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Framed within global policy debates over the need for private financial flows to align with the capital requirements of the Paris Agreement, this paper examines UK asset managers in their approaches to disclosing and managing climate risk. This paper identifies and evaluates climate risk management practices among this under-researched investor group in their capacity to address fundamental behavioural obstacles to low-carbon investment.

This paper takes an inductive approach to document analysis, applying content and thematic analysis to the annual disclosures of the 28 largest UK asset managers (by assets under management), including the investment management arms of insurance and pension companies.

The main takeaway from this research is that today’s climate risk management strategies hold potential to effectively address traditionally climate risk-averse investor behaviour and investment processes in the UK asset management context. However, this research finds that the use of environmental, social and governance (ESG) investment strategies to mitigate climate risks is a “grey area” in which climate risk management practices are undefined within broad sustainability and responsible investment agendas. In doing so, this paper invites further research into the extent to which climate risks are considered in ESG investment.

This paper contributes to research in sustainable finance and behavioural finance, by identifying the latest climate risk management techniques used among UK-headquartered asset managers and uniquely evaluating these in their capacity to address barriers to low-carbon investment arising from organisational behaviours and processes.

With the introduction of the Markets in Financial Instruments Directive (MiFID), financial institutions are faced with many investor protection provisions; this has a major impact on the day-to-day operations of private banks, which provide investment services to predominately retail or non-professional investors. The purpose of this paper is to determine how MiFID provisions regarding investor protection with respect to suitability are complied with in practice by private banks.

Based on interviews with 25 representatives of private banks from 10 different European Union (EU) member states, the researchers have determined how these provisions are fulfilled and associated risks mitigated. Mapping out the suitability requirements of MiFID and comparing them with how these have been operationalised, we arrive at the question of whether this leads to a level playing field and investor protection by different private banks.

Although MiFID is trying to achieve a level playing field between the EU member states, this study shows that this has not been achieved in all areas. Investor protection requirements from MiFID are interpreted and operationalised differently. Although these differences are sometimes small, sometimes they are larger and affect the way the investor is served and suitability determined.

This research provides a unique insight into the way private banks in Europe have implemented the MiFID II requirements and gives insight into best practices. For the future, this research can serve as a prelude to in-depth follow-up research on the implementation of EU provisions.

This paper aims to analyze the effectiveness of aid in stimulating investment using different measures of aid and up-to-date panel time-series techniques. This study controls for endogeneity by using dynamic ordinary least squares (DOLS) and minimizes the risk of running a spurious long-run relationship by using series that are cointegrated. This paper finds evidence that aid promotes investment in countries with good institutional quality and gain interesting insights on the influence of country characteristics and the amount of aid received. Aid is ineffective in countries with unfavorable country characteristics such as a colonial past, being landlocked and with large distances to markets. Aid can boost investment in regions that receive high (above-median) amounts of aid such as Africa and the Middle East but not in regions that receive low amounts of aid. Investment-targeted aid is effective but non-investment-related aid can also enhance investment.

Regressions on the aid-investment nexus are based on either a rather simple (115 countries) or an extended/augmented investment model (91 countries). The data covers the period of 1973–2011 and 1985–2011 if the institutional quality is included. This study estimates the relationship between aid and investment by applying the DOLS/dynamic feasible generalized least squares technique which is based on a long-run relationship of the regression variables (cointegration). In this framework, this paper incorporates country-fixed effects, control for endogeneity, autocorrelation and take heteroscedasticity and cross-country correlation of the residuals into account.

This study finds empirical evidence that aid promotes investment in countries with good institutional quality and gain interesting insights on the role played by country characteristics and the amount of aid received. Aid is ineffective in countries with unfavorable country characteristics such as the colonial past, being landlocked, distant from markets. Aid can boost investment in regions that receive high (above-median) amounts of aid such as Africa and the Middle East. Investment-targeted aid is effective but non-investment-related aid also able to enhance investment.

The study looks at the investment to gross domestic product (GDP) ratio (including domestic investment and foreign direct investment (FDI)) and, hence does not disentangle these factors. It looks at the net effect (positive and negative impact together) and, therefore does not allow to identify the direct crowding out the impact of aid. Of course, if this paper finds that aid has a negative impact on investment, it is clear that aid must have crowded out either domestic investment or FDI or both.

The authors think that it is relevant to have identified the circumstances and settings in which foreign aid can be particularly effective and in which foreign aid needs accompanying measures that improve the effectiveness of aid. Also, it is relevant that the relative amount of aid received (aid-to-GDP ratio) must be quite high so that aid can increase investment.

