Investment Characteristics Research Articles

Factors of international trade and environmental degradation in the UAE: Moderating role of foreign investor characteristics

The purpose of the study is to identify the moderating role of economic factors of foreign investor over the relationship between economic factors and environmental degradation in Dubai which is among the fastest-growing economies and is attracting foreign direct investments (FDI) at the best. In order to meet the objectives of the study two hypotheses were developed. The first hypothesis deals with the direct effect of economic dimensions of foreign direct investment (Alkathiri, 2022), whereas, the second hypothesis deals with the moderating impact of foreign investor characteristics over the relationship between economic dimensions of foreign direct investment and environmental degradation. Both hypotheses have been checked over the primary data collected from the executives of multinational companies operating in Dubai. The findings of the study revealed that economic dimensions of foreign direct investment have a significant impact on environmental degradation. Likewise, foreign investor characteristics hold a significant moderating role in the significant relationship between economic factors of foreign direct investment and environmental degradation (Khan & Agha, 2015). The study showed some limitations and opened the horizons for future research.

The effects of institutional investors on firms' green innovation

AbstractStakeholder theory suggests that institutional investors, as firms' vital stakeholders, might play a crucial role in influencing firms' green innovation. Considering both the shareholding and portfolio characteristics of institutional investors, we investigate the effects of different types of institutional investors with various supervisory motivations and governance capabilities on firms' green innovation. Importantly, we also explore which types of institutional investors become the driving force behind firms' green innovation. Furthermore, we consider how various aspects of financial and social benefits as contingencies affect the relationship between different types of institutional investors and firms' green innovation. Based on 5473 observations of Chinese manufacturing firms from 2013 to 2019, we find that, when considering institutional investors' effects on firms' green innovation, it is better to simultaneously consider both the shareholding and portfolio characteristics of institutional investors than to consider only one or the other. Dedicated institutional investors with more shareholding independence and higher portfolio concentration are positively associated with green innovation and are the driving force behind it, while transient institutional investors are not. However, institutional investors' effects on green innovation will change because of contingencies related to firms' financial and social benefits, generally presenting the characteristics of “pursuing benefits and avoiding risks.” Specifically, dedicated institutional investors promote green innovation for firms with satisfactory financial and social benefits to pursue long‐term benefits but do not have significant effects on the green innovation of firms with general or unsatisfactory financial and social benefits. By contrast, transient institutional investors are inclined to hinder green innovation for firms with unsatisfactory financial and social benefits to avoid short‐term risks; at the same time, they have insignificant effects on the green innovation of firms with satisfactory or general financial and social benefits.

The ethical obligations of institutional investors: Managing moral complexity

AbstractInstitutional investors control almost 60% of all assets under management worldwide and encompass a wide variety of organizations. Despite this reach, however, institutional investors have not received the normative scrutiny they merit beyond general discussions around their legally grounded fiduciary obligations to their beneficiaries. This paper offers a discussion of institutional investor ethical obligations in light of their specific attributes. We propose that the different characteristics of institutional investors and the diverse roles they play in the marketplace inform the scope of their activities, and, in turn, the different ways in which their basic ethical obligations can be fulfilled.

Moderating Role of Foreign Investor Characteristics on the relationship between Regulatory Factors of International Trade and Environmental Degradation in UAE

The study has been conducted to analyze the moderating role of economic factors of foreign investor over the relationship between regulatory factors and environmental degradation in Dubai. The study has been conducted in Dubai considering the country as a fastest growing economy and attracting foreign direct investment in all fields. For the purpose of fulfilment of the study objectives the research developed two hypotheses. The hypothesis was tested over a sample of 335 responses generated from the executives of multinational firms of Dubai. The results confirmed that regulatory factors have a direct impact over environmental degradation, similarly, foreign investor characteristics also have a significant moderating role over the significant relationship between regulatory factors of foreign direct investment and environmental degradation. The study is important for the policy makers to develop such rules that negative influence over the environment may be curtailed.

