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This paper aims to examine the valuation precision of composite models in each of six key industries in South Africa. The objective is to ascertain whether equity-based composite multiples models produce more accurate equity valuations than optimal equity-based, single-factor multiples models.

This study applied principal component regression and various mathematical optimisation methods to test the valuation precision of equity-based composite multiples models vis-à-vis equity-based, single-factor multiples models.

The findings confirmed that equity-based composite multiples models consistently produced valuations that were substantially more accurate than those of single-factor multiples models for the period between 2001 and 2010. The research results indicated that composite models produced up to 67 per cent more accurate valuations than single-factor multiples models for the period between 2001 and 2010, which represents a substantial gain in valuation precision.

The evidence, therefore, suggests that equity-based composite modelling may offer substantial gains in valuation precision over single-factor multiples modelling.

In light of the fact that analysts’ reports typically contain various different multiples, it seems prudent to consider the inclusion of composite models as a more accurate alternative.

This study adds to the existing body of knowledge on the multiples-based approach to equity valuations by presenting composite modelling as a more accurate alternative to the conventional single-factor, multiples-based modelling approach.

Surprisingly little is known of the various methods of security analysis used by financial analysts with industry-specific knowledge. Financial analysts’ industry knowledge is a favored and appreciated attribute by fund managers and institutional investors. Understanding analysts’ use of industry-specific valuation models, which are the main value drivers within different industries, will enhance our understanding of important aspects of value creation in these industries. This paper contributes to the broader understanding of how financial analysts in various industries approach valuation, offering insights that can be beneficial to a wide range of stakeholders in the financial market.

This paper systematically reviews existing research to consolidate the current understanding of analysts’ use of valuation models and factors. It aims to demystify what can often be seen as a “black box”, shedding light on the valuation tools employed by financial analysts across diverse industries.

The use of industry-specific valuation models and factors by analysts is a subject of considerable interest to both academics and investors. The predominant model in several industries is P/E, with some exceptions. Notably, EV/EBITDA is favored in the telecom, energy and materials sectors, while the capital goods industry primarily relies on P/CF. In the REITs sector, P/AFFO is the most commonly employed model. In specific sectors like pharmaceuticals, energy and telecom, DCF is utilized. However, theoretical models like RIM and AEG find limited use among analysts.

This is the first paper systematically reviewing the research on analyst’s use of industry-specific stock valuation methods. It serves as a foundation for future research in this field and is likely to be of interest to academics, analysts, fund managers and investors.

Increased economic activity in sub-Saharan Africa (SSA) has given rise to increased demand for port development. Given the often scarce availability of national public funding, port institutional reform programmes have been implemented to pave the way for the inclusion of external port investors. Notwithstanding this fact, some sub-Saharan African Governments remain institutionally locked into the notion that state-owned enterprises remain an appropriate vehicle for port terminal operations. This, despite the fact that terminal operational concessions globally and within the continent of Africa are increasingly being managed by global terminal operators. Given this context, this study aims to evaluate different port valuation and funding strategies. Two research questions form the core of this research: what is the financial value of a concession? What is the most cost advantageous funding strategy? The methodology is applied to the development of a two-berth container terminal in SSA.

After reviewing a range of financial valuation and funding techniques, the study presents valuation and funding model applicability-fit tests. Thereafter, a suitable valuation technique is selected and applied to the case study providing a concession valuation. Different funding strategies are applied to the valuation model to determine the cost implications of each funding instrument given the local context and institutional constraints applicable to SSA. Finally, the study discusses the significance of the results to potential SSA port investors by highlighting the impact of each funding approach on key financial metrics.

The study presents a range of financial investment appraisal results for the case study concession in consideration of four specific funding strategies. The highest concession valuation could be attributed to a higher debt ratio as a principal funding strategy. In addition, this funding approach (100% debt) realised the shortest payback period and the highest internal rate of return values. The authors, however, maintain that the optimal funding strategy for a concession depends ultimately on the financial goals of the investor.

This research makes a contribution to the existing literature on port finance and development by presenting a structured approach to the evaluation of the valuation and funding techniques, which can be used in terminal development subject to the specific local context and institutional constraints (in this case applicable to SSA). The study provides practical insight into the potential cost of the considered terminal concession for private or public sector participants and a view of the most cost advantageous funding strategy available for interested investors.

The purpose of this paper is to examine the influence of earnings persistence and earnings power on equity valuation.

The purposive sampling method was applied to determine the samples of selected 100 firms. This study employed secondary data obtained from the annual reports and financial statements of consumer goods firms listed on the Indonesian Stock Exchange for the period 2010–2014. The analysis technique used a multiple regression analysis.

The study result shows that, partially, earnings persistence and earnings power affect equity valuation by investors. Earnings persistence has a negative influence, whereas earnings power has a positive influence on equity valuation.

This study throws additional lights on equity valuation specific to consumer goods industries.

This paper aims to investigate the relevance of two groups of valuations models as follows: the accounting models based on the residual income (RIM) and the standard market model, on equity price, return and volatility relevance.

The models are tested on companies traded on Palestine exchange from 2009 to 2018, using panel regression analysis. Two-price and two-return models derived from RIM to compare with the market model and four volatility models.

The standard RIM outperformed other models in equity price modeling. The dividend discount model (DDM) outperformed the rest of the models in terms of return estimation. However, the authors find that the market model can explain equity variance better than RIM and DDM models.

For investors, market beta does not necessarily capture all relevant factors of value and traditional financial statements are still important in providing relevant information and different models are used for different values perspectives (price, return and volatility).

Previous studies focus on comparing the price and return relevance of accounting-based models (RIM and cash flow models). Three aspects differentiate this paper and contribute to its originality, namely, the uniqueness of the context, incorporating the market model into the picture along with the accounting-based models and adding Volatility dimensions of relevance.

The purpose of this paper is to explore how non-professional investors (NPIs) with varying levels of financial sophistication interpret and perceive corporate disclosures and management credibility, specifically risk factors, when those disclosures are presented in readable and less-readable formats.

The paper uses an online experiment to test hypotheses related to the effects of financial sophistication (measured) and readability (manipulated) on NPIs’ equity valuations and perceptions of management credibility (competence and trustworthiness).

Increased readability appears to counteract less-sophisticated NPIs’ conservatism in equity valuations, such that they are not statistically significantly different from more-sophisticated NPIs’ equity valuations. Further, less-sophisticated NPIs judge management as less competent when disclosures are less readable, while more-sophisticated NPIs judge management as more competent when disclosures are less readable.

The paper has important implications for the SEC’s regulations related to plain English requirements for risk factor and other corporate disclosures. Financial sophistication varies among NPIs, and readability appears to influence these individuals in different ways.

The SEC’s Concept Release (April 13, 2016) acknowledges the need to update and improve risk factor disclosure regulations. This study provides evidence that contributes to those decisions.

The paper extends the research on processing fluency, by examining readability of disclosures with a consistent tone (negative). The NPIs surveyed are directly representative of the population of interest for risk factor disclosure regulations.