Investment Selection Research Articles

Hesitant fuzzy linguistic preference consistency-driven consensus model with large-scale group interaction measure for venture capital investment selection

Hesitant fuzzy linguistic preference consistency-driven consensus model with large-scale group interaction measure for venture capital investment selection

Optimizing Investment Selection Through Similarity Measurement with Type-2 Intuitionistic Fuzzy Sets

Optimizing Investment Selection Through Similarity Measurement with Type-2 Intuitionistic Fuzzy Sets

An Attempt on Investment Selection Problem under Neutrosophic Environment based on Weighted Value Method

The main aim of this study is to develop a ranking algorithm in neutrosophic environment and applying this algorithm to choose the best option for investment selection problems. Firstly, the concept of single valued triangular neutrosophic numbers (SVTrN-numbers) and it’s characteristics are presented briefly. Here we define the λ-weighted value of SVTrN-numbers and applied it to the best selection of investment selection problem (ISP). Finally, to determine the feasibility and validity of this algorithm, we compared the resultant ranking by the proposed method with other existing approaches.

Optimizing Portfolio in the Evolutional Portfolio Optimization System (EPOS)

A novel method of portfolio selection is provided with further higher moments, filtering with fundamentals in intelligent computing resources. The Evolutional Portfolio Optimization System (EPOS) evaluates unobtrusive relations from a vast amount of accounting and financial data, excluding hoax and noise, to select the optimal portfolio. The fundamental question of Free Will, limited in investment selection, is answered through a new philosophical approach.

Methodologies for Determining the Opportunity Cost of Capital: Financing in the Selection of Investments

Objective: The objective of this study is to determine the rate of opportunity cost of capital and analyse project financing, within the scope of concepts and techniques in investment analysis and evaluation. Theoretical Framework: The concept of "opportunity cost of capital" is presented, as well as the methodologies for determining the rate of cost of capital for analysing and evaluating investments that business management faces, whether in new investments or in financing the growth of its current activity. Method: A descriptive method is appropriate to the objective and relates the theoretical framework for determining the cost of capital to decision-making and investment financing. Results: How the cost of capital is calculated in the various methodologies is detailed, highlighting the adequacy of the methodologies to the specific circumstances. An example is given of how to consider financing in cost of capital methodologies, emphasising that the value created by an investment does not derive from financing. Conclusion: The methodologies for determining the cost of capital for different financing structures are discussed and clarified. The difference between methodologies for determining the cost of capital and determining the present value of tax benefits from financing is demonstrated, making it clear that value creation results from the investment and not tax benefits from financing.

ASSESSMENT OF RISKS AND PROVIDING RECOMMENDATIONS TO MINIMIZE THEIR OCCURRENCE DURING TRANSPORTATION OF CARGO BY RAIL TRANSPORT.

Purpose: To assess the risks of emergency situations and provide recommendations for their minimization during the transportation of goods by rail transport. Method. On the basis of the methods of comparative typology, expert evaluations and system analysis for the route that runs through the industrial districts of Kryvyi Rih, using the methods of analysis of the causes and consequences of a key event, the combined diagram of the Ishikawa tree of a key event, risk maps of a key event, the analysis of hidden and direct priorities was determined indicator of the risk of the complex effect of negative factors of emergency situations during the transportation of heavy metals. The results. the authors identified the most likely causes of the emergency situation: 1) A rocket projectile that damaged the track, as a result of which the spontaneous exit of wagons occurred; 2) Exceeding the speed of a tank train; 3) Icy, which led to an increase in the braking distance and an accident; 4) Neglect of obstacles to movement before the movement of tanks, which in turn can lead to a stoppage of the technological process, cargo spillage and financial losses. A probabilistic risk assessment was carried out on the basis of an expert assessment of the risk operator and measures to reduce the occurrence of emergency situations were proposed with annual costs for them, thousand UAH. After that, a map of probabilistic risk assessment and a map of probabilistic assessment of risk management effects were created, which provide an opportunity for effective management and management of the probable cause of an emergency situation and the selection of financial investments for measures to reduce the occurrence of emergency situations. After that, it was proposed to use the combined wagon model 17-975(01) with all the necessary equipment as a means for quick localization and liquidation of the consequences of spills of emissions of hazardous substances during their transportation by railway transport in the event of an accident. The economic feasibility of using the proposed tool was also substantiated. The scientific novelty consists in the created model for the analysis of the risk assessment of an emergency situation, as well as the identification of possible causes and factors of the occurrence of emergency situations during the transportation of dangerous goods by railway transport, as well as the development of recommendations for their reduction. The practical significance is the implementation of the developed recommendations, based on the created model, for the formation of a special wagon, for operational needs, with the selection of the necessary equipment for the rapid implementation of the 1st stage of localization and liquidation measures.