Unveiling trading patterns: iTraxx Europe financials from the great financial crisis to ECB monetary easing

Financial stability is a statutory concern of the European Central Bank. Spreads of bank credit default swaps (CDS) indices are a reference for financial stability, but the literature is scarce in this respect. This paper poses the novel research question of which characteristics of investors in these derivatives are implied by the volatility behavior of the returns of financial CDS indices. Daily spread returns for the 5-year maturity iTraxx Europe Financials (subordinated and senior), for the period between June 2004 and March 2015, are used to estimate a GJR-M model with Student t innovations, and two MGARCH models (one with constant and the other with dynamic conditional correlations). The results show that investors in the index referring to subordinated debt are risk averse (risk premium estimate of 0.688) and liable to leverage effects, while investors in the index for senior debt do not have such characteristics. The degrees of freedom of the Student t innovations are estimated to be 4 for both indices, implying that returns have distributions with very fat tails. Population excess kurtosis diverges to infinity. The results show that the conditional correlation between the indices is dynamic. Although correlations vary widely, most of that variation occurs before the Euro Area crisis. It is concluded that the inclusion of both indices in a portfolio would be misadvised for bear markets with distressed financial entities: the correlations are always positive, above 0.75 since 2010. Moreover, both indices prove to be sensitive to the varying surrounding conditions as investors share market sentiments. AcknowledgmentsNECE’s research is funded by national funds through FCT – Fundação para a Ciência e a Tecnologia, I.P., Project UIDB/04630/2020CEBER’s research is funded by national funds through FCT – Fundação para a Ciência e a Tecnologia, I.P., Project UIDB/05037/2020  

What do we know about startup-valuation drivers? A systematic literature review

ABSTRACT Startup-valuation is a critical area of research within entrepreneurial finance, but research on this topic is less consistent and thorough than overall valuation research. Peer-reviewed studies express a range of divergent views and approaches, and the focus varies widely. To bring clarity to this fragmented field, we conduct a systematic literature review, examining 87 peer-reviewed studies published between 1985 and 2020. We analyze these publications in detail and identify 36 startup-valuation drivers and cluster them into five macro-themes: Entrepreneur Characteristics; Firm Characteristics; Investor Characteristics; Market Conditions; and Deal Conditions. We then describe the valuation-impact of these drivers on startups. The range of drivers identified in the literature gives rise to construction of an integrative meta-model based on the macro-themes, placed into appropriate chronological position in the valuation process Our study also identifies key research-gaps and highlights promising directions for exploring the startup-valuation field.

The Effect of the Behavioral Biases of Korean Invertors on Performance with Financial Literacy as a Moderator

Purpose – The purpose of this study is to analyze how the behavioral characteristics of Korean individual investors affect investment performance.
 Design/Methodology/Approach – Through the survey method, we tried to examine the behavioral bias characteristics and behavioral bias investment decisions on performance during the COVID-19 period. Multiple regression and SPSS PROCESS were used to find the effect of the behavioral characteristics and behavioral decisions on performance with financial literacy as the moderator.
 Findings – As a result of multiple regression analysis, it was found that among the biased investment characteristics, overconfidence and mental accounting statistically affect investment results. In the analysis through the SPSS PROCESS model, the level of financial literacy was found to be significant as a moderating variable, and it was also found that biased investment decision plays a role as a mediating parameter in investment performance.
 Research Implications – This study is meaningful in providing insight into the behavioral investment characteristics of individual investors by presenting an empirical analysis of the behaviorally biased characteristics and behaviorally biased investment decisions of individual investors on investment performance in Korea.

The sentiment pricing dynamics with short-term and long-term learning

Combining the behavioral characteristics of rational uninformed investors with learning information behavior of sentiment investors, this paper establishes a mathematical model about the impact of learning information behavior on the investor's transaction and asset equilibrium price under asymmetric information. Research shows that when rational uninformed investors learn information in the short term, on the one hand, they choose to bet against sentiment investors, thus reducing the influence of sentiment; on the other hand, they occasionally mistake sentiment for information to chase sentiment investors, then amplifying sentiment shocks. Furthermore, sentiment investors can also gain valuable information indirectly by observing the price in the long term. When sentiment investors learn information in the long term, the price fluctuations caused by sentiment and information, informativeness of the price system and market efficiency are no longer dependent on the quality of information.

