Original Investment Research Articles

Evaluating Portfolio Performance Using Technical Indicators and Financial Ratio for Stocks in NSE by PyPortfolioOpt

Financial indicators play a crucial role in stock market investment. Generally, a financial ratio engulfs a stock's financial condition. "Technicals" are heuristics that play a crucial role in identifying a stock based on short-term price movement indications. As a statistically dependent stock market, the NSE remains a well-suited stock exchange for observing technical indicator movements. Our research considered 7 stocks highly dependent on market capitalization (among the top 50 stocks by market capitalization). Our selection criteria were supported by their strong emphasis on financial ratios through EPS, current ratio, and P/E ratio. Also, these stocks were tested within the parameters of successful technical price movements. Finally, we applied portfolio optimization to support investment guidelines proposed by technical measurements and financial ratios. We have proposed the successful creation of a portfolio for the next 8 days, expecting a price rise. We successfully affiliated a portfolio that amplified a Sharpe ratio generation of more than 1. Our overall portfolio return is more than 8.525% in 8 days, resulting in a yearly expected return greater than 4.633 times that of the original investment. Hence, this proves our claim that a mixture of financial ratios and technical indicators provides sufficient evidence for a quality portfolio return.

Spatial analysis of regency city minimum wage, labor force, regional original income and investment affecting gross regional domestic product in central Java province in 2022

Economic growth in Central Java Province is influenced by various regional economic factors, such as the Regency/City Minimum Wage (UMK), labour force, Regional Original Revenue (PAD), and investment, which play an important role in increasing Gross Regional Domestic Product (GRDP). However, economic disparities between regions in the province require in-depth analysis to understand how these factors interact with each other and affect GRDP, as well as to formulate more equitable and sustainable development policies. This study aims to analyze the influence of the variables of Regency/City Minimum Wage (UMK), Total Labor Force (Work), Regional Original Income (PAD), Investment (Foreign Investment and Domestic Capital Investment) on Gross Regional Domestic Product (GRDP) per capita in Central Java Province in 2022 and spatial analysis of these factors in 35 Regency / City in Central Java Province. The analysis is quantitative descriptive using regression analysis techniques and spatial analysis with statistical tests on the GeoDa program. The results show that all four variables, namely MSEs, labour force, PAD, and investment, have a significant influence on GRDP with probability values less than 0.05, indicating that these factors directly contribute to economic growth in Central Java. The pattern of economic concentration found mainly around urban areas, such as Semarang City, suggests an economic spillover effect that drives growth in the surrounding areas. These findings reinforce the important role of investment, PAD management, as well as job creation and MSE adjustment in supporting more equitable and sustainable economic development across the province. This study provides strategic insights for more equitable and sustainable economic development planning in Central Java Province.

Machine learning Ethereum cryptocurrency prediction and knowledge-based investment strategies

This work proposes a novel methodology to help in decision making in the cryptocurrency market. Two investment strategies have been designed for Ethereum (ETH), based on predictions of the price and trend of this cryptocurrency using real data. The two Ethereum cryptocurrency prediction systems rely solely on past values of other contextual stock indices, market indicators and online trends, and ignore any technical indicators of price evolution. Real data from cryptocurrency market has been collected and processed with different feature selection methods. Applying a regression approach with Gated Recurrent Unit (GRU) and Long Short-Term Memory (LSTM) networks, prediction models for the ETH price for 1, 7 and 15 days are obtained and compared. Also, support vector machine (SVM) is applied to predict the ETH price trend by applying a classification approach. In both approaches, sentiment analysis has been included to check its effect on the prediction results. The reliability of these prediction models in the current market has been evaluated by designing two original knowledge-based investment strategies. They are tested over two different time periods with real cryptocurrency market data. The results show that it is possible to generate up to 5.16 profit factor with few operations using these models. Furthermore, adding sentiment analysis has shown to have little influence. In this way, we contribute to the advancement of our knowledge of this volatile and still young cryptocurrency market, and specifically of the evolution of Ethereum and the factors that can influence its behavior.

