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The literature on project finance appraisal contains several ambiguities mainly concerning the correct method of equity cash flow (ECF) determination. This vagueness can lead to serious misevaluation of these projects. The purpose of this paper is to present and justify a correct method of ECF determination for project finance evaluation.

Based on the analysis of the specificity of project finance ventures and the study of existing literature, the authors propose a coherent model of ECF estimation that avoids misevaluating project finance ventures.

This paper demonstrates that the potential dividends methodology of ECF estimation, used commonly in the corporate finance world, leads to the erroneous valuation of project finance investments. Moreover, simulations demonstrate that the scale of this misevaluation is an increasing function of the debt covenant duration, the required rate of return, and the investment outlay dispersion over time. The proposed model of proper project finance valuation, despite inconsistency with assumptions of the fair value concept, is best suited for project finance venture appraisal, taking into consideration the inherently specific timing of the ECF.

This paper rectifies, clarifies, and extends the range of existing solutions for the project finance valuation and the application of the concepts of actual dividends and potential dividends in different valuation contexts. Furthermore, it proposes a simple and coherent method to value project finance ventures. Additionally, it offers evidence of the scale of NPV misevaluation in project finance, which occurs when the potential dividends approach is utilized.

While the existing studies largely suggest that valuation uncertainty benefits acquirers, who apply discounts to targets' value attributable to information asymmetry, the authors argue that the opposite may be the case.

Through multivariate econometric analysis of transaction data, the authors establish the link between the degree of valuation uncertainty measured by targets' track of public listing and acquisition premia. The authors use text-mining tools to measure acquirer–target similarity and control for its role in intermediating the posited empirical relationships.

Having analyzed 618 acquisitions involving listed targets from China, the authors find that acquirers pay higher valuation premia for the more recently listed and relatively younger companies than for those with a longer history since floatation. Similar patterns apply to valuation multiples. Higher valuations are partially attributable to premia for control, as acquirers are likelier to buy a majority stake in the recently listed firms, especially if the latter are similar to them. Such transactions take less time to complete and involve a transfer of larger share blocks despite the higher degree of information asymmetry and a frequent lack of targets' operational profitability. The authors also observe a significant premium for target–acquirer similarity: acquirers appear to rush deal completion due to possible overestimation of targets' potential and familiarity bias.

The authors show that acquisition premia may be driven by acquirers' proclivity to place risky investment bets on the growth potential of opaque targets. This pattern may partially explain frequent failures of mergers and acquisitions (M&A).

The authors document a persistent negative link between contemporaneous trade credit provision and subsequent firm-level operating performance.

Textual analysis of firms' profile descriptions is used to study the role of market segmentation and product differentiation in intermediating the nexus between trade credit and corporate performance. The paper relies on dynamic panel regression modeling to investigate the postulated empirical relationships. This approach allows to address endogeneity issues and to test a number of different model specifications.

Despite fueling short-term sales growth, the more generous trade credit terms are found to be associated with lower post hoc margins and declining overall business profitability. The market share is not affected by firms' proclivity to provide trade credit suggesting that the latter may not be effectively used as a long-term growth enhancement strategy. Firms' similarity to their competitors is found to play a salient role in altering the magnitude of the discovered negative relationship.

The authors find that the intensity of intra-industry competition measured by firms' similarity to their competitors magnifies the discovered negative trade credit-performance nexus. Therefore, generous trade credit may play a more important role in solidifying client–supplier relationships on the more segmented markets with a higher degree of product differentiation.

This paper aims to present an iterative algorithm that yields the amount of debt contracting/repayment or equity investment necessary to achieve the target capital structure. The model also helps to estimate the gains in shareholder value that result from financial restructuring process and lead to the optimal leverage ratio.

The paper maintains that certain benchmarks – i.e. industry average financial leverage and unlevered beta corrected for cash – make it possible to determine the parameters of the optimal capital structure for the company, so a failure to adjust to the target may result in value destruction.

The paper presents an iterative algorithm that yields the amount of debt contracting/repayment or equity investment necessary to achieve the target capital structure.

The proposed algorithm overcomes the methodological problems of existing approaches to the estimation of shareholder value gained through financial restructuring and implicitly solves the circularity problem in the calculation of the weighted average cost of capital.