Profitable Investment Research Articles

SOCIAL RETURN ON INVESTMENT (SROI) ANALYSIS OF THE ELECTRIC MOTOR CONVERSION TRAINING PROGRAM IN NORTH LAMPUNG

Converting conventional motors into electric vehicles can reduce dependence on fossil fuels. The conversion process involves engine replacement, charging system installation, and vehicle structure modification. The conversion program was carried out involving workshops and vocational high school students. The Social Return on Investment (SROI) method was employed to measure the social and economic impacts of the program, involving impact identification, measurement, monetization, cost comparison, and analysis. The PLN Cares program undertook motor conversion with the aim of improving sustainability and quality. The research problem and objectives focused on measuring the SROI in the electric motor conversion program. The research method employed a qualitative approach with data collection techniques through in-depth interviews, focus group discussions, observations, and literature studies. Data were continuously analyzed during and after collection. SROI calculations involved initial investment capital input and impact value, resulting in an SROI ratio of 5.03. The research results indicated that the PLN Cares program had a significant social impact, with an SROI ratio indicating a profitable investment value. Conclusions and recommendations involved maintaining the working mechanisms, synergy among stakeholders, and using the program as a guide for similar projects in the future.

Effect Of Agricultural Cooperative Societies On Poverty Alleviation Among Rural Households In Ikere Local Government Area

The study examined the effect of agricultural cooperative societies on poverty alleviation among rural households in Ekiti State with a special reference to Ikere Local Government Area. Primary data sources were used in the study through self-administered questionnaires and were analyzed using linear regression model. Result from the study revealed that Agricultural Cooperative Societies have a positive and significant contribution to ending poverty and hunger among rural households in the Ikere Local Government Area. The study concluded that Agricultural cooperative societies have a positive and significant effect on poverty alleviation among rural households in Ekiti State. The study recommends that Agricultural Cooperative Societies should be more generous in credit facilities to their members. Also, while that is important, the Societies are encouraged to educate their fellow members on the judicious use of funds for profitable investment activities which can reduce poverty lines in their communities

IMPLEMENTASI SISTEM SMARK UMKM DAN LITERASI INVESTASI PADA UMKM DI KOTA BANDUNG

The Community Service Program (PKM) aims to provide training and mentoring to Micro, Small, and Medium Enterprises (MSMEs) in Bandung City on marketing audits using the SMARK System and investment literacy. Of the 10 invited MSMEs, 7 actively participated in the program, which was conducted both online via Zoom and offline at STIE Ekuitas. The activities included training sessions on marketing audit strategies, practical guidance on utilizing the SMARK application to enhance business efficiency, and an introduction to secure and profitable investment instruments. Participants gained increased understanding of the importance of systematic marketing evaluation and sound financial management, including investment planning. As a tangible output, participants received a SMARK manual book and presentation materials related to marketing audit and investment literacy. These resources are expected to help participants implement the acquired knowledge in improving their business performance. The results of the program indicate that the SMARK System and marketing audits are crucial for MSMEs, enabling them to systematically evaluate and refine their marketing strategies. This initiative contributed by equipping MSMEs with tools to conduct independent marketing audits and offering guidance on financial literacy to utilize safe investment options effectively. Such steps are critical for fostering professionalism, informed decision-making, and long-term sustainability for MSMEs amid increasingly competitive markets. The program’s impact underscores the need for continued monitoring and further training to ensure that MSMEs can fully benefit from and sustain the knowledge and skills acquired through this initiative.

Public Debt – Economic Growth Nexus: A Systematic Literature Review

The purpose of this study was to present a systematic literature review on the public debt-economic growth nexus. The objective was to provide policymakers and researchers with significant insights on the impact of public debt on economic growth and to provide reliable evidence on the gaps in the literature that require their urgent attention. The study used a systematic review of the literature contained in two databases, namely Semantic Scholar and Google Scholar. The study shows that public debt above the threshold is detrimental to economic growth, while low public debt is conducive to growth, and that the degree of non-linearity in the debt-growth relationship varies considerably depending on the economic status and debt burden of the country. Policymakers in each country should identify the tipping point at which further public debt begins to impede growth. Debt policy should take into account not only fiscal constraints, but also the effectiveness of governance and the possible consequences of eroding public confidence. The study also shows that institutional quality, public investment, production expenditure, foreign direct investment and exports are among the variables that significantly affect the relationship between public debt and economic growth. Policymakers should control the level of public debt and its drivers to support longer-term economic growth. The study also recommends that countries account for public debt and ensure that such debt is acquired only to finance profitable investments that generate future returns, and not for consumption, deficit reduction, wasteful spending, or political purposes.

