Managerial Investment Decisions Research Articles

Self‐serving attribution and managerial investment decision

AbstractThis study examines whether managerial overconfidence coupled with self‐attribution bias distorts the investment decisions of firms. To this end, we investigate the impact of overconfidence on asymmetric investment cash flow sensitivity (ICS). We find that managerial overconfidence affects ICS in a downward‐sticky direction, which is reinforced by overconfidence coupled with managerial self‐attribution. The results for both unconstrained and constrained firms are qualitatively consistent with those for the overall sample; however, the constrained subsample provides slightly weaker results. Thus, our findings indicate that managerial overconfidence and self‐attribution to recent successes may induce managers to make excessive investment commitments.

BEHAVIOURAL ASPECTS OF INVESTMENT DECISIONS

Behavioural finance theory suggests that patterns of overconfidence, overreaction and overregulation are common to many investors, and that such groups can be large enough to prevent a company's share price from reflecting economic indicators. Modern empirical studies show that investment decisions are influenced by a number of subjective factors. These subjective factors are behavioural biases. They provide a number of new approaches to explaining investment activity. The article studies the influence of behavioural factors on the investment decisions of managers, especially on the investment decisions of corporate relations subjects. It was found that knowing the main reasons for irrational actions of corporate relations subjects, it is possible to predict and control such situations and, as a result, to avoid negative consequences of irrational behaviour.

Evolutionary game analysis of chemical enterprises' emergency management investment decision under dynamic reward and punishment mechanism

The safe operation and management of chemical enterprises remains a critical area of focus, and encouraging companies to proactively invest in emergency management is a significant practical challenge for government supervision. In this study, we combine prospect theory, mental accounting, and evolutionary game theory to establish a bounded-rationality hypothetical model for all actors (enterprises, government, and neighboring residents) involved in the emergency management investments of chemical enterprises. We analyze the evolutionary stable strategies for government departments, neighboring residents, and enterprises under static and three dynamic reward and punishment mechanisms, followed by a simulation analysis. Our findings indicate that: (1) the emergency management investment decisions of chemical enterprises are influenced by multiple factors, not only shaped by external elements but also governed by the decision-makers' own competency factors; (2) the application of a static reward and punishment mechanism by government departments, in the absence of evolutionary stable strategies, fails to exert a substantial restraining effect on enterprises; (3) the adoption of a dynamic reward and punishment mechanism effectively compensates for the limitations of static mechanisms, with the dynamic reward and dynamic punishment mechanism proving to be the optimal choice, outperforming other alternatives.

Behavioral Biases and Investment Decisions of SMEs Managers: Empirical Analysis within the Moroccan Context

This article examines the impact of overconfidence, optimism, risk aversion, mimicry and intuition biases on the investment decisions of Moroccan SMEs managers. The study was based on a sample of 133 SMEs managers, who were randomly selected to ensure the representativeness of the results. Analysis showed that optimistic managers tend to make investment decisions more frequently, while those who are more risk-averse adopt a more cautious approach. Mimicry was also identified as an influential factor in investment decisions, with executives likely to be influenced by the choices of their peers. Furthermore, intuition bias was also identified as a positive factor in the investment decision-making process, enabling managers to capitalize on their experience and tacit knowledge for more appropriate and timely choices. However, overconfidence showed no significant effect on investment decisions. These findings have important implications for the managers of Moroccan SMEs, enabling them to better understand the factors influencing their investment decisions, and to optimize the allocation of their financial resources for the sustainable growth of their businesses.

Does competition exacerbate investment inefficiencies? Evidence from Japanese firms

This paper investigates the implications of product market competition for the efficiency of managerial investment decisions. Using a sample of Japanese public corporations, we find that competition in the product market leads to overinvestment. We attribute this finding to the deleterious effects of competition on agency costs. Our hypothesis is supported by the fact that these adverse effects become more severe in environments with high agency costs, i.e., those with cross-shareholdings and interlocking business relationships, often referred to as Keiretsus, and those with weaker corporate governance arrangements. Our results are robust to the inclusion of firm-level characteristics, empirical specifications, and endogeneity of competition. Overall, our findings shed light on an important channel through which competition induces overinvestment namely, agency costs.