This study sees that the least developed, low-income countries and (in terms of regions) the sub-Saharan Africa countries benefit from aid. This is very desirable. This paper further sees that higher relative amounts of aid do help more and that it is helpful to care about a better institutional quality in developing countries. Hence, this study provides some support for the desirability of aid.

The paper was done very diligently, and this study is very confident that the results are robust. This paper is also confident that this study has studied the long-run (which is of special importance) nexus between aid and investment. The estimation technique used is original, as it combines regular DOLS with corrections for autocorrelation and cross-section dependence.

This paper aims to address two fundamental questions: (1) How has Bahrain's industrial policy evolved during the 21st century? and (2) what factors contribute to this evolution?

Utilizing secondary data, this paper identifies key decision-makers responsible for economic policy in Bahrain and delineates the evolution of Bahrain's industrial policy throughout the 21st century. Subsequently, it employs a series of interviews with elite civil servants engaged in the formulation and implementation of Bahrain's economic policies to understand the reasons behind the observed changes.

Since assuming the role of Crown Prince in 1999, Sh. Salman bin Hamad Al Khalifa has been the key economic decision-maker in Bahrain. During the 21st century, Bahrain has shifted away from decisions closely aligned with the Washington Consensus towards those more in line with classical industrial policy. Interviews reveal that the private sector's underperformance in job creation, coupled with fiscal pressures, has driven this departure from the Washington Consensus. Moreover, the early successes of the interventionist Saudi Vision 2030 and Bahrain's own success in technocratically managing the COVID-19 pandemic have accelerated this transition.

Insights into the determinants of Bahrain's industrial policy can guide policymakers in refining future strategies. Recognizing the positive role of intellectual developments in academic economics literature becomes crucial for informed decision-making.

This paper fills a gap in the existing literature by providing answers to its research questions, particularly considering the significant changes witnessed in Bahrain's industrial policy post-pandemic.

People’s tendency to overestimate their ability to control random events, known as illusion of control, can affect financial decisions under uncertainty. This study developed an artifactual field experiment on illusion of control for a farm machinery investment.

In an experiment with two treatments, the individual farmer was either given or not given a sense of control over a random outcome. After each decision, the authors elicited perceived control, and a questionnaire collected additional indirect measures of illusion of control from 78 German farmers and 10 farm advisors.

The results did not support preregistered hypotheses of the presence of illusion of control. This null result was robust over multiple outcomes and model specifications. The findings demonstrate that cognitive biases may be small and difficult to replicate.

The sample is not representative for the German farming population. The authors discuss why the estimated treatment effect may represent a lower bound of the true effect.

Illusion of control is well-studied in laboratory settings, but little is known about the extent to which farmers’ behavior is influenced by illusion of control.

From the buying club’s perspective, the transfer of a player can be interpreted as an investment from which the club expects uncertain future benefits. This paper aims to develop a decision-oriented approach for the valuation of football players that could theoretically help clubs determine the subjective value of investing in a player to assess its potential economic advantage.

We build on a semi-investment-theoretical risk-value model and elaborate an approach that can be applied in imperfect markets under uncertainty. Furthermore, we illustrate the valuation process with a numerical example based on fictitious data. Due to this explicitly intended decision support, our approach differs fundamentally from a large part of the literature, which is empirically based and attempts to explain observable figures through various influencing factors.

We propose a semi-investment-theoretical valuation approach that is based on a two-step model, namely, a first valuation at the club level and a final calculation to determine the decision value for an individual player. In contrast to the previous literature, we do not rely on an econometric framework that attempts to explain observable past variables but rather present a general, forward-looking decision model that can support managers in their investment decisions.

This approach is the first to show managers how to make an economically rational investment decision by determining the maximum payable price. Nevertheless, there is no normative requirement for the decision-maker. The club will obviously have to supplement the calculus with nonfinancial objectives. Overall, our paper can constitute a first step toward decision-oriented player valuation and for theoretical comparison with practical investment decisions in football clubs, which obviously take into account other specific sports team decisions.

This study aims to determine whether, by means of the application of genetic algorithms (GA) through the traditional technical analysis (TA) using moving average convergence/divergence (MACD), is possible to achieve higher yields than those that would be obtained using technical analysis investment strategies following a traditional approach (TA) and the buy and hold (B&H) strategy.