ANALISIS KEBANGKRUTAN SILICON VALLEY BANK TERHADAP HARGA SAHAM PT. BANK CENTRAL ASIA Tbk

This article explores the resilience of the banking sector in the face of rising interest rates and the global economic slowdown caused by the recent measures of the Federal Reserve System (The Fed). Based on quantitative data with descriptive analysis and data visualization, the results show that the banking sector remains strong despite the volatile stock market. Notably, Bank Central Asia (BBCA) shares show higher stability and lower risk than Silicon Valley Bank (SIVBQ) shares, which experienced significant fluctuations due to bankruptcy in March 2023. Investors tend to be more attracted to BBCA because of its stability. This study also emphasizes the importance of a thorough understanding of the internal and external factors that affect stock value, as well as the importance of prudence in investment selection to reduce the risk of loss. Future researchers are advised to expand the scope of the study by including data from more institutions and exploring other factors that affect stock performance.

One-way ticket to the moon? An NLP-based insight on the phenomenon of small-scale neo-broker trading

We present an Natural Language Processing based analysis on the phenomenon of “Meme Stocks”, which has emerged as a result of the proliferation of neo-brokers like Robinhood and the massive increase in the number of small-scale stock investors. Such investors often use specific Social Media channels to share short-term investment decisions and strategies, resulting in partial collusion and planning of investment decisions. The impact of online communities on the stock prices of affected companies has been considerable in the short term. This paper has two objectives. Firstly, we chronologically model the discourse on the most prominent platforms. Secondly, we examine the potential for using collaboratively made investment decisions as a means to assist in the selection of potential investments.. To understand the investment decision-making processes of small-scale investors, we analyze data from Social Media platforms like Reddit, Stocktwits and Seeking Alpha. Our methodology combines Sentiment Analysis and Topic Modelling. Sentiment Analysis is conducted using VADER and a fine-tuned BERT model. For Topic Modelling, we utilize LDA, NMF and the state-of-the-art BERTopic. We identify the topics and shapes of discussions over time and evaluate the potential for leveraging information of the decision-making process of investors for trading choices. We utilize Random Forest and Neural Network Models to show that latent information in discussions can be exploited for trend prediction of stocks affected by Social Network driven herd behavior. Our findings provide valuable insights into content and sentiment of discussions and are a vehicle to improve efficient trading decisions for stocks affected from short-term herd behavior.

Research on investment selection of park-level integrated energy system considering electricity-heat-cooling-storage based on matter element extension

The park-level integrated energy system characterized by electricity heat cooling storage is regarded as a viable solution to energy and environmental crises due to its cleanliness and high efficiency. However, decision-makers encounter challenges in picking the optimum construction scheme. The paper introduces the matter element extension into the investment decision-making of the park-level integrated energy system. To begin, the paper analyzes the composition of the evaluation index system from the basic composition of the park-level integrated energy system, and establishes a standard system for comprehensive performance analysis, including economic, environmental, energy, security, and intelligence. Second, the subjective weight is calculated using the fuzzy analytic hierarchy process, the objective weight is calculated using the entropy weight. The matter element extension is used to evaluate the alternatives' performance. Finally, an industrial park in Jiangsu Province of China is selected as a case to verify. The results show that good comprehensive performance can be obtained by using photovoltaic, wind turbines, electric energy storage, ice storage, and heat pumps. The decision-making results will not be affected by the change in subjective and objective weight and the change in index weight within 20 %, but changes in matter-element classification would.