High‐Temperature Exposure and Land Transactions in China

AbstractWe estimate the relationship between high‐temperature exposure and land transaction using daily transaction data from 2013 to 2018 in China. Standard hedonic price method is used to perform multidimensional fixed effects regression on 458,564 transaction samples. This study shows that each additional day of the extremely high temperature increases the average bid price by 0.6%, which is equivalent to an additional annual increase of 15.018 billion yuan in land transaction costs. The effect of high temperature on land prices is considerably stronger for residential and commercial lands. We further find that high‐temperature‐induced changes of mood and cognition play a role. Extreme gradient boosting (XGBoost) algorithm is used to calculate price deviation, which overcome missing eigenvalues and reduce nonlinear measurement error. Our findings indicate that heat can make investors more aggressive, which occurs when bidders continue to raise prices to win. The number of bidding behavior will not drop due to the hidden costs of land transactions. Specially, bidding experience offsets the cognitive output bias. This study contributes to the behavioral finance and decision‐making literature, helps investors make better investment management decisions, and alleviates the negative effect of land transaction premium on the real estate market.

Forecasting the tax burden of agricultural enterprises by machine learning methods

The article analyzes the data of a set of agricultural enterprises and builds machine learning models to predict the tax burden. The subject of this study is a system of statistical indicators of agricultural enterprises that characterize the level of tax burden. The purpose of the study is to predict the tax burden using machine learning methods. The introduction of modern artificial intelligence tools is an integral and inevitable process in all spheres, including in the tax environment. Machine learning methods were used to build models: regression analysis, decision tree, random forest, gradient boosting. Models of forecasting the tax burden depending on a set of factors were built. The high quality of tax burden forecasting models will make it possible to more accurately assess the financial condition of enterprises, calculate profitability, predict profitability and make informed investment management decisions. As a result of forecasting the tax burden, the gradient boosting machine learning model turned out to have the best quality. In general, the model allows you to predict the tax burden better than traditional econometric models and make high-quality forecasts. The introduction of modern forecasting tools based on artificial intelligence methods will allow obtaining highly accurate forecasts with minimal time, which will increase the efficiency of enterprises and the level of production.

Support Vector Machine-based Stock Prediction Analysis

Changes in the stock market are closely related to the dynamics of the market development and economic research of the whole country. Correctly predicting the stock price trend is not only beneficial for investors to make correct investment management decisions but also of great importance to promote the effective allocation of resources and improve market effectiveness. To this end, the empirical prediction and analysis of a stock development market using a support vector machine show that the accuracy of stock prediction using a support vector classification machine is as high as about 90%, indicating that the accuracy of stock prediction based on support vector machine is ideal and meaningful.

Application of the Yield Curve Inversion Indicator to Determine the Current Phase of the Stock Market

Purpose: To establish the possibility of using the indicator of the inversion of the difference in the yield curve of 10-year and 2-year US Treasury bonds to determine the current phase of the stock market, predict the future direction of market movement and improve the efficiency of managerial investment decisions.
 Design/Method/Approach: The following methods were used when writing the paper: empirical – to carry out experimental checks of the revealed regularities; graphic - for a visual presentation of research results; systematization and generalization - for generalization of scientific concepts, developments, and proposals; statistical - to implement a quantitative approach to studying data. The US stock market was chosen as the base for research. The research was carried out by statistical processing of data on the value of the indicator of the inversion of the yield curve difference of 10-year and 2-year US Treasury bonds and the Standard & Poor's stock market index - 500 for the period from 1989 to 2022.
 Findings: It has been established that the indicator of the difference of the yield curve of 2-year and 10-year US Treasury bonds is a fairly reliable tool for determining the approaching recession in the economy, but at the same time it is not possible to determine the exact time of the recession. It is shown that this indicator is expedient to use for early warning about a possible fall in international stock markets. At the same time, it was found that not every inversion of the yield curve is followed by a fall in the stock market, but every fall is preceded by an inversion. It was noted that the current dynamics of the yield curve are signaling a possible significant drop in the US stock market in the near future.
 Theoretical Implications: Establishing the peculiarities of the indicator of the inversion of the yield curve difference of 10-year and 2-year US Treasury bonds in the conditions of the modern economy.
 Practical Implications: The practical application of the research results will allow us to more accurately determine the current phase of the international stock markets and receive early signals about the future decline of the markets, which will contribute to increasing investment efficiency.
 Originality/Value: This study expands knowledge about the peculiarities of the use of the indicator of the yield curve difference of 2-year and 10-year US Treasury bonds when determining the likely onset of a recession in the economy and the possibility of a fall in international stock markets, offers an updated model of the use of this indicator when forecasting the direction of movement of international stock markets. The results of the research may be of interest to specialists who work in the field of investing in international financial markets.
 Research Limitations/Future Research: The results of the work presented in this article create a basis for conducting similar research on the possibility of using other indicators in order to increase the accuracy of establishing the moment of recession in the economy or the beginning of a fall in international financial markets. From the author's point of view, first of all, such indicators as the movement of gold prices, the dynamics of changes in the Fed's discount rate, and Buffett’s indicator should be studied. This will make it possible to develop an effective application mechanism for making investment decisions and will contribute to increasing investment efficiency.
 Paper Type: Empirical
 JEL Classification: E44, F21, G15