Overlapping portfolio holdings and unique sources of emerging market risk

Momentum, size, and low volatility in emerging markets regularly exhibit increased correlations across factors and markets in periods of negative returns. I provide a framework to distinguish a unique source of risk from a set of factors in the stage of portfolio formation. The framework is based on discarding duplicate positions that exceed half the portfolios in periods of factor comovement. Unique factors eliminate rising correlation and factor crashes. The results are robust for the most recent financial shocks. For practitioners, the approach helps in distinguishing original investment strategies and provides opportunities for active management in emerging markets.

Process simulation and economic assessments for biodiesel production catalyzed by green Nanocatalysts

AbstractThe biodiesel production catalyzed by naturally derived catalysts such as calcium oxide (CaO) and sulfonated carbon catalysts achieved high biodiesel yield at moderate operating conditions. However, very few studies were conducted to evaluate the economic feasibility of industrial‐scale production of biodiesel catalyzed by both green catalysts of CaO and sulfonated carbon catalysts. The current study aims to assess the technical competency and economic feasibility of industrial‐scale production of biodiesel catalyzed by two processes 1.) CaO catalyst and 2.) sulfonated carbon catalyst. Process simulations via Aspen Hysys were carried out to perform material and energy balances for both process configurations designed earlier with respect to the base catalyst (CaO) and acid catalyst (sulfonated carbon) used. Economic analysis was initiated after the equipment sizing and costing had been carried out. Total capital investment, total manufacturing cost, and key performances of the rate of return, payback time, breakeven point, and net profit after‐tax rate were calculated for each process. Based on the economic analysis, the computed return on investment (ROI) is 105.36%, and it has a low payback period of 0.94 year to offset its original investment. The discounted cumulative profit (NPV) analysis shows that breakeven was achieved in the 3rd year. On the other hand, for the plant that utilizes sulfonated carbon in the transesterification reaction, the computed ROI is 14.02% with a payback period of 7.13 years, and the breakeven was achieved in the 9th year. In conclusion, the manufacturing plant of transesterification reaction catalyzed by CaO catalyst appeared as the most promising pathway either technically or economically.

Canonical portfolios: Optimal asset and signal combination

This paper presents a novel framework for analyzing the optimal asset and signal combination problem. Our approach builds upon the dynamic portfolio selection problem introduced by Brandt and Santa-Clara (2006) and consists of two stages. First, we reformulate their original investment problem into a tractable one that allows us to derive a closed-form expression for the optimal portfolio policy that is scalable to large cross-sectional financial applications. Second, we recast the problem of selecting a portfolio of correlated assets and signals into selecting a set of uncorrelated managed portfolios through the lens of Canonical Correlation Analysis of Hotelling (1936). The new investment environment of uncorrelated managed portfolios offers unique economic insights into the joint correlation structure of our optimal portfolio policy. We also operationalize our theoretical framework to bridge the gap between theory and practice, showcasing the improved performance of our proposed method over natural competing benchmarks.

The investment model of commitment: examining asexual and aromantic populations using confirmatory and exploratory factor analysis

ABSTRACT Past research on the Investment Model of Commitment suggests that satisfaction, quality of alternatives, and investment consistently predict commitment levels in romantic relationships. Previous research examining the Investment Model has focused on allosexual and alloromantic populations – i.e. individuals who experience sexual and romantic attraction, respectively. We extended this research to asexual and aromantic individuals. Asexual and aromantic participants in relationships completed the four Investment Model subscales (i.e. satisfaction, investments, quality of alternatives, commitment). A confirmatory factor analysis (CFA) showed that the model fit to the original Investment Model factors was poor. An exploratory factor analysis (EFA) revealed that the investments and quality of alternatives items mostly loaded on the original factors; however, satisfaction items and commitment items mostly loaded on the same factor. These results suggest that asexual and aromantic individuals may not distinguish between relationship satisfaction and commitment, or individuals may have relatively equal amounts of satisfaction and commitment in their relationships. In addition, many asexual and aromantic individuals practice non-monogamous relationships, and have a higher quality of alternatives than those who practice monogamous relationships. Ultimately, the findings could guide practitioners when working with asexual and aromantic individuals as well as future research focusing on these populations.