Study on the Impact of Investment Selection Factors for Knowledge Industry Centers on the Purchase Decision of Potential Investors

Study on the Impact of Investment Selection Factors for Knowledge Industry Centers on the Purchase Decision of Potential Investors

Behavioral Finance: Understanding Investment Decisions Among Individual Investors

In the early 1990s, India started to open up to the outside world. Steep GDP growth has been facilitated by privatization, liberalization, and globalization together. An important aspect in this was the investors. As a result, the administration thought of enticing more investors. Sophisticated investors from all over the world started to pay more attention to the Indian capital markets, especially after 2003. In this instance, it is vital to examine the How, Why, When, Where, and Amount of the Investors’ Investments. A further tool for comprehending the decision-making process of investors is behavioral finance, a relatively new field of study. Emotions and psychology play a part in the way investors make financial decisions. It says that people are not foolish or illogical. They are common individuals with diverse prejudices. Numerous elements, such as personality and demography, can affect how risk and return on investment are evaluated. They can also have an impact on investor psychology and attitudes, investment selection, and decision-making processes. In this study, we look at how Bengaluru’s individual investors’ choice of investment instruments is influenced by their personalities and demographics. Frequency analysis along with other statistical methods were used to describe the variables. Only respondents who have invested in any form of financial instrument at least once are selected for the study.

Entrepreneurial finance in Europe and the Russian war against Ukraine

AbstractPrior research has investigated how the prices of stocks and commodities as well as inflation levels have been affected by the Russian war against Ukraine. So far, however, we know little about the impacts of the war on the entrepreneurial finance sector. Prior research on the effects of unexpected exogenous crisis events on entrepreneurial finance suggests a strong negative impact on new and follow-on funding for entrepreneurial ventures. Our study regards the Russian war against Ukraine as an unexpected exogenous crisis event and explores its impact on the entrepreneurial finance sector. It goes beyond a mere sentiment and impact analysis and also explores the underlying reasons and mechanisms as well as potential response and coping strategies employed by entrepreneurial finance investors. Based on two surveys of European venture capital (VC) and private equity (PE) investors, we find that the war had a strong negative impact on the two types of investors and their respective funds. Both VC and PE investors report more risk-aversion of limited partners (LPs) and LPs leaving the market as important challenges resulting in an overall lower willingness of LPs to invest. This applies in particular to banks, insurance funds, and pension funds. On the portfolio firm level, securing equity financing and maintaining liquidity were considered pressing issues. Overall, the situation seems to be more difficult for portfolio companies of VC as compared to PE investors. For the former, the financing- and liquidity-related issues seem to be more existential and survival-threatening. Responding to these challenges, both VC and PE investors altered their industry focus and put more emphasis on entrepreneurial experience. Financial investment selection criteria such as financial valuation, profitability, and cash- as well as revenue-generating capacity also increased in importance. Again, differences between VC and PE investors exist. Our study has implications for entrepreneurial finance theory and practice and concludes with an agenda for research on the impacts of the Russian war against Ukraine on entrepreneurial finance.

Теоретичний базис формування інвестиційної банківської стратегії фінансування венчурного бізнесу

The article generalizes the theoretical basis and develops scientifically grounded approaches and models that allow to effectively form banking strategies for financing venture business. It is defined that the methodology for studying the formation of investment banking strategies for financing venture business can vary depending on specific goals and approaches. The most common methods that can be used to conduct such studies include: system analysis, quantitative and statistical analysis, case method, qualitative analysis, generalization method, and others. It is proved that the definition of investment banking strategy covers various aspects of the formation and implementation of investment strategies that banks use to support and develop venture business. This allowed to form the theoretical foundations of such a strategy, which are based on a number of elements, in particular: market analysis and definition of strategic goals; assessment of risks and opportunities; development of an investment strategy; the process of selection and evaluation of investments; investment management and monitoring; exit from investments; ethical and regulatory aspects. Theoretical approaches to determining the investment banking strategy for financing venture business are systematized. Thus, among the most common theories in the scientific space, the following theories were allocated: ecosystems of venture capital, institutional support, globalization of venture capital, crowdfunding and alternative financial mechanisms, sustainable development and green investments. Overall, venture capital business has been proven to be an important element of investment banking strategy, as it not only expands investment opportunities but also promotes innovation and economic development. Banks that actively incorporate venture capital investments into their strategy can gain significant competitive advantages and increase profits.