Portfolio selection: should investors include crypto‐assets? A multiobjective approach

AbstractThis paper analyzes the diversification benefits of adding alternative crypto‐assets in a traditional portfolio, from the perspective of an investor who seeks to achieve multiple objectives. Our analysis is based on daily and weekly return data for eight different assets including Bitcoin, Ethereum, Ripple, for the crypto‐assets and NASDAQ, S&P500, Dow‐Jones, Crude‐Oil, and Gold, for traditional assets. We use both in‐sample and out‐of‐sample estimation procedures to analyze these data sets. We apply the weighted sum of deviations goal programming method to solve a bi‐objective optimization problem where investors optimize simultaneously portfolio risk and return. For a variety of investor characteristics, ranging from risk‐seeking to risk‐averse, we show that augmenting portfolios with alternative crypto‐currencies improves portfolio performance and the efficiency frontier, compared to standard portfolios. This improvement is even more observable for risk‐seeking investors, for both in‐sample and out‐of‐sample estimation procedures.

Distrust or speculation? The socioeconomic drivers of U.S. cryptocurrency investments

Employing representative data from the U.S. Survey of Consumer Payment Choice, we find no evidence that cryptocurrency investors are motivated by distrust in fiat currencies or regulated finance. Compared with the general population, investors show no differences in their level of security concerns with either cash or commercial banking services. We find that cryptocurrency investors tend to be educated, young and digital natives. In recent years, a gap in ownership of cryptocurrencies across genders has emerged. We examine how investor characteristics vary across cryptocurrencies and show that owners of cryptocurrencies increasingly tend to hold their investment for longer periods.

A comparison of investment behavior, attitudes, and demographics of socially responsible and conventional investors in India

PurposeIndia is an emerging economy and one of the preferred investment destinations for environmental, social and governance (ESG) fund issuers. Institutional investors invest retail investors’ money, and hence, it becomes imperative for ESG fund managers to understand the social investment preferences of retail investors. This study aims to compare the Indian socially responsible (SR) investors and conventional investors in terms of their socially responsible investment (SRI) awareness level, opinions about broad and specific ESG issues, investment behavior and demographics. In addition, this paper makes an attempt to have a deeper insight into Indian investors’ behavior toward SRI by segmenting the Indian retail investors based on their SRI awareness level, attitude toward ESG issues and intention to accept lower financial returns, and choices made by them as consumers.Design/methodology/approachAfter collecting the data through the survey method an independent t-test is used to compare SR investors with conventional investors. Chi-square has been used to analyze the data related to demographics, and cluster analysis is used to identify segments among Indian retail investors.FindingsThe results indicated that Indian SR investors’ SRI awareness level is more, they are more concerned about broad and specific ESG issues, they are more into faith-based investing, and are responsible consumers vis-à-vis conventional investors. As per demographic, SR investors are in the middle age group of 30–40 years, male, hold a postgraduate degree and have an annual income of 10–20 lakhs in comparison to conventional investors. The results of cluster analysis indicated that Indian retail investors can be classified into three groups based on their SRI awareness, intention to sacrifice financial return, attitude toward ESG issues and choices made by them as consumers.Research limitations/implicationsResults have implications for national and international fund managers, policymakers, regulators and society. These results will help mutual fund companies to provide curated SR mutual funds as per the behavior and choice of retail investors and penetrate the Indian investment market more deeply.Originality/valueThis research study contributes to the literature on SRI by identifying the differentiating characteristics of Indian SR and conventional investors and segmenting Indian retail investors on the basis of their SRI awareness, the importance of ESG issues and choices made by them as investors and consumers.