Replication of the Interpersonal Sunk Cost Effect

Olivola (2018) postulated that the sunk cost fallacy, choosing a less preferred option simply because an original investment was already committed, would be facilitated by interpersonal factors. The prior work had compared sunk cost decisions made individually (intrapersonally) and those made on behalf of someone else (interpersonally) and found the relationship between type of investment and commitment of the sunk cost fallacy to be impacted by both intrapersonal and interpersonal influences. Our study sought to replicate Olivola’s original experimental methods and analyses but advanced his original research question with additional analytic investigation using factorial logistic regression. We found similar results to Olivola, however, we also discovered that committing the sunk cost fallacy was significantly more impacted by the price of the sunk cost rather than the person investing, χ2 (420, N = 423) = 209.41, p < .001, R 2 = .53, OR = 33.11, p < .001. This study expanded prior research findings on how individual investment decisions are influenced by others’ investments by contrasting this outcome with how the amount that is invested or given might be more important than the giver or the situation. This is an important distinction as future research seeks to find what influences people’s decisions for personal investments of money, time, etc.

Administrative data source based research methods for territory defined structure of budget investments

Introduction. The paper examines the territory defined structure of the budget investments in the Russian Federation constituents. Purpose. The paper aims at identifying and quantitatively evaluating the connection between the structure indicators of the budget investments and their frequency (per capita, square kilometer, gross regional product) by the groups of regions. Materials andMethods. The research referred to the administrative data sources with the information by the Russian Federation constituents included in the budget expenditure, its spending, investments in targeted investment programs. The paper applies theoretical and mathematical statistical methods of cluster analysis.Results. The paper structurizes the stages of budget legal arrangements and describes an original budget investment flow diagram at the federal, regional, and local levels. The research compares and analyzes the information capacities of the official statistics data and administrative resources in terms of budget investments by sources, composition, flow stages, administrative territorial levels. The original indicator system helps evaluate the territory defined structureof the budget investments with the cluster analysis methods. Conclusion. The results obtained by the author together with the administrative data and official statistics provide the informational grounds for comprehensive accounting and analysis of budget investment flows. The author’s methodological approach to a multidimensional study of a territory defined budget investment structure could be used by the executive authorities and local self-governments.

A Systematic Literature Review of the Adoption of Building Information Modelling (BIM) on Life Cycle Cost (LCC)

The need for embedding sustainability in construction development contributed to the introduction of Building information Modelling (BIM) to be adopted into the Life Cycle Cost (LCC) process. Through BIM, project information used during design can be shared to estimate the project’s end of life costs. LCC enables to assess the overall cost of an asset (building) through its life cycle via functionalities including the original investment costs, maintenance expenses, operating expenses, and the remaining value of the asset at the end of its life. The objective of this paper is to discuss the merging of BIM into LCC through four prevalent aspects; methodology, design software used, benefits, and challenges. A total of 20 studies were reviewed upon filtering process using PRISMA method. These studies discussed at least one of the aspects mentioned and contributed to the information regarding BIM and LCC. This paper thus aims to expanding studies on BIM adoption on LCC through the collected information sourced from peer-reviewed publications.

