Investment Losses Research Articles

The impacts of land reforms on water infrastructure use and investment: A case study of the Biri dam, Zimbabwe

This paper sought to answer the question, how did Zimbabwe land reforms impact on water use, property rights and investment in water infrastructure? This was done for Biri dam in Middle Manyame subcatchment. Landuse and landcover changes from 1984 through the land reform period to 2019 were analysed through GIS and remote sensing techniques. Water allocation and dam levels records were analysed to understand water use patterns within the subcatchment in the aftermath of the land reforms. Interviews were used to investigate perceptions on property rights and investment in water infrastructure. The study found that construction of the Biri dam coincided with the commencement of the Fast-Track Land Reform Programme. As a part of the reform process, the custodianship of the Biri dam was moved to the national water authority. Consequently, farmers who had invested in the dam lost their investment. Changes in land ownership affected water use, so much that between 2007 and 2020 the dam mostly maintained water storage levels above 70%. The study attributed the 85% decrease in land put under irrigation from 1984 to 2019 to the land reforms. Municipal water use, rather than agriculture for which the dam was primarily constructed, has now become the largest water user in the subcatchment. The study concluded that land reforms impacted negatively on water utilization and loss of investment in water infrastructure. The study recommends that land and water changes be implemented concurrently, taking into account how changes in one resource affects the other.

Research on Emotional Leverage Effect of Capital Flow of Well-known Investment Institutions

China’s capital market started late, compared with developed countries, China’s individual investors account for a larger proportion. Because individual investor does not have the specialized investment knowledge and the mature investment psychology, its investment behavior often will receive the external factor the interference to produce “The herd effect”, therefore, the well-known investor institutions can rely on the reputation effect brought by their own popularity to influence the stock price fluctuation by influencing the investor sentiment, thus exceeding the influence degree of the corresponding buying and selling fund flow. This paper defines the above process as the emotional leverage effect of well-known investment institutions. In this paper, we use principal component analysis to construct the index of investor sentiment, and use correlation test to find that the well-known investment institutions, by virtue of their own reputation, make their capital flow have a significant impact on investor sentiment, there is a significant positive correlation between investor sentiment and the fluctuation of individual stock prices in the industry. Small and medium-sized investors will suffer investment losses because of their blind faith in the trading strategies of well-known institutions. In order to further enhance the protection of investors’ interests, this paper puts forward suggestions to improve the protection mechanism of small and medium-sized investors’ rights and interests from the perspective of information disclosure and policy supervision.

Synthesis of wastewater treatment process (WWTP) and supplier selection via Fuzzy Analytic Hierarchy Process (FAHP)

Wastewater treatment process (WWTP) is essential in every manufacturing company to meet stringent discharge regulations and reduce environmental impacts. The wastewater generated from manufacturing companies need to be treated in a suitably designed WWTP. However, with countless wastewater treatment technologies available in the market, WWTP technologies are usually selected based on vague assumptions and past experience. This approach to technology selection may result in high loss of investment to a company on the long run. In addition, there is a paradigm shift in the current manufacturing industrial practise towards more sustainable practices. Therefore, aspects such as carbon footprint and area footprint are important criteria to be considered during the synthesis of WWTP. In that context, this work aims to develop a decision-making tool in technology selection for the synthesis of WWTPs driven by economic and environmental incentives while meeting with local discharge regulations. As multiple optimisation objectives are involved, Fuzzy Analytic Hierarchy Process (FAHP) is adapted in this work. FAHP assigns weighting factors to criteria and alternatives based on judgements from industrial domain experts. By implementing FAHP, the synthesised final WWTP traded off at a maximum degree of satisfaction of 67.5% had reduce 244.44 USD/day of total investment cost, 134.43 kg CO2-eq/day of carbon footprint and 2 m2 of area footprint. In addition, this work had extended further the decision-making to supplier selection of wastewater treatment equipment based on the wastewater treatment technologies from the synthesised sustainable WWTP. A case study on a sago wastewater treatment process is demonstrated in this work with this proposed approach.