Heuristics and cognitive biases in the housing investment market

PurposeThis paper aims to analyze the heuristics and cognitive biases described by behavioral finance in the investment decision-making process of Portugal’s housing market.Design/methodology/approachIn a first step, the authors applied an exploratory factor analysis (EFA) to assess the impact of heuristics and cognitive biases on investors’ decision-making. In a second step, the authors run a structural equation model (SEM) diagram path to assess if the sociodemographic characteristics of housing market investors determine the identified heuristics and if the heuristics condition the investors’ investment criteria.FindingsHerd behavior and the heuristics of representativeness, availability and anchoring influence the housing market’s investors’ behavior in their decision-making process. Investors with above-average income show higher levels of overconfidence. Investors showing higher levels of overconfidence also tend to be more sensitive to the house price under analysis for investment. Women tend to show higher levels of the availability and anchoring heuristic. In turn, housing market investors showing higher levels of availability and anchoring heuristic tend to be more sensitive to the price and location of the house under analysis for investment.Research limitations/implicationsThe explained variance of the EFA is below 50%, and the root mean square of approximation of the SEM is above the threshold of 0.05. These indicators are evidence of the models’ fragility.Practical implicationsGovernments and regulators can better prevent real estate bubbles if they monitor behavioral biases and heuristics of housing investors together with quantitative indicators. Realtors can profit from adapting their marketing strategy and commercial communication to investors of sociodemographic groups more prone to a specific type of heuristics.Originality/valueTo the best of the authors’ knowledge, this is the first study that combines the contributions of behavioral finance with Portugal’s housing investment market and the first study connecting heuristics to investment criteria.

금융기관의 대체투자 중 부동산 Equity 투자 결정요인 분석

Interest rates, which have continued to fall since the 2008 financial crisis, have recently fallen to 0.5% of the Bank of Korea's benchmark interest rate, entering an ultra-low interest rate era. Investors in financial institutions are paying attention to alternative investment assets to cope with the weakening profitability of their investments, as it is difficult to expect profitability from bonds and stocks, which are traditional investment assets. Among them, real estate investment has steadily become an essential factor in institutional investors' portfolios, as real estate investments can be guaranteed high returns depending on location and supply and demand conditions, but are relatively less affected by financial market trends. In particular, financial institutions, which are actively expanding alternative investments due to falling operating returns due to the worsening economy, are focusing on profitable real estate equity investments. However, despite the growing demand for real estate Equity investment by financial institutions, there are few specific investment criteria for which investment impact factors are determined, in the case of domestic real estate investment decision-makers, few have focused on investment. The objective of this study is to empirically analyze and identify the investment impact factors on the investment satisfaction and willingness of financial institutions in the real estate equity investment market, and to specifically analyze the differences in the types of investment impact factors. This study first examined the preceding research to derive the influences of real estate equity investment, and conducted a survey on investors from financial institutions. In addition, investor characteristics used descriptive statistical analysis, and factor analysis was conducted to verify the validity of the survey variables. Based on this, a regression analysis was conducted to test the hypothesis, and additionally a descriptive statistical analysis was used to analyze differences in the importance of investment impact factors depending on the type of financial institution. The results of the study are summarized as follows. First, as a result of hypothesis tests on investment impact factors and investment satisfaction for investors in financial institutions, location characteristics, profitability, and stability were adopted, and location characteristics were the factors that affected investment satisfaction the most. A hypothesis test of investment impact factors and willingness to reinvest in financial institutions showed that profitability and stability had a positive impact on the willingness to reinvest. Second, after analyzing the difference in importance of investment impact factors according to the type of financial institution, bank investors value stability and capital investors value timeliness the most among the investment impact factors. Investor in insurance companies put the most importance on profitability. Overall, investors in financial institutions participating in real estate equity investments demonstrate similar relationships between investment impact factors, investment satisfaction, and reinvestment intentions, and empirically analyzed that there are also differences in investment impact factors. These findings suggest that in financial institutional investment markets, financial institutional investors make decisions based on profitability, stability and location characteristics, but consider differences in investment propensity for financial institutions.

