1,720,962 research outputs found

    Essays on risk, stock return volatility and R&D intensity

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    This thesis consists of three empirical essays studying the capital market implications of the accounting for R&D costs. The first empirical study (Chapter 2) re-visits the debate over the positive R&D-returns relation. The second empirical study (Chapter 3) examines the risk relevance of current R&D accounting. The third empirical study (Chapter 4) explores the joint impact of R&D intensity and competition on the relative relevance of the idiosyncratic part of earnings. Prior research argues that the positive relation between current R&D activity and future returns is evidence of mispricing, a compensation for risk inherent in R&D or a transformation of the value/growth anomaly. The first empirical study contributes to this debate by taking into account the link between R&D activity, equity duration and systematic risk. This link motivates us to employ Campbell and Vuolteenaho (2004)'s intertemporal asset pricing model (ICAPM) which accommodates stochastic discount rates and investors' intertemporal preferences. The results support a risk based explanation; R&D intensive firms are exposed to higher discount rate risk. Hedge portfolio strategies show that the mispricing explanations is not economically significant. The second empirical study contributes to prior research on the value relevance of financial reporting information on R&D, by proposing an alternative approach which relies on a return variance decomposition model. We find that R&D intensity has a significant influence on market participants' revisions of expectations regarding future discount rates (or, discount rate news) and future cash flows (or, cash flow news), thereby driving returns variance. We extend this investigation to assess the risk relevance of this information by means of its influence on the sensitivity of cash flow and discount rate news to the market news. Our findings suggest R&D intensity is associated with significant variation in the sensitivity of cash flow news to the market news which implies that financial reporting information on R&D is risk relevant. Interestingly, we do not establish a similar pattern with respect to the sensitivity of discount news to the market news which may dismiss the impact of sentiment in stock returns of R&D intensive firms. The third empirical study examines the effect of financial reporting information on R&D to the value relevance of common and idiosyncratic earnings. More specifically, we investigate the value relevance of common and idiosyncratic earnings through an extension of the Vuolteenaho (2002) model which decomposes return variance into its discount rate, idiosyncratic and common cash flow news. We demonstrate that the relative importance of idiosyncratic over common cash flow news in explaining return variance increases with firm-level R&D intensity. Extending this analysis, we find that this relation varies with the level of R&D investment concentration in the industry. Those results indicate that the market perceives that more pronounced R&D activity leads to outcomes that enable the firm to differentiate itself from its rivals. However, our results also suggest that the market perceives that this relation depends upon the underlying economics of the industry where the firm operates.University of Exeter Business Schoo

    How the information content of integrated reporting flows into the stock market

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    According to its advocates, integrated reporting (IR) aims to enhance firms' information environment by placing financial reporting into a much broader perspective in which interrelated non-financial information of firms' activities are taken into consideration. We examine whether this intended outcome of IR embeds into the stock pricing process using a sample of South African listed firms that mandatorily adopted IR in 2011. Unlike previous studies that explore market valuation implications of IR, we examine the channel through which the IR-related information flows into firm value. Specifically, we quantify the effects of revisions of expectation about future cash flows (prompted by financial reporting information), revisions of expectation about discount rates (prompted by non-financial reporting information) and their interconnectedness. We hypothesize and empirically show that the adoption of an IR approach prompted greater market revisions of expectations about future discount rates and a stronger interconnectedness between market revisions of expectations about future cash flows and discount rates. Thus, the change in the stock pricing process after the adoption of IR is determined by non-financial reporting information and its strong interconnectedness with financial reporting information. We also show that our results are stronger for firms with greater earnings opacity, suggesting that investors find IR more useful when firms' financial reporting is opaque. Results indicate to researchers, practitioners and regulators that IR enhances the firm-level information environment by providing informative non-financial reporting which is also well integrated with financial reporting

    Going Beyond Counting First Authors in Author Co-citation Analysis

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    The present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed

    Variations on the Author

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    “Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship

    Appropriate Similarity Measures for Author Cocitation Analysis

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    We provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis

    Dispelling the Myths Behind First-author Citation Counts

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    We conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more sophisticated methods

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    Factor Investing in Real Estate:The Performance of Smart Beta Strategies

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    This article is the first to develop and test factor-based (smartbeta) strategies in real estate using real estate investment trusts (REITs), the real estate equivalent of stocks. Following the equity pricing literature, the authors construct five factor portfolios—size, value, investment, profitability, and momentum—and analyze their performance from January 1993 to December 2020. The results support all factors except profitability. Building on these factors, the authors design smart beta strategies that integrate the REIT market portfolio with the factor portfolios to optimize asset allocation. These strategies consistently deliver superior risk-adjusted returns relative to a passive buy-and-hold investment in an all-REITs US Index. Furthermore, under three of five weighting schemes, the smart beta strategies outperform diversified multi-asset portfolios spanning real estate, equities, bonds, and commodities. This suggests that REIT-based factor strategies can serve as competitive, and at times superior, alternatives to broader cross-asset allocation frameworks
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