ІНВЕСТУВАННЯ ЗА ЕSG-ПРИНЦИПАМИ ЯК ВИЗНАЧАЛЬНИЙ ЧИННИК ВПЛИВУ НА КОНКУРЕНТОСПРОМОЖНІСТЬ МЕТАЛУРГІЙНИХ ПІДПРИЄМСТВ

The article states that the traditional model of economic growth of metallurgy due to the export of energy-intensive products no longer works, new impulses and effective tools are needed to transform the current model of economic growth to the latest model – the model of low-carbon production. Emphasis is placed on the importance of ESG-investment in the process of transformation to a low-carbon economy and its impact on the competitiveness of enterprises. It is substantiated that the introduction of ESG-investment requires the formation of a certain regulatory environment, and accordingly to clarify the substantive component of this concept and its operationalization, bringing the concept to a form that will work with it on a practical level, operate it in solving specific analytical and forecasting tasks, verify or refute research hypotheses. The author’s definition of ESG investing is proposed as an investment aimed at minimizing ESG risks, reducing environmental pollution to levels that do not harm human health and natural ecosystems, as well as strengthening social responsibility and improving corporate governance. It is substantiated that Ukraine’s delay in ratifying international regulations on the introduction of ESG-investing and ignoring the world experience in creating a regulatory environment for investing in ESG-principles threatens metallurgical enterprises with the loss of investors and, accordingly, competitive positions in the global metal market. Using specific examples from world experience, the need to recognize the standardization of reporting on the impact of business on climate and environment, one of the priority issues in the formation of the regulatory environment of ESG-investment. An arsenal of effective measures for the formation of the regulatory environment of ESG-investment, the introduction of which in domestic practice will allow to make effective and optimal management decisions to maintain the position of domestic metallurgical enterprises in the TOP-10 leading countries in metal production.

Implementation of Moisture-Evaporation Decision Tree for Stock Rate Prediction

– Stock rate prediction always attracts investor; it is not only because of interest but also act as a big challenge and a mystery. This problem is very complex in nature and it is quite dynamic type of problem. A lot of volatility always remains and the Global stock market makes it a more challenging and interesting job of stock prediction. Predicting stock prices is a very risky job which may have lot of errors. These errors needs & should be minimized so that financial losses in investment in stock market can be minimized. In this research paper ,we have applied supervised machine learning algorithm known as moisture and evaporation decision tree (MEDT).To predict stock prices, we have applied last five years of Historical data with attributes: open high, low and close rates and volume of the particular stock. MEDT algorithm on 5 year’s stock data of (historical prices) has been taken for experiments. As we already know that the market news always affects Stock price movements. The current research we have considered positive or negative news about particular stock. If the news is positive it is called moisture and it assigned a weight between 0 and 1 based on the type and the importance of the news for that particular stock. The news is very impactful then and its moisture value maybe point 0.8, otherwise news is less impactful then its value may vary 0.1 or 0.2. If the news is impactful on the stock rate in the positive direction then its magnitude will be positive moisture value otherwise it will be a negative moisture value. Technique is seen successful in 88% cases.

A financial statement fraud model based on synthesized attribute selection and a dataset with missing values and imbalanced classes

Many financial fraud events have occurred over the past few decades. These events have led to massive losses for investors. Hence, government officials have begun to focus on the problem and have issued several decrees (acts) on financial fraud. Many scholars have explored the factors of financial fraud, and although their results performed well, most studies have not generated a set of useful rules to support auditors. Furthermore, data on financial statement fraud usually constitute an imbalanced class problem, and previous work minimally addresses this problem. Therefore, this study, based on the handling of missing values and imbalanced classes, builds a detecting model of financial statement fraud. First, it utilizes listwise and pairwise deletion to remove missing values. Second, it proposes three merged attribute selection methods and applies a nonlinear distance correlation to select important attributes. Third, it applies undersampling and oversampling to address the imbalanced classes. Finally, it uses rule-based classifiers to generate a set of useful rules. In practice, this study employs a list of fraudulent companies to collect data on financial statement fraud. We summarize the results as follows: (1) the pairwise deletion removes fewer records than does listwise removal in handling missing values; (2) the merged attribute selection (Com_I4) has the best performance on the four evaluation criteria; (3) the oversampling can enhance accuracy, and has the lowest type 1 and type 2 errors; (4) the random forest of Com_I4 can build the optimal model of financial statement fraud in the pairwise deletion and random oversampling; and (5) the results show that the ensemble learning (random forest) is a robust model in this study. Finally, these results in this study can be provided to practitioners, investors, and auditing personnel as references.