Life is Too Short? Bereaved Managers and Investment Decisions

Abstract We examine whether bereavement affects managerial investment decisions in large organizations using the exogenous events of managers’ family deaths. We find evidence that bereaved managers take less risk in separate samples of mutual funds and publicly traded firms. Mutual funds managed by bereaved managers exhibit smaller tracking errors, lower active share measures, and higher portfolio weights on larger stocks after bereavement events. Firms managed by bereaved CEOs exhibit lower capital expenditures and fewer acquisitions after bereavement events. Further analyses support the emotion-driven explanation over other explanations. The risk shifting by bereaved managers has negative implications on the performance of funds and firms that they manage.

Stock Prediction and Analysis Based on Support Vector Machine

The changes of the stock market are closely related to the market development and economic research trends of the whole country. Correctly predicting the stock price trend is not only beneficial for investors to make correct investment management decisions, but also plays an important role in promoting the effective allocation of resources and improving market effectiveness. significance. To this end, the daily closing prices of Shanghai Hengrui Medicine and Baosteel Co., Ltd. are used as the basic data, and the support vector machine of python software is used to empirically predict and analyze the development of my country's stock market. The accuracy rate is as high as about 90%; then the parameter optimization is carried out on the basis of the model again, and it is also concluded that the accuracy of stock prediction is as high as about 90%, indicating that the stock prediction accuracy rate based on support vector machine is ideal and has meaningful.

The Relationship between Corporate Governance and Performance of Pension Fund Managers in Kenya

Pension funds performance in Kenya have been facing myriad of challenges ranging from poor administration and investments of pension funds, lack of transparency and accountability, non-remittance of monthly contributions by employers, misappropriation of scheme assets by the trustees, loss of scheme funds through negligence of trustees and poor investment of the scheme assets. The objective of this study was to examine the relationships between corporate governance, and performance of registered pension fund managers in Kenya. This study adopted positivism philosophy. The study employed a cross sectional survey design whereby access to the widest possible amount of data from the targeted Fund Managers in Kenya was sought. The population of interest of the study was 31 Fund Managers in Kenya licensed by RBA and CMA. The study used purely primary data sources. Primary data was obtained from the selected respondents. Primary data was collected through questionnaire. Regression analysis was used to establish the relative significance of each of the variables on the influence of corporate governance on the performance of pension fund managers in Kenya. The study findings indicated that there was significant relationship between corporate governance and performance of pension fund managers in Kenya. The study concluded that there is significant relationship between corporate governance and performance of pension fund managers in Kenya. The study determined that the corporate governance practices being implemented had been incorporated in the Pension Fund’s investment management decisions with its assets being more diversified and having enhanced reporting on investments. The study recommends on pension reforms, by creating a new class of potential activist shareholders in the form of pension funds, could in principle improve corporate governance and increased shareholder discipline. The governments as well as Pension Fund Managers supervisors should consider a more active role in the selection process of the board members, while reducing their choices to professional beneficiaries of the pension funds Keywords: Corporate Governance, Transparency, Ownership Structure, Accountability, Participation Performance, Pension Fund Managers & Kenya