Directional distance based cross-efficiency evaluation and decomposition for parallel two-stage systems: An application to equity funds

As an effective approach in ranking decision making units (DMUs), cross-efficiency evaluation is only extended to two basic network systems: series and parallel, which is not applicable to the common complex network system in reality. By using the directional distance function (DDF), this paper extends the cross-efficiency evaluation to a complex system called the parallel two-stage system, which consists of several independent parallel processes and each of them is a sub-system with a general two-stage series structure. The proposed method is able to decompose the cross-efficiency measure of the system into the weighted average of those of processes, stages and overall stages, respectively, and as a result, successfully achieves the layer-by-layer decomposition of cross-efficiency measures under complex nested networks. An empirical study on 40 open-ended equity funds in China from 2018 to 2020 verifies that the newly proposed method not only has a stronger performance discrimination power than self-evaluation, but also can identify the relationships among efficiencies of the system, processes and stages, and meanwhile it can reflect the effects of processes and stages on the system. More importantly, our method has a better practical value for actual fund investment selection.

Green technology investment selection with carbon price and competition: One-to-many matching structure

With the deterioration of natural resources and the aggravation of environmental pollution, there is a growing imperative to implement industrial green reform through green technology investment (GTI). This paper constructs a nonlinear dual-objective function by drawing on the theory of two-sided matching under the carbon trading regulation, aiming to examine GTI selection decisions made by two oligarchic manufacturers (i.e., oligarchs) and a monopoly supplier (i.e., supplier). The supplier offers multiple green technologies, while oligarchs rack their brains to buy green technologies in an attempt to exploit their social, economic and environmental potentials. Available technologies vary in terms of their environmental efficiency and cost. Then, a two-sided matching mechanism is constructed to explore the availability of stable matchings and examine the impacts of the carbon price and green improvement coefficient on GTI, product pricing decisions and profits within a competitive environment. Finally, a Monte-Carlo experiment is designed to analyze the impact of uncertain market risks on supplier's decisions. The results show that there is a two-sided matching mechanism that enables oligarchs and suppliers to obtain stable matching solution sets. Higher carbon prices lead to higher product prices, lower market demand, and improved environmental performance. Product price and market demand are positively correlated with investment volumes of oligarchs themselves and negatively correlated with those of their competitors. Investment risk has a certain negative impact on suppliers' profitability.

An Experimental Private Small Hydropower Plant Investments Selection Classification System

Investment selection problems and models are crucial for humans, communities, and states. Private small hydroelectric power/ hydropower plant investments (PSHPPIs) selection problem is a unique one in those problems and models. Many available scientific methods can be implemented on this research topic. One methods group is type-2 Mamdani’s type fuzzy inference systems (FISs). This study presents an experimental one-node general type-2 4-zslices Mamdani’s type FIS model for PSHPPIs selection. There are 3 input variables (total estimated electricity generation: M1, total estimated cost: M2, change in the average runoff: M3), 1 output variable (O1: selected/unselected, selection classification of PSHPPIs), and 49 rules. M1 is designed in 5 triangular and trapezoidal general type-2 4-zslices fuzzy membership functions (MFs), M2 in 5 triangular and trapezoidal general type-2 4-zslices fuzzy MFs, M3 in 5 Gaussian type-2 4-zslices fuzzy MFs, and O1 in 2 Gaussian type-2 4-zslices fuzzy MFs. All modeling details are finalized by a human-expert decision process. JuzzyOnline V2.0, a browser-based platform of Juzzy (a Java-based library: Juzzy toolkit), is used for all FIS modeling and calculation activities. Five PSHPPI options assumed to be in their very early investment stages in Turkiye are evaluated in an experimental application. It is clear that an improved, tuned, and fine-tuned version of this model will help private investors to take more convenient/satisfying actions/decisions in a very short evaluation period in their PSHPPIs decision processes. An automatic investment selection classification system can be built in an appropriate development period after experiencing many methods and models. This study is one of the open-science humanoid robot, robot and platform development activities entitled Global Power Robots and Platforms: GPRP/GPRAP (Global Power Plants Developers: GP2D/G2PD/GPPD, Global Power Plants Engineers: GP2E/G2PE/ GPPE, Global Power Plants Owners: GP2O/G2PO/GPOO, Global Power Prediction Systems: GP2S/G2PS/GPPS), Global Profile Analyses Systems, and Global Social Network Analyses Systems.