Foreign exchange market response to pandemic-induced fear: Evidence from (a)symmetric wild bootstrap likelihood ratio approach

This study tested whether pandemic-induced fear is a predictor of the exchange rate returns of seven major currencies – Australian dollar, Canadian dollar, Swiss franc, yuan, EURO, pound sterling, and yen. Daily data on US dollar-based exchange rate returns and the global fear index for COVID-19 pandemic for the period 10-02-2020–02-04-2021 were used. Symmetric and asymmetric wild bootstrap likelihood ratio tests were employed in testing the relationship. The symmetric test results showed that pandemic-induced fear is capable of predicting the exchange rate returns of the Swiss franc, yuan, and the EURO. Specifically, negative relationships were recorded between their returns and the global fear index for pandemics. The asymmetric test results however showed that increasing pandemic-induced fear leads to decreases in the returns of the Australian dollar, Canadian dollar, Swiss franc, yuan and EURO. Overall, this study showed that pandemic-induced fear is a predictor of exchange rate returns. It is therefore suggested that the maintenance of stability in the financial system should be treated as an integral part of policy responses designed to mitigate the adverse effects of pandemics. This way, economic agents will not be forced to move their investments to foreign currency-denominated assets due to fear of investment losses.

Crowdfunding: Social Enterprise and Corruption Counteraction in This Sphere

At present, crowdfunding is viewed as a prospective trend in entrepreneurship, an important element of ensuring the economic development of the country. Modern research of crowdfunding mainly focuses on success indicators for financing various projects in this segment of economy. However, the specific technical situation of its functioning does not eliminate the risk of financial losses for investors from various criminal actions of investment seekers, which makes it necessary to assess these risks and pay attention to the problems of current normative regulation of crowdfunding. The authors study different features of crowdfunding, analyzes the models where the risk of abuse is highest. They also describe signs of crimes in the sphere of crowdfunding, primarily signs of crimes indicating fraudulent actions, and presents factors that make it possible to predict a factual or potential fraud in crowdfunding. The conducted research allowed the authors to conclude that the stress that Russian legislation puts on informing the investor about the persons that seek investment, on their investment proposals, on limiting the sum of investment, is not an effective measure of preventing fraud and that additional measures for protecting investors are necessary.

AN ONLINE CREDIT AGREEMENT WITH COLLATERAL IN INDONESIA

Along with the rapid development of information technology which in turn has an impact on economic activity around the world, financial technology is here to provide facilities in the provision of financial services for the community. The ease of convenience offered through unsecured online loans carries the risk of loan defaults made by debtors. The purpose of this research is to find out what is the urgency of the need for collateral as one of the requirements for submitting online loans and how online registration of fiduciary collaterals can be a preventive measure for bad credit in online credit distribution. This study uses a normative-juridical research method. The result of this research is that there is a collateral that the online lending agreement functions as a legal umbrella so that debtors' obligations to creditors are fulfilled so that they avoid default, default, and even investor losses in Fintech P2P Lending activities. The importance of having a fiduciary collateral that is registered in the credit agreement online is to avoid a legal vacuum (rechts vacuum) or legal vacuum (wet vacuum) when there is default or default by the debtor.

Investment Risk Analysis On Bitcoin With Applied of VaR-APARCH Model

Investment can be defined as an activity to postpone consumption at the present time with the aim to obtain maximum profits in the future. However, the greater the benefits, the greater the risk. For that we need a way to predict how much the risk will be borne. Modelling data that experiences heteroscedasticity and asymmetricity can use the Asymmetric Power Autoregressive Conditional Heteroscedasticity (APARCH) model. This research discusses the time series data risk analysis using the Value at Risk-Asymmetric Power Autoregressive Conditional Heteroscedasticity (VaR-APARCH) model using the daily closing price data of Bitcoin USD period January 1 2019 to 31 December 2019. The best APARCH model was chosen based on the value of Akaike's Information Criterion (AIC). From the analysis results obtained the best model, namely ARIMA (6,1,1) and APARCH (1,1) with the risk of loss in the initial investment of IDR 100,000,000 in the next day IDR 26,617,000. The results of this study can be used as additional information and apply knowledge about the risk of investing in Bitcoin with the VaR-APARCH model.