Keterkaitan Antara Managerial ownership, Capital Structure dan Investment Decision Dalam Perspektif Convergence – Interest hypothesis

This study aims to analyze the effect of managerial ownership, capital structure, and investment decisions in the convergence of perspective –interest hypothesis. This type of research is quantitative analytic. The data analysis method used regression for panel model 2 and model 3, as well as the simultaneous Equation model for model 1. This study used a statistical regression coefficient test (t-test) for bivariable analysis, F test, and R2 test. The results of the interpretation of model 1 and model 2 (without outliers) are not normally distributed, there is no multicollinearity, there are no symptoms of heteroscedasticity and there is a positive autocorrelation. The results of the interpretation of model 3 (without outliers) are normally distributed, there is no multicollinearity, there are symptoms of heteroscedasticity and there a positive autocorrelation The result for the study can be concluded classical assumption test show that the three models have abnormal symptoms and heteroscedasticity. The researcher has removed the data outliers one by one in the three models and transformed data into the third model. We suggest adding different variables such as dividend payout decisions. As well as being able to will add a sampling period that more samples are studied and consider taking samples from other companies for next research.

The impact of organisational structures on management compensation packages and investment decisions - a principal-agent approach investigating formula apportionment and separate accounting

The impact of organisational structures on management compensation packages and investment decisions - a principal-agent approach investigating formula apportionment and separate accounting

The Statistical Endeavors of Andrew Carnegie

American steel tycoon and philanthropist Andrew Carnegie (1835-1919) was a member of the American Statistical Association from 1892 until his death. He learned cost accounting at the Pennsylvania Railroad, and later adapted its data-driven approach to managing his steel business. He successfully outperformed competitors by introducing a detailed data collection program within his steel mills, and using the resulting information for personnel management, marketing, and capital investment decisions. Carnegie was also a consumer of US census data, using it extensively in his polemical book Triumphant Democracy to argue in favor of the US political and economic arrangements, as opposed to those of old Europe; and for making decisions on donating public libraries and church organs across the world. However, Carnegie lacked a modern understanding of statistical variation. The statistics profession has advanced, and narrowed, since Carnegie's time, and I argue that Carnegie's modern counterparts in business would not be welcome in the American Statistical Association today.

Bahasa IndonesiaManajemen Laba dan Perilaku Investasi: Apakah Framing Effect Diperhitungkan?

This study aims to obtain empirical evidence on the effect of earnings management on company's investment decision making, as well as to see indications of the framing effect caused by earnings management on the company's investment behavior. The sample of this study includes all manufacturing companies listed on the stock exchanges of countries in Southeast Asian region with an observation period from 2009 to 2019. The results indicate a positive and significant effect of earnings management on management investment decisions. Meanwhile, the framing effect is believed to arise as a result of earnings management practices and also influences managers in viewing further as a consideration for making company investment decisions.
 Keywords: Earnings Management; Investment Decision; Framing Effect.

How fiduciary duty law incentivises investors to manage sustainability risks

The compatibility of Environmental, Social and Governance (ESG) risk management with the investment management requirements under the investors’ fiduciary duties (FD) figures among the key questions in today’s context of a rapid growth of sustainable investment strategies. Despite some legal developments, namely, in Europe, investors still have no clear answer to this question, which leaves them inert in the face of these new, unconventional types of risk. In our research, we explore the recent advancements in the EU and the US legal practice with the objective to establish to what extent the FD actually requires investors to consider ESG risks in their investment management decisions. Through analysis, we define a theoretical decision-making pattern for ESG risk management set by the current FD law as applied to investors and identify: 1) ESG risk materiality and 2) the effectiveness of ESG risk hedging as its fundamental elements. Then, we design a theoretical representation of ESG risk materiality under the FD legal constraints and identify that the current FD law binds investors to assimilate ESG risks to financial risks; thus, their management is required only if they are financially material for investments. We show that this principle equally applies to long-term ESG risks (like climate change); investors are incentivised to manage only those that are sufficiently financially material considering the applied hypothetical discount rate. Also, through the case study of a recent US ERISA ESOP lawsuit, we reveal that risk aversion towards probability to successfully hedge material ESG risks could impede efficient risk management by incentivising investors not to hedge a material ESG risk, i.e. to breach their FD.

