Search results

This paper aims to identify a possible mismatch between the theory found in academic research and the practices of investment managers in Brazil.

The chosen approach is a field survey. This paper considers 78 survey responses from 274 asset management companies. Data obtained are analyzed using independence tests between two variables and multiple regressions.

The results show that most Brazilian investment managers have not adopted current best practices recommended by the financial academic literature and that there is a significant gap between academic recommendations and asset management practices. The modern portfolio theory is still more widely used than the post-modern portfolio theory, and quantitative portfolio optimization is less often used than the simple rule of defining a maximum concentration limit for any single asset. Moreover, the results show that the normal distribution is used more than parametrical distributions with asymmetry and kurtosis to estimate value at risk, among other findings.

This study may be considered a pioneering work in portfolio construction, risk management and performance evaluation in Brazil. Although academia in Brazil and abroad has thoroughly researched portfolio construction, risk management and performance evaluation, little is known about the actual implementation and utilization of this research by Brazilian practitioners.

This study aims to contribute to the field of customer portfolio management by proposing a novel approach rooted in dialectic critical realism (DCR). DCR, as an ontological theory, enables a fundamental reimagining of customer portfolio management as a dialectic process. The conceptualized dialectic portfolio management is motivated by the concept of “absence”, akin to Hegelian “antithesis”, which highlights limitations, problems and tensions in portfolio management. In essence, “absence” serves as a diagnostic tool that directs portfolio actions towards resolving problems by pursuing a more comprehensive “totality”, similar to the Hegelian notion of “synthesis”.

This conceptual paper theorizes DCR in business marketing and customer portfolio management.

DCR conceptualizes customer portfolios as relational structures characterized by omissions and tensions. These issues are addressed through a dialectic synthesis aimed at achieving a more comprehensive “totality”. Consequently, DCR guides portfolio management to continually re-think the connections and distinctions that define a portfolio within its network context. This dialectic process is facilitated by a novel vocabulary that enhances the understanding of network and portfolio relations, incorporating concepts such as “intrapermeations”, “existential constitutions”, “intra-connections” and “intensive” and “extensive” portfolio practices.

This study aims to foster a fresh and process-oriented perspective on portfolio management, drawing inspiration from the growing demand for enriched dialectic theorizing within the realm of business marketing. The adoption of a dialectic process orientation based on DCR revolutionizes the comprehension of portfolio management by fundamentally reimagining the underlying ontological assumptions that underpin the existing body of literature on customer portfolios. Moreover, DCR asserts that ethical considerations are inextricably linked to human experiences and associated practices, emphasizing ethics as an integral component of customer portfolio management.

This research mainly intends to ascertain the stimulus of investor investment tendencies on the amount of capital investment in the share market.

Utilizing a sample of 477 individual investors who actively trade on the Bangladesh capital market, this empirical study was conducted. The objective of this examination is to ascertain the investment trading behavior of retail investors in the Bangladesh capital market using multiple regression, hypothesis testing and correlation analysis.

The coefficients of market categories, preferred share price ranges and investment source reveal negative predictor correlations; all predictors are statistically significant, with the exception of investment source. Positive predictive correlations exist between investor category, financial literacy degree, investment duration, emotional tolerance level, risk consideration, investment monitoring activities, internal sentiment and correct investment selection. Except for risk consideration and investment monitoring activities, all components have statistically significant predictions. The quantity of capital invested in the stock market is heavily influenced by the investment duration, preferred share price ranges, investor type, emotional toleration level and decision-making accuracy level.

This investigation was conducted exclusively with Bangladeshi individual stockholders. Therefore, the existing study can be extended to institutional investors and conceivably to other divisions. It is possible to conduct this similar study internationally. And the query can enlarge with more sample size and use a more sophisticated econometric model. Despite that the outcomes of this study help the regulatory authorities to arrange more informative seminars and consciousness programs.

The conclusions have practical implications since they empower investors to modify their portfolios based on elements including share price ranges, investment horizons and emotional stability. To improve chances of success and reach financial objectives, they stress the significance of bettering financial understanding, active monitoring and risk analysis. Results can also be enhanced by distributing ownership over a number of market sectors and price points. The results highlight the value of patience and giving potential returns enough time.

This study on the trading behavior of investors in Bangladesh is unique and based on field study, and the findings of this study will deliver information to the stakeholders of the capital market regarding the investors’ trading behavior belonging to different categories, financial literacy level, investment duration, emotional tolerance level and internal feeling.