“Theoretical Model on CEO Overconfidence Impact on Corporate Investments”

This theoretical model estimates the impact of CEO overconfidence on corporate investment decision making process. The model helps us understand how CEO overconfidence impacts corporate investments by quantifying the expected losses and opportunity losses in corporate investments due to CEO overconfidence. This aims to raise organizational awareness about the destructive effects of this bias and ultimately to incentivize organizations to address the personalities of CEO overconfidence. Literature in this area of research supports the existence of destructive effects on corporate investments due to CEO overconfidence.The model focuses on a corporate environment in which a corporate investment can take a positive or negative NPV value. The model also centers on a population composed of both overconfident and non-overconfident CEOs. Non-overconfident CEOs use a Bayesian learning rule to estimate project returns, while overconfident CEOs use a non-Bayesian rule as they tend to commit biases in estimating project returns. A decision tree is then formulated based on the type of corporate investment, level of CEO overconfidence, and corporate investment decision in order to derive the theoretical model.

RETRACTED ARTICLE: Influence of enterprise cloud computing database application and enterprise debt financing based on SVM algorithm: internal control quality analysis

The continuous deepening of the development of my country's market economy has brought more development opportunities to Chinese enterprises, which has made the development of Chinese enterprises more rapid. A financial crisis in an enterprise will bring about disastrous consequences such as investment loss, unemployment of employees, and unrecoverable credit, which will further affect the country's economic development, financial security and social stability. Therefore, the impact of corporate cloud computing database applications and corporate debt financing has attracted widespread attention, and the impact of corporate debt financing capabilities and debt financing costs have become the main issues studied in this article. This article uses scientific methods to establish an effective financial crisis early warning model, conducts an empirical analysis of the financial data of listed companies in my country, selects indicators that have a significant impact on the financial status of the enterprise, and obtains an accurate early warning classification of the financial status of the enterprise, which verifies this article The feasibility and effectiveness of the proposed early warning ideas, early warning index system and early warning methods. This article also focuses on the internal risk management methods of enterprises, and makes an in-depth study on whether high-quality internal control can weaken creditors' expectations of risks caused by corporate strategic differences, thereby weakening the relationship between strategic differences and corporate debt financing. Based on the conclusions obtained, this article puts forward a number of constructive suggestions for Chinese enterprises to optimize their strategic positioning and control operating risks to alleviate financing difficulties, which have certain theoretical significance and practical value.

Potential Legal Conflict For The Implementation Of Financial Services Authority Regulation Number 65 /POJK.04/2020

Financial Services Authority Regulation Number 65 / POJK .04 / 2020 was promulgated to increase effectiveness and justice in law enforcement in the capital market sector. The form of legal protection regulated is the Return of Unauthorized Profits and the Investor Loss Compensation Fund (Disgorgement Fund). The research objective in this paper is to find potential legal conflicts that arise in the implementation of the Financial Services Authority Regulation Number 65 / POJK .04 / 2020. The research method, this type of research is normative juridical research, which uses secondary data. The findings obtained are that there are two potential legal conflicts. First, there is a potential conflict between the Financial Services Authority Regulation Number 65 / POJK .04 / 2020 and Law Number 37 of 2004. Second, the Potential Conflict between the Financial Services Authority Regulation Number 65 / POJK. 04/2020 with Law Number 37 the Year 2004 and Law Number 40 the Year 2007, which will obstruct legal objectives.

Past Stock Returns and the MAX Effect

This paper investigates how past stock returns affect investors’ lottery demand. We show that the maximum daily return (MAX) effect, first documented by Bali et al. (Maxing Out: Stocks as Lotteries and the Cross-Section of Expected Returns) is predominantly concentrated among stocks that have worst returns in the recent past. In contrast, for stocks that have recorded best past returns, the MAX effect becomes much weaker or even disappears. Our findings hold in the presence of a variety of control variables including the conventional return predictors, stock mispricing, stock price proximity to its 52-week high, and capital gains overhang. We interpret it as evidence that investors’ lottery demand intensifies in the presence of investment losses, consistent with the notion of time varying and state dependent nature of investors’ lottery preference. We further show that a self-financing portfolio that goes long in stocks with the worst past returns and low MAX and short in stocks with worst past returns and high MAX yields statistically and economically significant abnormal returns after risk adjustment by standard asset pricing models.

Detection of False Investment Strategies through FWER and FDR (Seminar Slides)

Financial systems rarely allow experimentation. For example, we cannot reproduce the flash crash of 2010 while controlling for environmental conditions. As a result, much financial research relies on the statistical analysis of finite (historical) datasets, where: (a) Time series datasets are limited, and (b) The investment universe is limited. The implication is that a large number of hypotheses are tested on the same observations. In the context of asset management, this situation leads to false investment strategies and losses, particularly among quantitative funds. This seminar explains how to detect false investment strategies by controlling for the familywise error rate (FWER) and the false discovery rate (FDR) of an organization. It is part of Cornell University's ORIE 5256 course.