Novel score function and standard coefficient-based single-valued neutrosophic MCDM for live streaming sales

Single-valued neutrosophic sets (SVNS) provide a comprehensive approach to express uncertainty in decision scenarios, surpassing the utility of fuzzy sets (FS) and intuitionistic fuzzy sets (IFS). Yet, current SVNS score function concepts stem from FS and IFS construction methods, showing inconsistencies. Thus, we introduce a novel SVNS score function based on inherent uncertainty essence. Additionally, we devise a standard coefficient to gauge SVNS standardization akin to fuzzy sets. Addressing SVNS researchability and limitations in fundamental concepts, especially the score function, we propose an SVNS-based multi-criteria decision-making (MCDM) model. This leverages the new score function and standard coefficient. We demonstrate its effectiveness on two decisions: “software engineer recruitment” with known weights and “investment selection” with unknown weights. Ultimately, we successfully applied the model to the field of live streaming sales to solve the actual MCDM problem. By comparing with existing methods, we affirm the model's validity and practicality. Compared to prior approaches, the new method exhibits: (1) Enhanced stability and credibility in result values and rankings, promoting robust optimal solutions. (2) Reduced computational steps and workload, enhancing usability and practicality.

Ordered weighted utility distance operators and their applications in group decision-making

In multiple attribute group decision-making (MAGDM), a consensus exists that the psychological factors of decision makers (DMs) generally influence their choice of optimal alternatives. To quantify well the influence of DMs’ risk attitudes on the group decision-making process, this paper develops a new approach to MAGDM by introducing DMs’ utility functions into the aggregation process. First, the ordered weighted utility distance (OWUD) operator is constructed by introducing DMs’ utility functions into the distance operator. As a novel operator, the OWUD operator not only satisfies both the basic features of distance measures and the desirable properties of aggregation operators, but also has some unique characteristics. Then, the linear risk tolerance (LRT) utility function is further used in the OWUD operator as the basic utility function, and a specific form of the OWUD operator, which is named as the ordered weighted-linear risk tolerance utility distance (OW-LRTUD) operator, is proposed. The OW-LRTUD operator can quantify well the influence of DMs’ risk attitudes on the group decision-making process. It also has an analytically tractable form and includes many well-known distance measures and aggregation operators, and thus can be applied to many different kinds of decision-making problems. Subsequently, to determine the weights of the OW-LRTUD operator, an extension of the maximum Bayesian entropy method is proposed by incorporating the prior known weight information and different risk attitudes of all individual DMs. An approach to MAGDM based on the OW-LRTUD operator and the proposed weight determination method is developed. An application for determining the optimal alternative in the investment selection is provided to show the feasibility, effectiveness and robustness of our approach in practice, and the corresponding sensitive analysis illustrates the influence of DMs’ risk attitudes on the group decision-making process.

Killing two birds with one stone? Sound investment with social impact

AbstractThis paper uses a novel dataset on investments by the European Bank for Reconstruction and Development to quantify a (sizeable) trade‐off between the impact and financial objectives of a large lender. The unique feature of this dataset is ex ante records of impact. These are made at the early stages of work on each transaction alongside probability‐of‐default scores. Impact scores are further updated at the final approval stage with around 55 percent of transaction concepts translating into signed deals. We show that this approach delivers a simultaneous selection of debt investments on the quality of credit and impact with a sizable trade‐off between pursuing commercial and development objectives. For commercially riskier investments, impact characteristics have a greater bearing on the probability of an investment going ahead. We further use machine‐learning analysis to show that the impact of some investments is strengthened prior to project approval.

An extended hesitant fuzzy set for modeling multi-source uncertainty and its applications in multiple-attribute decision-making

Handling uncertainty has always been a pervasive and formidable challenge in the realm of multiple-attribute decision-making (MADM). Hesitant fuzzy set (HFS) can retain several different values, making it a useful tool for expressing the uncertainty experienced by decision-makers (DMs). Recently, the introduction of the normal wiggly hesitant fuzzy set (NWHFS) has aimed to uncover potential uncertain information within HFS, and it has been empirically demonstrated to enhance the rationality of MADM. However, it is essential to acknowledge the role of probabilistic information, which assesses the likelihood of evaluation values occurring and is a factor that cannot be ignored in MADM. In this current study, we propose an innovative approach known as the mixed-normal-based hesitant fuzzy set (MNHFS), considering both probabilistic information and the potential uncertainty. To distinguish MNHFSs in MADM, we defined a score function and distance measures. Subsequently, we apply the proposed MNHFS to TODIM (an acronym in Portuguese for interactive and multiple attribute decision-making) and investigate its validity and superiority in a case study involving the selection of a promising venture capital investment. Finally, we provide a visualization method to illustrate the internal uncertainty of the decision results and offer insights into investment risk.