This study aims to organise and present the development of asset pricing models in the international environment. The stock market integration and cross-listing lead us to another objective of bibliometric analysis for “International Asset Pricing” to provide a complete overview and give scope and directions for future research.

Web of Science database is used to search with “International Asset Pricing.” Of 3,438 articles, 2,487 articles are selected for the final bibliometric analysis. Various research such as citation analysis, keyword analysis, author’s and corresponding author's analysis have been conducted.

The bibliometric analysis finds that the USA comes out to be the country where the maximum research was conducted on the topic. The keyword analysis was also analysed to evaluate the significant areas of the research. Risk, return and international asset pricing are the most frequently used keywords. The year 2020 has the maximum number of published research articles and citations due to the change in the market structure worldwide and the effect of Covid-19 across the world.

The present paper provides the collection, classification and comprehensive analysis of “International Asset pricing,” which may help the academicians, researchers and practitioners for future research for the relevant subject area.

This study examines the role of behavioural factors, such as confidence, optimism, pessimism and rational expectation, in affecting investment decisions in the Pakistani stock market.

Using daily trading data of Karachi Stock Exchange-100 index from January 2012 to December 2015, different regression models, including descriptive statistics and stationarity tests, are performed.

Results indicate that stock market trading has suffered from pessimistic behaviour of investors. In the first model, the authors find a positive sign of confidence and negative sign of optimism with the trading volume. The second model shows a positive role of confidence and rational expectations in affecting the trading volume in daily, Monday and Friday samples. The results of the third model show a negative sign of both optimism and rational expectation with the trading volume. Furthermore, the next model shows a negative sign of confidence combined with pessimism while testing their relationship with the trading volume. Finally, results of the final model suggest that optimism negatively affects the trading volume, and on the other hand, pessimism has a positive impact on the trading volume.

The method and empirical testing of behavioural biases and their relationship with economic variable used in this study seem to be a promising way to better understand the role of psychology in deriving financial decisions for academics and policymakers.

This study uses secondary data for measuring behavioural biases and decomposes the effect between rational expectation and behavioural biases.

The purpose of this paper is to test the relationship between the annual income earned by the investors and eight behavioural biases exhibited by the investors such as mental accounting, anchoring, gambler’s fallacy, availability, loss aversion, regret aversion, representativeness and overconfidence.

The relationship is derived based on a questionnaire survey conducted on 436 secondary equity investors residing in Chennai, India.

Analysis of variance test was performed on the normalised and non-normalised version of the biases divided in terms of the annual income earned by the investor. The test found that for the significant biases except the overconfidence bias, the investors with higher annual income were less prone to the biases when compared to investors with lower annual income. On the other hand, with respect to the overconfidence bias, the investors with higher annual income were prone to exhibit overconfidence bias when compared to the investors with lower annual income. Correlation analysis showed that the investors with high annual income were more likely to exhibit higher overconfidence bias but lower representativeness, loss aversion, availability and mental accounting biases.

A contribution in the financial and economic front which would benefit the financial advisors to now consider the income earned by the clients as an important factor while giving financial advice to the clients and while guiding them about the biases they are prone to exhibit.

This study aims to examine the ability of clean energy stocks to provide cover for investors against market risks related to climate change and disturbances in the oil market.

The study adopts the feasible quasi generalized least squares technique to estimate a predictive model based on Westerlund and Narayan’s (2015) approach to evaluating the hedging effectiveness of clean energy stocks. The out-of-sample forecast evaluations of the oil risk-based and climate risk-based clean energy predictive models are explored using Clark and West’s model (2007) and a modified Diebold & Mariano forecast evaluation test for nested and non-nested models, respectively.

The study finds ample evidence that clean energy stocks may hedge against oil market risks. This result is robust to alternative measures of oil risk and holds when applied to data from the COVID-19 pandemic. In contrast, the hedging effectiveness of clean energy against climate risks is limited to 4 of the 6 clean energy indices and restricted to climate risk measured with climate policy uncertainty.

The study contributes to the literature by providing extensive analysis of hedging effectiveness of several clean energy indices (global, the United States (US), Europe and Asia) and sectoral clean energy indices (solar and wind) against oil market and climate risks using various measures of oil risk (WTI (West Texas intermediate) and Brent volatility) and climate risk (climate policy uncertainty and energy and environmental regulation) as predictors. It also conducts forecast evaluations of the clean energy predictive models for nested and non-nested models.