Life cycle assessment of plastic waste end-of-life for India and Indonesia

Developing countries like India and Indonesia struggle with proper management of plastic waste, causing rampant plastic pollution that adversely impacts the ecosystem and potentially human health. In this study, life cycle assessment (LCA) was adopted to compare the environmental impact of end-of-life (EOL) treatment of 1 kg plastic waste in India and Indonesia based on the EOL mix, which includes mechanical recycling, co-processing in cement kilns, incineration, sanitary landfill, open dumping and open burning. Nine environmental impacts were considered, namely climate change, cumulative energy demand, water depletion and marine eco-toxicity, human toxicity, terrestrial acidification, fossil depletion, particulate matter formation and urban land occupation. Waste plastics EOL treatment in India was found to have a lower environmental impact than Indonesia among all nine categories, which was attributed to higher mechanical recycling rates in India. Hotspot analysis revealed that open burning is a major contributor to climate change, while landfills are the major contributor to marine eco-toxicity. A sensitivity analysis found that the percentage of plastic waste collection, percentage of uncollected plastic waste openly burnt, percentage of plastic rejects from recycling and percentage replacement of virgin plastic from recycled plastic granules were key sensitive parameters. The results of a future scenario analysis showed that further investments in mechanical recycling by 2030 can not only reduce mismanaged plastic waste, but also contribute towards the Paris Agreement carbon reduction pledges for both India and Indonesia. The results from this study can be used to support future waste management investment decisions in both countries.

Evolution in a General Equilibrium framework

In this paper, we consider a general equilibrium model in which the economies are characterized by the distribution of firms on a set of branches of production; we will show that based on the decisions of the managers of the firms, it is possible to build a dynamic system whose solutions reproduce the possible trajectories of the economy. Once the initial state of an economy is known, that is, the initial distribution of firms, we will have a unique solution for this dynamic system, which will coincide with the evolution of the economy, that is, the evolution of prices and equilibrium allocations.The investment decisions of the administrators of the companies will change the distribution over the set of existing productive branches, which in turn will produce changes in the wealth of consumers who are also shareholders of the companies and then as a consequence, their demand will change, and therefore the equilibrium allocations and prices will too.In most cases, these decisions lead to an improvement in the efficiency of the productive side of the economy and an increase in the welfare of the economy as a whole, but, as we will show, under some particular circumstances, even when it comes to rational decisions from the point of view of administrators, this can lead to undesirable repercussions on the welfare of consumers. Besides, in a neighborhood of a critical economy, even when these decisions may involve small changes in the distribution of companies, they can cause abrupt and unexpected changes in the behavior of the economy, or in other words, they can cause an economic crisis. These are characterized by large changes in the prices, in the demand, and in the supply of goods. In contrast, in a sufficiently small neighborhood of a regular economy, small changes in the distribution of firms produced by the investment decisions of managers do not lead to large changes in the subsequent behavior of the economy. We will exemplify these statements with several numerical examples.

DYNAMIC INTERCONNECTEDNESS AND RISK CONTAGION AMONG ASIAN FINANCIAL MARKETS

This study investigates dynamic interconnectedness, spillover transmissions and risk contagion through the lens of intraday and overnight returns to ascertain whether intraday and overnight trading information (returns) have idiosyncratic effects on risk behavior of financial markets. The study employs the generalized VAR-based spillover measure, graph theory and Bayesian causality network (BN) models. Our results reveal that spillover propagation from the US market is mainly through the intraday return series to Asian markets, whereas the overnight series is mainly a recipient of spillovers. Furthermore, in terms of risk contagion, the result identifies the most systemically central financial markets (SCFMs) as Singapore, Hong Kong, Korea and Taiwan. In particular, the findings demonstrate that while Singapore maintains the role as the most systemically central markets in large part, other markets occasionally took the leading role as most central markets. Overall, the findings provide important practical implications for market regulators and investors to monitor the channels of trading information and the performance of SCFMs for better risk management and strategic investment decisions.