Developing Models for Analyzing Financial Time Series Data for Investment Strategies

Financial time series data is a cornerstone of investment strategy development, providing critical insights into market trends, asset performance, and risk assessment. This research explores the application of advanced statistical and machine learning models for analyzing financial time series data to optimize investment strategies. The study examines various techniques, including autoregressive integrated moving average (ARIMA), GARCH models for volatility forecasting, and recurrent neural networks (RNNs) for capturing temporal dependencies in financial data. By leveraging these models, the research aims to enhance the prediction of market behavior and identify profitable investment opportunities. It also investigates the integration of feature engineering and real-time data processing to improve model accuracy and adaptability. Challenges such as overfitting, non-stationarity, and the unpredictability of financial markets are addressed, along with the importance of ethical considerations in data-driven decision-making. The findings provide actionable insights into the effective use of financial time series models, offering a robust framework for data-driven investment strategy optimization.

The Impact of Financial Support Mechanisms and Geopolitical Factors on the Profitability of Investments in Solar Power Plants in Slovenia

This article examines the impact of financial support mechanisms and geopolitical factors on the profitability of investments in solar power plants within Slovenia. The European Union’s energy policy prioritizes increases in renewable energy sources, aiming to reduce dependency on unstable and volatile fossil fuel markets. Solar power plants play a vital role in this transition. The energy policy framework also includes mechanisms and support systems to operate such facilities. This article analyzes electricity price trends over the past decade and addresses which support type—guaranteed purchase or operational support—has proven more profitable for investments in solar power plants up to 50 kW in Slovenia, considering economic and geopolitical influences on the electricity market. Although the global energy market has been affected by various significant events in recent years, it was found that the COVID-19 pandemic had minimal impact on the electricity market. In contrast, the onset of the conflict in Ukraine has contributed to rising electricity prices and has influenced the support dynamics essential for the development and sustainability of renewable energy systems. Analyses from the past decade indicate a higher return on investment in solar power plants when operational support mechanisms are chosen over guaranteed purchase support.

ANÁLISE DE RENTABILIDADE DE INVESTIMENTOS EM SISTEMAS DE REFRIGERAÇÃO COM ALTA EFICIÊNCIA ENERGÉTICA

This study analyzes the profitability of investments in high-energy-efficiency refrigeration systems, addressing the economic and environmental impacts of these systems compared to conventional technologies. Energy efficiency is essential for reducing operational costs and promoting sustainability, especially in sectors with high continuous refrigeration demand. The objective is to evaluate the economic feasibility of efficient systems, highlighting variables that influence the return on investment. A descriptive and qualitative literature review was conducted, analyzing studies on energy efficiency, environmental impact, and cost-benefit in commercial and industrial sectors. The findings indicate that, although the initial investment in high-efficiency technologies is high, these systems significantly reduce energy consumption and operational costs over time. It concludes that adopting efficient refrigeration systems is economically viable across various sectors, especially those with high energy demand, and an effective strategy for meeting environmental requirements and reducing emissions.

Reinforcement learning when your life depends on it: A neuro-economic theory of learning.

Synaptic plasticity enables animals to adapt to their environment, but memory formation can require a substantial amount of metabolic energy, potentially impairing survival. Hence, a neuro-economic dilemma arises whether learning is a profitable investment or not, and the brain must therefore judiciously regulate learning. Indeed, in experiments it was observed that during starvation, Drosophila suppress formation of energy-intensive aversive memories. Here we include energy considerations in a reinforcement learning framework. Simulated flies learned to avoid noxious stimuli through synaptic plasticity in either the energy expensive long-term memory (LTM) pathway, or the decaying anesthesia-resistant memory (ARM) pathway. The objective of the flies is to maximize their lifespan, which is calculated with a hazard function. We find that strategies that switch between the LTM and ARM pathways, based on energy reserve and reward prediction error, prolong lifespan. Our study highlights the significance of energy-regulation of memory pathways and dopaminergic control for adaptive learning and survival. It might also benefit engineering applications of reinforcement learning under resources constraints.