Investor Characteristics and Their Effect on Investment Decisions among Public University Workers in Kenya

Investment decision has become part of individuals’ lives in the in recent days. People invest in insurance policies, fixed deposits, shares, equities, real estate, mutual funds, and government securities among others. Universities are the peak of knowledge hence the community expects that workers in such institutions be in the frontline in making informed investment decisions. Although the university staff work in the same environment, it has not yet been established how their different investor characteristics affect their investment decisions. There is scanty information on the moderating effect of mobile borrowing on the relationship between investors’ risk attitude, demographic profile, and socio-economic status on investment decisions. This study investigated the effect of the investor characteristics on investment decision. The objectives of the study were to; assess the effect of investor risk attitude on investment decision among public university workers in Kenya, test the effect of the investor demographic profile on investment decisions among public university workers in Kenya, and determine the effect of socio-economic status on investment decision among public university workers in Kenya. Finally, the study examined the moderating effect of mobile borrowing on the effect of investor risk attitude and socio-economic status on investment decision among public university workers in Kenya. Capital Asset Pricing Model, Efficient Markets Hypothesis, Prospect Theory and Behavioural Finance Theory guided the study. The study adopted a descriptive survey research design with a target population of 2075 workers from the sampled Public Universities in Kenya. Stratified random sampling technique was employed from which a sample of 336 was used. Further, the study used primary data sources through a structured questionnaire. The questionnaires were administered using google forms. Data was analysed with the aid of SPSS version 26 software and Microsoft excel. Charts, tables, graphs, and figures were used to present the results. The results of the study indicated that risk attitude played the biggest role in investment decision-making since it explained 41.7 percent of investment decision. In addition, all the demographic factors influenced the choice of investment. The results also showed that investors in the age of 31-40 were willing to diversify their investments unlike the other age groups. Mobile borrowing was found to moderate the relationship between investment decision and its predictors. The study recommends that a similar study is conducted once the government operationalises the mobile lending control. Since workers between 31-40 years were found to have a much higher affinity for risk and investment, the government should consider targeting civil servants and other professionals in this age group by providing them with investment incentives.

Forming Efficient Frontier in Stock Portfolios by Utility Function, Risk Aversion, and Target Return

Asset allocation has always been a challenging issue / for individuals and businesses to survive in our competitive world. One of the famous businesses, which has an enormous impact on people's lives worldwide, is the pension industry. Pension funds- as Defined Benefit, Defined Contribution, or others- accept reserves from contributors and try to invest them in a way to keep up with their obligations in the future or even pay more than that. The equity market has been one of the good choices for investment as pension funds try to reach a particular rate of return to maximize their wealth while considering not crossing red lines in taking risks. This paper will detail the new mathematical model for finding optimal stock portfolios using Generalized Co-Lower Partial Moment as a risk measure to minimize portfolio optimization. On the other hand, it introduces new tailored Expected Utility as a performance metric to maximize in this model. The proposed model's issue against previous studies is considering risk aversion and target rate of investment return as two significant investor characteristics. This is based on price returns' simulation of candidate stocks in TSE while using accurate and nonparametric Probability Density Function in historical data analysis.

Risk Assessment and Regulation Algorithm for Financial Technology Platforms in Smart City.

The informatization of cities has been further promoted, and the construction of smart cities supported by technological innovation has been upgraded. The financial industry and data are closely related. Whether the financial industry can make good use of new information technology is the key to its successful transformation. The development of smart cities has a significant effect on the development of people's livelihood, the process of urbanization, the use of technology, the solution of urban problems, and the improvement of economic levels. This also provides a good choice for the development of cities in each country. For better development, it needs technical support. Therefore, it is very important to improve the technical level. This research mainly discusses the risk assessment and regulation algorithms of financial technology platforms in smart cities. This study divides the risk decision channels into two paths based on the smart city theory, considers the internal risk factors and external risk factors of the robo-advisory service platform from the three perspectives of platform characteristics, corporate characteristics, and investor characteristics and exploring the construction of a robo-advisory service platform risk prediction model based on the machine learning perspective. The design and implementation of a personalized financial investment prototype system, a Python-based web development framework Django, and a variety of toolkits have realized a B/S architecture robo-advisor. Among them, the function of buying and selling ETF and the trend recording function after buying are realized by simulating the transaction data collected by the data collection module. The study found that the key potential characteristics that constitute platform risks are mainly the listing year of the background company, the age of the platform, the investment threshold, and the search index. To a certain extent, this provides data support for investors and regulatory authorities to evaluate platform capabilities and platform selection. Investors should comprehensively consider platform qualifications when making platform decisions and pay attention to information such as the age of listing of companies with platform background, platform age, and investment thresholds. Only when the quality of people is improved, the quality of the population of this city improves, so that the development of the city has a broad room for growth. The accuracy of the similar formula calculation method in the big data proposed in this study reached 88%. This research provides new ideas for perfecting the black box regulatory system of robo-advisory algorithms.