Doubling the ADMD in housing schemes to cater for future electrification of heat and transport

The rate at which electrification of transport (and heat) will take place, and what the exact impact on the network will actually be is uncertain, yet has to be catered for in any new network which is being designed. This is particularly the case in new Housing Schemes where there may be both an Electric Vehicle (EV) and a Heat Pump (HP) per house. Traditionally the ADMD estimate used was based on multiple small appliance loads acting in a statistically predictable manner, but with the addition of a 7kW EV, or a 3.5kW HP, both of which operate for several hours, any historical ADMD predictions are now largely irrelevant. Accordingly correct design requires the accurate prediction of electrification development and the optimum network associated - which of course means that if the electrification growth is significantly different then either gross over-investment in the network required has taken place, or possibly even worse, inadequate investment has initially taken place so that the costs of subsequently adding extra network capacity in an existing development are now multiples of the original investment. Applying Real Options theory in a practical manner suggests that that at each stage in the development of a network there is scope to make choices to either expand, contract, delay, abandon or redeploy assets. This suggests that designing the network to be able to exercise such flexibility could provide much more robust solutions in the face of uncertainty. Accordingly, when examined in this manner, it was found that doubling the existing ADMD from 2.5kVA to. 5.5kVA per customer provided the largest increase in ADMD at least cost to cover future unknown expansions in electrification loads. Furthermore, such doubling only adds about 10% to the overall costs of the original network development previously required, as the marginal cost of a slightly larger transformer is low as a percentage of the overall cost, and provision of extra cable outlets to offload such transformers (if even increased further in future) is even less. On the other hand, designing for a lower ADMD would save very little, but mean that the cost, if future expansion were required, would be very high. Development of modified Substation designs to facilitate uprating from 630kVA to 1000kVA allows scope for even further load increases if required, yet their initial deferral avoids stranding by future network development e.g. DSM.

The Sleeping Beauty and the Green Swan: How Should Smart Beta Stand the ESG Challenge?

Smart beta is a disruptive financial innovation that we believe will be disrupted by the ESG transition. How should smart beta managers position their products within the large ESG spectrum and how should they align their investment objectives and adapt their frameworks in order to achieve those ESG outcomes? This article discusses the main emerging directions in the industry to overcome those challenges. We report empirical evidence from recent return patterns of top ESG-rated stocks that investors’ preferences have shifted toward ESG, which might signal that some sustainability risk aspects have started to be priced in. This finding provides the rationale for using ESG-based factors in multifactor strategies in expectation of a future development of related risk premia. We also build on the case of the minimum-volatility strategy to show how smart beta managers can mitigate sustainability risks in their portfolio construction frameworks without affecting their original investment objectives.

ЛЕГІТИМНІ ОЧІКУВАННЯ ІНВЕСТОРІВ У СФЕРІ ВІДНОВЛЮВАНОЇ ЕНЕРГЕТИКИ

The article aims at studying the approaches of international investment tribunals to the definition and protection of the legitimate expectations of investors in the renewable energies sector in case where a host state changes or cancels the previously established investment incentive schemes. The author also provides recommendations for Ukrainian authorities regarding the treatment of investors in order to settle existing conflicts and prevent them in future. The research methodology consists of the system-structural method, methods of analysis and synthesis, comparative and prognostic methods. At the beginning of the 21st century, many countries (including those in the European Union) enacted schemes, such as feed-in tariffs (FITs) or other special rates, to encourage long-term investment in the renewables. Confronted with a global financial crisis in 2008–2009, however, many of these countries reduced or eliminated altogether their original investment incentive frameworks. These amendments have prompted a significant number of investment disputes based on claims of breaches of investors' legitimate expectations over the stability of remuneration schemes, alleged to amount to an infringement of the fair and equitable treatment (FET), under the second sentence of Article 10 (1) of the Energy Charter Treaty. Ukraine now faces the same problem in its own relations with investors in renewable energies. Therefore, it is necessary to carefully study the existing (particularly negative) foreign experience in order to mitigate the risks of both losing disputes and inhibiting the development of the "green" energy sector. In order for the state not to bear the burden of compensation payments over the lawsuits by investors, changes in the regulatory regime should be proportionate, reasonable, non-arbitrary and in the public interest, but not radical or unpredictable. At the same time, any lawsuit by an investor poses a risk for the state, since the outcomes of the investment disputes resolution are unpredictable. In this regard, proper communication and negotiations with investors are extremely important to prevent lawsuits, which also carry the danger of creating a negative information background for green energy.