Hybrid offshore wind projects. Social desirability vs. incentives to invest

To unlock the full potential of offshore wind requires investment in a more integrated offshore grid infrastructure combining generation and interconnection between countries in so-called hybrid projects. Taking the perspective of a social planner, these projects may result in more efficient allocation of scarce resources. Alas, the distribution of this welfare gain may result in disagreement on what grid design is the most attractive, what markets should be connected and whether and when to invest. To examine these dilemmas, we apply real options theory to investments projects with different grid design and market characteristics. We compare the incentives to invest in a) only the wind farm and b) both the wind farm and the grid infrastructure, assuming the project value of the last alternative can serve as a proxy for social welfare. Solutions are derived using a simulation approach called least squares Monte Carlo method. We find: 1) Non-stationary stochastic prices and/or decreasing costs may make it socially optimal as well as commercially beneficial to postpone even profitable investments. 2) Connecting markets is socially desirable but may reduce the offshore wind investor's project value. 3) Connecting markets with different characteristics is socially desirable but reduce the offshore wind investors' project value.

Model Investasi Cryptocurrency dalam Upaya Pencegahan Tindak Pidana Pencucian Uang

This study aims to analyze cryptocurrency investment models in relation to the prevention of money laundering (Anti-Money Laundering/AML) activities. Cryptocurrency, as a growing form of digital investment, has garnered attention from regulators due to its potential money laundering risks. This paper explores preventive strategies that can be implemented within cryptocurrency investment systems, including the use of blockchain technology, KYC (Know Your Customer) procedures, and international regulations such as the Financial Action Task Force (FATF) guidelines. Through a qualitative method based on literature review and policy analysis, the study identifies investment models that can minimize money laundering risks while maintaining profitability for investors. These findings provide insights into the challenges and solutions in developing a safer cryptocurrency investment system that complies with AML regulations.

Raspberry Production Opportunity to Develop an Agricultural Business in the Context of the Circular Economy: Case Study in South-West Romania

This paper presents a study on the establishment and the capitalization of a remontant red raspberry crop, the Polka variety, on a privately agricultural land area of 0.2 ha in a crop with a support system in V using a geotextile membrane for soil mulching and the method of micro-irrigation by drip. It has been shown that the annual gross profit is advantageous for diversifying the population incomes of rural areas, and the red raspberry is economically profitable regarding cultivation because the recovery of the invested sum is achieved in a maximum of 5 years after the establishment of the culture. The aim of this paper is to explore the growth and commercialization of red raspberry cultivation on privately owned arable land in rural Romania, emphasizing its potential for productivity and sustainability in the context of the circular economy. This initiative not only delivers substantial profits for investors but also fosters rural development and boosts local income levels. The study demonstrates that this cultivation method of red raspberry, aligned with the principles of the circular economy, enhances sustainability by reducing waste, optimizing resource use, and involving local communities in production cycles.

Цифровые финансовые активы как технология фиксации имущественных требований и обмена данными о них

The authors explore the phenomenon of digital financial assets from the perspective of innovative investment technology. The dualism of legislative provisions interpreting the legal nature of these assets is criticized. The conclusion is substantiated that digital financial assets do not belong to objects of civil rights previously unknown to the Russian legal system, but represent property rights that are individualized in circulation by unique information codes. Being negotiable investment assets, they have a commodity-value nature; data on their ownership and transfer of rights to them are transmitted via Internet communications. Through digital financial assets, information technology has been implemented to record the property claims of participants in civil turnover and exchange data about them; they can submit mandatory requirements that are not legally prohibited from alienating them within the framework of assignable structures. Due to this innovative technology, participants in civil turnover receive the legal equivalent of a certain mandatory requirement in digital form, including a requirement fixed in equity securities, a requirement to transfer such securities, as well as corporate rights determined by participation in the capital of a non-public joint-stock company. The use of digital financial assets provides an opportunity for individuals and legal entities to build investment relationships with minimal intermediary participation, conduct financial transactions in a transparent manner, increase investment profitability, and simplify the search for counterparties.

Shareholder Loans: Fact or Fiction

Shareholder loans are often used as an alternative to traditional third-party loans or equity especially for private companies in various jurisdictions, including South Africa, to finance their business activities. These loans provide companies with greater flexibility to meet their financing needs, i.e., there is no need to seek external financing while offering shareholders a potentially profitable investment opportunity. However, the legal nature of shareholder loans could pose complex legal questions and this form of loans may not necessarily be as straightforward as it first appears. This article explores the legal framework and practical considerations surrounding shareholder loans in South Africa in small private companies, with a focus on developments in case law and their implications for companies and shareholders. Amongst other issues, the application of the principle of arbitrium boni viri to the interpretation and enforcement of these agreements will be discussed. The article aims to provide a critical analysis of the legal questions associated with shareholder loans in South Africa.