Changes in investors risk-taking behavior during Indonesian economic recession due to the Covid-19 in 2020

This research discusses the differences in investor risk-taking behavior in Indonesia before and during the economic recession caused by the Covid-19. This pandemic began to infect Indonesia in 2020. Investor risk-taking behavior consists of three criterias, that are return expectation, risk tolerance and risk perception. Factors that can influence investor risk-taking behavior in this study are the economic recession itself and the characteristics of investors. While the characteristics of investors are seen from their status, namely age, gender, work status, marital status, education level, income, net worth and length of investment. In this study, questionnaires were distributed targeting investors in Indonesia. It was found that in fact the Covid-19 pandemic caused changes in investors risk-taking behavior, which included returning expectations and risk tolerance to decrease and risk perception to increase. Characteristics of investors Indonesian in general, it has no effect on investors' risk-taking behavior. Of the ten characteristics of investors, only two correlates with one of the criteria, namely profession and gender. It was found that the characteristics of investors did not have a positive effect because the majority of investors in this study were members of investment, money markets and capital markets communities. They join many of these communities, so that the exchange of information and discussions between one community and another will be affected. Investors’ decision making also based on the results of discussions in the community.

Individual investors' dispersion in beliefs and stock returns

AbstractWe construct a measure of dispersion in beliefs among individual investors. We find that dispersion in beliefs negatively predicts future cross‐sectional stock returns, and it is positively related to trading volume and stock volatility. We also find that illiquidity does not affect the significance of dispersion in beliefs in predicting future stock return, and that the negative disagreement‐return relation is significant under high‐sentiment periods but becomes insignificant under low‐sentiment periods. Moreover, investor characteristics affect their dispersion in beliefs even when controlling firm fundamentals. In particular, stocks with more wealthy, younger, and male investors tend to have higher dispersion in beliefs, and stocks with more experienced investors have lower dispersion in beliefs.

Investment Decisions in Emerging Market: Demographic Analysis of Individual Investor in Indonesia Stock Exchange

The number of individual investors in Indonesia has continued to grow in recent times and has reached 97.67% of the total investors in Indonesia. Due to this high number, the investment decisions of individual investors should be an important benchmark in the movement of Indonesia’s capital market. Investment behavior between individuals is very different and easy to change, but there is a pattern or model that can provide an overview of the activities carried out. Not only psychological factors, but demographic factors are also suspected to be determinants that influence investors’ decisions. The diversity of investment behaviors can be described by stock ownership. In Indonesia, blue-chip stocks are represented in the LQ45 index group. Although investors have different characteristics, their demographics are often used as second references to determine investment behavior. This study aims to determine the investment behavior using four important inherent characteristics of investors including gender, age, occupation, and income. The secondary data obtained from 3,911 investors were analyzed using analysis of variance (ANOVA). The results showed a unique pattern of investment behavior; therefore, the demographics of investors need to be analyzed regularly.

THE ISSUES OF MONETARY POLICY RESPONSE TO ASSET PRICE BUBBLES IN MODELS WITH ASSUMPTION OF THE FINANCIAL ACCELERATOR

In economic modeling problems, asset prices are considered endogenous variables. Meanwhile, there are times when they do not reflect the true nature of the economy, that is, pricing is not based on the fundamentals. It is worth noting that such fluctuations in asset prices are not only the result of deviations from the fundamentals of the economy; but also have an impact on the economy, causing real economic instability. Such fluctuations in asset prices can be attributed to both the irrational (or so-called behavioral) characteristics of investors and the liberal policies pursued by regulators, which are characterized by increased access to credit and can lead to asset overvaluation. The paper aims to present possible ways in which asset price bubbles affect real macroeconomic variables, as well as the models used by regulators to respond to bubbles, emphasizing those based on the concept of a financial accelerator. The paper expands the results of the statistical test for the presence of bubbles in the real estate market in Yerevan and the approaches used by the Central Bank of RA to respond to asset price fluctuations