lowest predictive power to market values. The Wald-test results depict that none of the valuation methods produces an unbiased estimate of market values. Full article