Optimal dimensioning of renewable energy generation and storage systems

With high energy demand and large available area, agricultural farms offer significant potential for renewable energy investments, like photovoltaic systems and electrical energy storages. However, the profitability of such investments depends strongly on self-consumption, so accurate planning requires computation-intensive simulation and optimization considering local consumption. This study presents a novel methodology for the optimal dimensioning and configuration of photovoltaic systems and electrical energy storages using efficient techniques from continuous non-linear optimization. Combining physical and economic models with measured consumption data, an investment’s net present value over 20 years is maximized. Using gradient-based solver WORHP, the simulation, optimal control, and optimal dimensioning of the local energy system are calculated simultaneously, allowing for efficient computation over an entire year of hourly data to capture both daily and seasonal variations.The approach is demonstrated with simple use cases, including an exemplary day of a dairy farm’s consumption, for which optimal systems with and without storage achieve 77% and 43% of autarky, respectively. Saturation effects of optimal plant size can be observed when sizes are large enough for optimal self-consumption but not expanded further for grid export. With energy storage, this saturation is reached at higher values. Optimizing photovoltaic plants with different orientations to match the specific consumption patterns characteristic of the dairy farm achieves similar autarky as a single plant while reducing investment costs by more than 20%. While thorough validation and comparison against heuristic methods predominantly used in the field is part of ongoing research, the presented use cases demonstrate the flexibility and efficiency of the proposed method and highlight its promise as a planning tool in the agricultural domain and beyond.

Techno-economic analysis of biocrude, biogas, and fertilizer production from microalgae Coelastrella striolata cultivated in agroindustrial wastewater

Coelastrella microalgae have gained attention due to their robustness, high lipid content, effective bioremediation agent, and ability to thrive in diverse environmental conditions. The objective of this study was to evaluate the economic feasibility of an integrated biorefinery of the unique original Coelastrella striolata var. multistriata strain 047 applied in agro-industrial wastewater, flue gases, and excess energy on a 1.2 ha open raceway pond (ORP). This study consists of three scenarios: (1) biocrude only (BO); (2) biocrude and biogas (BB); and (3) biocrude, biogas, and fertilizer (BBF). The findings indicated that the BB and BBF scenarios enhanced the financial feasibility and potential profitability of investment. This is reflected in the economic feasibility indicators for the BB scenario over a project lifetime of 20 years, which include a net present value (NPV) of $4,757,082, an internal rate of return (IRR) of 25.6%, a profitability index (PI) of 2.77, and a payback period of 3.75 years. Similarly, in the BBF scenario, financial viability is demonstrated with an NPV of $4,714,418, an IRR of 25.2%, a PI of 2.73, and a payback period of 3.79 years. Operational expenditures were identified as the most sensitive aspect of this study, particularly in the hydrothermal liquefaction (HTL) process for biocrude production. The utilization of effluent and excess energy from palm oil mill (POM) reduced the operational costs for energy and nutrients by up to 69% compared to the baseline, where palm oil mill effluent (POME) and excess energy were not utilized. Additionally, to achieve optimal results in the BO scenario, increasing the concentration of Coelastrella striolata var. multistriata strain 047 in POME proved to be the most effective approach for increasing biocrude oil production, reducing costs, and increasing economic sustainability.

Dynamic evolution of causal relationships among cryptocurrencies: an analysis via Bayesian networks

AbstractUnderstanding the relationships between cryptocurrencies is important for making informed investment decisions in this financial market. Our study utilises Bayesian networks to examine the causal interrelationships among six major cryptocurrencies: Bitcoin, Binance Coin, Ethereum, Litecoin, Ripple, and Tether. Beyond understanding the connectedness, we also investigate whether these relationships evolve over time. This understanding is crucial for developing profitable investment strategies and forecasting methods. Therefore, we introduce an approach to investigate the dynamic nature of these relationships. Our observations reveal that Tether, a stablecoin, behaves distinctly compared to mining-based cryptocurrencies and stands isolated from the others. Furthermore, our findings indicate that Bitcoin and Ethereum significantly influence the price fluctuations of the other coins, except for Tether. This highlights their key roles in the cryptocurrency ecosystem. Additionally, we conduct diagnostic analyses on constructed Bayesian networks, emphasising that cryptocurrencies generally follow the same market direction as extra evidence for interconnectedness. Moreover, our approach reveals the dynamic and evolving nature of these relationships over time, offering insights into the ever-changing dynamics of the cryptocurrency market.