THE EFFECT OF REGIONAL ORIGINAL INCOME AND INVESTMENT ON ECONOMIC GROWTH IN LUWU EAST REGENCY, SOUTH SULAWESI PROVINCE

This study aims to determine the effect of regional original income (PAD) and investment on economic growth in East Luwu Regency, South Sulawesi Province. The type of research used in this research is quantitative research. The data processed is secondary data from Regional Original Income, Investment and Economic Growth in East Luwu Regency, South Sulawesi Province in 2011-2020. The results of the study show that simultaneously Regional Original Income and Investment have a significant effect on Economic Growth in East Luwu Regency, South Sulawesi Province, this is evidenced by the significance value is smaller than the probability (0.010 0.05). Partially Local Original Income (PAD) has a significant effect on economic growth in East Luwu Regency, South Sulawesi Province, as evidenced by the significance value is smaller than the significance probability value (0.027 0.05) and partially Investment has a significant effect on economic growth in East Luwu Regency, Province South Sulawesi, as evidenced by the significance value is smaller than the significance probability value (0.030 0.05).

Discovering the optimal terroir for pinot noir in China. The case of Tianshui

The experience of the pioneering vineyard venture of M. Boutari & Co Ltd in Gansu Province is presented as supporting evidence to our thesis that Tianshui could be considered as an optimal place to grow Pinot Noir in China. The original investment was based on the idea that Tianshui has an untypically temperate macroclimate extremely rarely encountered in China that could be conducive to high-quality winemaking. Comparative research on the weather conditions of Chinese wine regions was conducted; furthermore, the actual vineyard microclimate was studied based on daily meteorological data. Additional “terroir” parameters (the loess soil, disease, weed & pest control, human & social considerations), as well as grapevine sourcing and varietal adaptation, were assessed since the project onset in 2008. Wine was made and evaluated during three pilot vintages from 2015-2017 with the first vintage release made in 2018. The results themselves, as well as the market acceptance of the wine produced, suggest that our original hypothesis was correct. This work intends to draw more attention to further develop the status of Tianshui as a promising new appellation for Pinot Noir in the wine world.

Systematic and Unsystematic Risk in Real Estate Development: A Theoretical Based Analysis

The real estate development industry includes a wide range of organizations and individuals and, it is inherently risky, with high barriers to entry reflecting the cyclic and capital-intensive nature of the sector, and the typically slow payback period. In certain cases, risk includes the prospect of losing the original investment. The risk is classified into different categories among them, systematic risks and unsystematic risks is one important category for an investor. Moreover, systematic risk is the type of risk caused by external factors that affect all investments and, systematic risk is the probability of a loss associated with the entire market or the segment and cannot be controlled whereas unsystematic risk is associated with a specific industry as well as it is controllable. In Sri Lankan context, though there are few researches on identifying the risk factors, but not explained what is systematic and what is unsystematic. Therefore, this research focus to categorize the already identified risk factors in to two areas as systematic and unsystematic. The data collection is based on the past literature and 25 published articles in indexed Journals, conference papers and reports relating real estate development risk factors up to 2020 were identified. Accordingly altogether 35 risk factors were identified and , ten risk factors which were recognized as most significant to the commercial real estate developments were selected for the purpose of the analysis. Results emphasized that climate changes, natural disaster, pandemic risk, council approval process and changes of tax policies as systematic risk factors. On the other hand, the community acceptability, duration, facility management, brand visibility as well as workforce availability as unsystematic risk factors. Hence having identified the risk factors on this basis will help to measure the beta coefficient of the systematic risk in commercial real estate developments to take better investment decisions while increasing the satisfaction of long-term investment goals as well as contribute to improve the risk management strategies in the real estate industry. Measures should be taken to eliminate the unsystematic risk thus the losses from systematic risk may automatically mitigate.
 Keywords: Systematic Risk, Unsystematic Risk, Risk Management, Real Estate Development