The study was carried out based on the daily price records of the NASDAQ financial asset during 2013–2017. TA approach was carried out under graphical analysis applying the standard MACD. GA approach took place by chromosome encoding, fitness evaluation and genetic operators. Traditional genetic operators (i.e. crossover and mutation) were adopted as based on the chromosome customization and fitness evaluation. The chromosome encoding stage used MACD to represent the genes of each chromosome to encode the parameters of MACD in a chromosome. For each chromosome, buy and sell indexes of the strategy were considered. Fitness evaluation served to defining the evaluation strategy of the chromosomes in the population according to the fitness function using the returns gained in each chromosome.

The paper provides empirical-theoretical insights about the effectiveness of GA to overcome the investment strategies based on MACD and B&H by achieving 5 and 11% higher returns per year, respectively. GA-based approach was additionally capable of improving the return-to-risk ratio of the investment.

Limitations deal with the fact that the study was carried out on US markets conditions and data which hamper its application in some extend to markets with not as much development.

The findings suggest that not only skilled but also amateur investors may opt for investment strategies based on GA aiming at refining profitable financial signals to their advantage.

This paper looks at machine learning as an up-to-date tool with great potential for increasing effectiveness in profits when applied into TA investment approaches using MACD in well-developed stock markets.

Robotic process automation (RPA) has recently emerged as a technology focusing on the automation of repetitive, frequent, voluminous and rule-based tasks. Despite a few practical examples that document successful RPA deployments in organizations, evidence of its economic benefits has been mostly anecdotal. The purpose of this paper is to present a step-by-step method to RPA investment appraisal and a business case demonstrating how the steps can be applied to practice.

The methodology relies on design science research (DSR). The step-by-step method is a design artefact that builds on the mapping of processes and modelling of the associated costs. Due to the longitudinal nature of capital investments, modelling uses discounted cashflow and present value methods. Empirical grounding characteristic to DSR is achieved by field testing the artefact.

The step-by-step method is comprised of a preparatory step, three modelling steps and a concluding step. The modelling consists of compounding the interest rate, discounting the investment costs and establishing measures for comparison. These steps were applied to seven business processes to be automated by the case company, Estate Blend. The decision to deploy RPA was found to be trivial, not only based on the initial case data, but also based on multiple sensitivity analyses that showed how resistant RPA investments are to changing circumstances.

By following the provided step-by-step method, executives and managers can quantify the costs and benefits of RPA. The developed method enables any organization to directly compare investment alternatives against each other and against the probable status quo where many tasks in organizations are still carried out manually with little to no automation.

The paper addresses a growing new domain in the field of business process management by capitalizing on DSR and modelling-based approaches to RPA investment appraisal.

The purpose of this paper is to implement a genetic algorithmic geared toward building an optimized investment portfolio exploring data set from stocks of firms listed on the Nigerian exchange market. To provide a research-driven guide toward portfolio business assessment and implementation for optimal risk-return.

The approach was to formulate the portfolio selection problem as a mathematical programming problem to optimize returns of portfolio; calculated by a Sharpe ratio. A genetic algorithm (GA) is then applied to solve the formulated model. The GA lead to an optimized portfolio, suggesting an effective asset allocation to achieve the optimized returns.

The approach enables an investor to take a calculated risk in selecting and investing in an investment portfolio best minimizes the risks and maximizes returns. The investor can make a sound investment decision based on expected returns suggested from the optimal portfolio.

The data used for the GA model building and implementation GA was limited to stock market prices. Thus, portfolio investment that which to combines another capital market instrument was used.

Investment managers can implement this GA method to solve the usual bottleneck in selecting or determining which stock to advise potential investors to invest in, and also advise on which capital sharing ratio to reduce risk and attain optimal portfolio-mix targeted at achieving an optimal return on investment.

The value proposition of this paper is due to its exhaustiveness in considering the very important measures in the selection of an optimal portfolio such as risk, liquidity ratio, returns, diversification and asset allocation.

By examining the link between the two types of FDI and intrastate conflict from 1990 to 2015 in 138 countries, this paper intends to test the peace-through-FDI thesis.

To empirically test the hypotheses, this study examines county-year observations from 1990 to 2015 for 138 countries. An instrumental variable method is utilized to this end.

This paper shows that, while greenfield FDI generates pacifying effects on intrastate conflict, M&A investment is likely to promote the onset of intrastate conflict.

Despite the extensive literature on FDI and the onset of intrastate conflict, many have approached FDI as a singular phenomenon, and have not broken it down into its constituent parts of greenfield and brownfield investment types. Theorizing that this practice had oversimplified and blurred the relationship of FDI on intrastate conflict onset, the authors pursued the collection of novel data in order to more completely distinguish between the two types of FDI. With this novel approach dividing FDI into its component parts, the authors break open the black box of FDI to empirically find out the extent of its diverse influence on the onset of intrastate conflict.