Feasibility study of floating solar photovoltaic systems using techno-economic assessment and multi-criteria decision-making method: A case study of Bangladesh

Many developing countries with abundant solar resources and rich history of agriculture, face overpopulation and land shortage issues. Floating solar photovoltaics (FSPVs) do not compete with agriculture for land and offer higher energy potential than land-based photovoltaics (LBPVs). For feasibility and site suitability evaluation of FSPVs, this study proposes an integrated approach of techno-economic assessment (TEA) and multi-criteria decision making (MCDM), based on a case study of Bangladesh. The system advisor model (SAM) was used to conduct TEA, evaluating the potential of nine FSPV sites on a regional scale using ten criteria. Combined compromise solution (CoCoSo) was implemented to determine the optimum site. Bergobindopur lake was ranked top, with the highest energy yield and lowest cost of energy of 1564 kWh/kW and $0.055/kWh respectively. Case study of Bergobindopur revealed buy-all-sell-all electricity tariff was more profitable than net billing and net metering. Energy generation was found to be influenced by tilt angle and soiling. Sensitivity analyses demonstrated the superiority of FSPVs over LBPVs for varying electricity prices, degradation and discount rates, project durations, and investor's equities. Longer project durations and lower equities resulted in higher profits for investors. The proposed approach contributes to the expansion of FSPV in land-constrained areas.

The Dynamic Relationship Between Exchange Rate Volatility and Stock Prices in the Egyptian Real Estate Market and the Moderating Effect of Interest Rates

Among different channels of the financial market, the exchange rates and stock markets play a vital role in the domestic and international markets. This study aims to explore the dynamic relationship between the exchange rate (USD/EGP) and the real estate sector listed companies of the Egyptian Stock Exchange (EGX) from 2013 to 2023. Additionally, the study examines the moderating effect of interest rates on the relationship. To achieve this, the study employs several econometric methods such as Augmented Dicky Fuller (ADF) test, Granger Causality test to determine the direction of the relationship, Vector Autoregressive (VAR) model, and more. The results demonstrate that a long-run relationship exists between the variables. Furthermore, there is a significant unidirectional causality that runs from the exchange rate to real estate stock prices; thus, fluctuations in the exchange rate can significantly affect the profitability of investments in real estate stocks. Therefore, investors should closely monitor the movements in the exchange rate level to predict changes in real estate stock prices. When including the interest rate as a moderator, the outcome changes to bidirectional causality, meaning that the exchange rate and real estate stock price movements affect each other at a 1% significance level. Hence, interest rate could be used as an instrument to control demand in both the stock market and foreign exchange market. Finally, it is recommended that policymakers use the monetary policy while considering this bidirectional relationship in the presence of interest rate as a moderating variable.

Harnessing machine learning algorithms to unveil energy efficiency investment archetypes

Increasing transparency about the performance of different projects is crucial to reducing the heterogeneity in the energy efficiency services market, thereby upscaling investments. In this context, machine learning algorithms could assist in identifying and analyzing energy efficiency project archetypes, although this field has so far been explored with a limited view in the literature. This paper aims to address this gap by identifying energy efficiency investment families and the determinant factors of the classification scheme, using machine learning. In this effort, it hinges on a wide range of indicators from implemented projects around Europe and the USA, including investment profitability, initial investment, risk of failure, intervention type, life measure, region of implementation and building type. The analysis employs two clustering approaches, namely Partitioning Around Medoids (PAM) and K-means, determining the number of clusters based on the Silhouette index and total within–cluster sum of squares. The results indicate that energy efficiency investments can be classified into three categories: (i) “junk investments”, characterized by low–profitability (IRR∼10%), moderate risk, and extended horizons; (ii) “safe profitability”, distinguished by high profitability (IRR∼30%) and minimal risk; and (iii) “high stakes”, described by exceptionally high profitability (IRR∼40%), coupled with a substantial risk. Next to profitability and risk of failure, also energy efficiency intervention and building type (sector) emerge among the most influential factors in the classification scheme. Feature importance shows a significant sensitivity to the chosen classification model.

Evaluating ESG Investment Profitability: From the Perspective of Sophistication in Investment Decision-Making

Environmental, Social, and Governance (ESG) investments are widely discussed in the stock market. Further, the debate on ESG investment profitability has garnered significant scholarly attention. This study examines the relationship between ESG investments and equity investment return (EIR) and whether this relationship is affected by investors' sophistication. The results suggest that while ESG investors generally gain relatively lower profits than others, sophisticated investors, characterized by greater financial knowledge, diversified investments, contrarian investment strategies, and not being influenced by familiar biases, can mitigate these lower returns. These findings enhance our understanding of ESG investments and offer valuable insights to guide investors in making sophisticated ESG investment decisions.