Tedarikçi Bağlılığını Etkileyen Faktörlerin Çok Kriterli Karar VermeYöntemleriyle Belirlenmesine Yönelik Bir Araştırma: Giresun İli Örneği(Multi-Criteria Decision Making of Factors Affecting Supplier Loyalty A Research to Determine Its Methods: The Case of Giresun Province)

Purpose – The main purpose of the study, in the province of Giresun in the hazelnut sector of the factors that influence the supplier's commitment to manufacturing enterprises (Trust, Dependency, resource, communication, shared values, social cohesion, the original investment, reputation and psychological Contracts) by the method of multicriteria decision making methods, the entropy is prioritized. Design/methodology/approach – The data used in the study were obtained through face-to-face interviews with business managers and academicians working in my hazelnut industry and a literature review. With the ENTROPI method, which is one of the multi-criteria decision making methods, the factors affecting supplier loyalty were prioritized. Findings – It has been determined that the most important factors for supplier loyalty are “Reputation”, “Original Investments” and “Resource”. It has been determined that the other most important criteria for supplier loyalty factors in hazelnut enterprises are Communication, Common Values and Trust, respectively. On the other hand, the Social Ties factor was the criterion with the least importance. The other least important factors were found to be Addiction, Psychological Contracts and Satisfaction, respectively. Discussions – In today's business world, where global competition is very high, the importance of supplier, supplier evaluation process and supplier selection decision is increasing every day. In particular, one way for companies to be sustainable is undoubtedly through supplier performance. Based on this point, establishing long-term relationships with suppliers and maintaining this relationship is considered and evaluated as a critical factor for companies that want to succeed in today's competitive conditions. A similar study involving provinces covering more comprehensive hazelnut production enterprises in the future can be investigated comparatively as the results of the priority of factors affecting supplier loyalty in the hazelnut sector between provinces. On the other hand, the problem examined in this study can be investigated to include other food sectors and the priority of supplier commitment can be determined through the eyes of different food sectors.

The ‘Netflix Original’ and what it means for the production of European television content

The European audiovisual market has unique contextual characteristics that constrain the sustainability and development of audiovisual content. Among other shifts, the rise of global subscription video-on-demand players like Netflix have been reshaping this market. Although Netflix has been investing in Europe, little is known about their actual investment strategies. This study’s goal is to analyse Netflix original investment in European scripted series and examine their implications for the European market. Based on a mapping of all European Netflix Originals, we identify four investment patterns. The analysis shows a significant uptake of Netflix investment, yet concurrently these reinforce existing discrepancies between large and small states in Europe.

Economic study for blend membrane production

BackgroundIn this work, an economic study for production reverse osmosis (RO) membrane from a blend of polyvinylchloride (PVC) with cellulose acetate (CA) was investigated. The model for predicting RO membrane performance was developed based on laboratory experimental data. The economic study was conducted to investigate the feasibility of producing blend RO polyvinylchloride/cellulose acetate (PVC/CA) membrane using a large-scale batch casting machine was developed and fabricated in workshop in the National Research Centre, Egypt.ResultsThe cost of the prepared blend membrane using batch casting machine technique reached to 36 $/m2 for flat sheet polymeric membrane which was cheaper than the cost of sheets of commercial RO membranes. The original capital investment will be recovered in 7.5 years with estimation of machine lifetime 25 years.ConclusionsThe economic study revealed that the establishing small factories to produce blend membranes using the fabricated machine is a promising and will create a reasonable profit.

Linear Programming Model for Investment Problem in Maximizing the Total Return

In this paper, we concentrate on the investment problem of fixed deposit (FD). Our problem is to allocate the amount invested to a suitable tenure and obtain the optimal investment. There are two types of maturity that need to be considered which are short-term and long-term. Our objective is to maximize the total return of the total amount invested with a different percentage of annual return. A linear programming (LP) model is proposed to solve this investment problem using scheduling methodology. We conduct a computational experiment of a real case study for one company located in Kuala Lumpur with RM 20.6 million of investment to see the performance of the model by using the Excel Solver Parameter package. The results show that a significant improvement obtains by our model compared to the original investment practice by the company.