The Impact of Corporate Performance on Mental Accounting and Loss Aversion in Financial Decisions

This study investigates the effect of the organization performance on two psychological biases, mental accounting and aversion to loss, on financial decisions to both investors and managers. To achieve this, two experiments are conducted. The first experiment consists of 40 graduate students as investors, while the second one consists of 40 accountants in a real estate company as managers. The results of the study indicate that the performance of companies impacts both mental accounting and aversion to loss of investors, whereas the performance of companies affects the mental accounting of managers in making their financial decisions but does not affect the aversion to loss.

Water–Food–Energy Nexus Tradeoffs in the São Marcos River Basin

Given its potentialities and characteristics, energy generation, food production, and water availability have a strong interdependency and correlation. Water is needed to produce energy and food, while energy is required to produce water and food. This nexus brings several challenges when scarce water resources must be allocated among competing uses, often in the form of unexpected tradeoffs. Addressing those challenges requires knowledge about the water–food–energy nexus and the associated tradeoffs to support water allocation and management decisions. Those tradeoffs are still not properly understood in the uncertain and stochastic context of water availability. When not properly accounted for, the results are conflicts, loss of investments, environmental impacts, and limited effectiveness of sectoral policies, all of which undermine a country’s development model relying on water and energy security. This paper addresses the competitive uses of recent irrigated agriculture expansion and existing hydropower production in a Brazilian watershed with water conflicts, assessing the economic tradeoffs and water values between energy and irrigated agricultural production under uncertainty. An explicitly stochastic hydro-economic model is used to determine water’s economic value and its variation in space and time. Results indicate that the agricultural benefits outweigh the potential energy losses, and the best course of action should explore an economically compensated reallocation strategy, upon negotiation among users, rather than imposing water supply cutbacks to the agriculture sector.

Two-dimensional stochastic modeling for predicting bankruptcy for manufacturing companies

Increasing accuracy of the model prediction on business bankruptcy helps reduce substantial losses for owners, creditors, investors and workers, and, further, minimize an economic and social problem frequently. In this study, we propose a stochastic model of financial working capital and cashflow as a two-dimensional Brownian motion X(t) = (X1(t),X2(t)) on the business bankruptcy prediction. The probability of bankruptcy occurring in a time interval [0,T] is defined by the boundary crossing probability of the two-dimensional Brownian motion entering a predetermined threshold domain. Mathematically, we extend the result in Fu and Wu (2016) on the boundary crossing probability of a high dimensional Brownian motion to an unbounded convex hull. The proposed model is applied to a real data set of companies in US and the numerical results show the proposed method performs well.

Dynamic portfolio choice and information trading with recursive utility

This paper examines a consumption-portfolio allocation and information trading problem with recursive utility in continuous time when stock returns are unobservable and when investors have to learn about it by using the stock price and the information products they purchase. We derive optimal consumption, portfolio policies, and information trading strategies in a semi-closed-form. Our quantitative analysis shows that ignoring information trading opportunities leads to significant economic losses for investors, particularly in a high-uncertainty case. More importantly, using the recursive utility, we innovatively find that the elasticity of intertemporal substitution (EIS) has a significant impact on an investors’ information trading. In particular, the lower the EIS of the investor, the more information products purchased by the investor. This paper provides an important economic foundation regarding trading information products in the financial market.

Risk Profiling and Investment Instruments among Youth in Malaysia

The investment instruments in a financial market can be in various form such as common stocks (shares in a stock exchange), unit trust (government-backed and private) and money market instruments. Each of these instruments has their own risk characteristics that require a sufficient level of understanding on the risk tolerance level that people do not always comprehend. It is argued that only after the understanding of one’s risk profile an individual will be ready to invest optimally. This is because the misunderstanding of the risk tolerance level will result in mismatching between risk profile and the type of instruments hence increasing the chances of losses in investment. Thus, it is crucial for potential investors to understand their risk profile before they can even select for any of the instruments to invest. In order to resolve the above issue, this study is developed to facilitate individuals to recognize the amount of risk that they can absorb in order to help them identify the suitable types of investment instruments to participate in. In other words, this study aims to propose a conceptual framework to facilitate individuals in identifying their risk profile before embarking in any types of investments. This study will broaden the scope of literature in this area by providing evidence on Malaysian environment exclusively from the perspective of generation Y and Z.