To comply with the adopted Paris Agreement, global finance flows must be measured against climate scenarios consistent with possible pathways towards limiting global warming to 2°C or less. For this, there must be proven and accepted accounting principles for assessing financial plans of climate relevant actors against climate models. As there are a variety of data sources describing the financial plans of relevant actors, these principles must accommodate a variety of reported information, while still yielding relevant metrics to different stakeholders. The paper aims to discuss these issues.

A set of accounting principles tested by governments, financial supervisory bodies and both institutional investors and mangers, covering global-listed equity and corporate bond investment is described.

The application illustrates that a common set of accounting principles can act across both asset classes and provide relevant metrics to multiple stakeholders.

The principles require data of varying quality and are ultimately unverified. Thus, the definitive quality of the output metrics is uncertain and is yet to be characterized. The principles are yet to be applied to the credit market as the information is seldom publicly available, but it too plays an important role in the required market transition and therefore must be incorporated into these guiding principles of analysis.

The principles allow for standardised assessment of financial flows of equity and corporate debt with global climate scenarios.

It illustrates the acceptance of a common set of accounting principles that is relevant across different actors and asset classes and summarizes the principles underlying the first climate finance scenario analyses.

The purpose of this paper is to identify how project portfolio selection (PPS) methods have evolved and which approaches are more suitable for radical innovation projects. This paper addressed the following research question: how have the selection approaches evolved to better fit within radical innovation conditions? The current literature offers a number of selection approaches with different and, in some cases, conflicting nature. Therefore, there is a lack of understanding regarding when and how to use these approaches in order to select a specific type of innovation projects (from incremental to more radical ones).

Given the nature of the research question, the authors perform a systematic literature review method and analyze 48 portfolio selection approaches. The authors then classified and characterized these articles in order to identify techniques, tools, required data and types of examined projects, among other aspects.

The authors identify four key features related to the selection of radical innovation projects: dynamism, interdependency management, uncertainty treatment and required input data. Based on the content analysis, the authors identified that approaches based on different sources and nature of data are more appropriated for uncertain conditions, such as behavioral methods, information gap theory, real options and integrated approaches.

The research provides a comprehensive framework about PPS methods and how they have been evolving over time. This portfolio selection framework considers the particular aspects of incremental and radical innovation projects. The authors hope that the framework contributes to reinvigorating the literature on selection approaches for innovation projects.

Investor risk perception is a personalized judgement on the uncertainty of returns pertaining to a financial instrument. This study identifies key psychological and demographic factors that influence risk perception. It also unravels the complex relationship between demographic attributes and investor's risk attitude towards equity investment.

Exploratory factor analysis is used to identify factors that define investor risk perception. Multiple regression is used to assess the relationship between demographic traits and factor groups. Kruskal–Wallis test is used to ascertain whether the factors extracted differ across demographic categories. A risk perception framework based on these findings is developed to provide deeper insight.

There is evidence of the relationship and influence of demographic factors on risk propensity and behavioural bias. From this study, it is apparent that return expectation, time horizon and loss aversion, which define the risk propensity construct, vary significantly based on demographic traits. Familiarity, overconfidence, anchoring and experiential biases which define the behavioural bias construct differ across demographic categories. These factors influence the risk perception of an individual with respect to equity investments.

The reference for the framework of this study is limited as there has been no precedence of similar work in academia.

This paper establishes that information seekers make rational decisions. The paper iterates the need for portfolio managers to develop and align investment strategies after evaluation of investors' risk by including these behavioural factors, this can particularly be advantageous during extreme volatility in markets that concedes the possibility of irrational decision making.

This study highlights that regulators need to acknowledge the investor's affective, cognitive and demographic impact on equity markets and align risk control measures that are conducive to market evolution. It also creates awareness among market participants that psychological factors and behavioural biases can have an impact on investment decisions.

This is the only study that looks at a three-dimensional perspective of the investor risk perception framework. The study presents the relationship between risk propensity, behavioural bias and demographic factors in the backdrop of “information” being the mediating variable. This paper covers five characteristics of risk propensity and eight behavioural biases, such a vast coverage has not been attempted within the academic realm earlier with the aforesaid perspective.