Passive Income Research Articles

The five dimensions of financial independence retire early

The purpose of the present study is to map out and extend knowledge on the conceptual territory of Financial Independence, Retire Early initiative (FIRE). This topic has produced increasing interest in the public, but it constitutes a relatively new research area for academics. In this study, we analyse the four pillars to achieve financial independence to be able to retire early: budgeting and expense control, saving and investing to earn passive income; creating additional income sources, and improving financial literacy. We also analyse the five main dimensions: FIRE as a self-improvement philosophy, as a self-help initiative, as part of the simple/ecological lifestyle, as a result of financialisation, and as a tool for financial literacy and well-being. The five dimensions we distinguish allow to approach FIRE initiative from different perspectives to have a more complete understanding, but at the same time, these dimensions unveil new approaches to research and understand the impact of FIRE in society.

Automated passive income from stock market using machine learning and big data analytics with security aspects

Automated passive income from stock market using machine learning and big data analytics with security aspects

Rich Dad, Poor Dad's Financial Freedom Road Map

With the rapid development of the global economy, trade between nations is becoming more and more closer in the context of economic globalization. People's pursuit of a happy life has also reached a new level, with financial freedom being a goal that an increasing number of people are pursuing on their path to happiness. The objective of this research is to examine in detail the ideas of financial freedom presented in the book “Rich Dad Poor Dad” and to investigate how these ideas may be more effectively applied to individual financial planning in order to attain financial independence, taking into account the current socioeconomic climate. This study employs a range of research methodologies, such as the literature research method, case study method, and qualitative analysis method. It begins by introducing the idea and significance of financial freedom, then analyzes the book's central financial concepts, and finally offers recommendations and strategies for achieving financial freedom in the context of the contemporary socioeconomic environment. The paper concludes by summarizing the findings and anticipating the direction of additional research on financial independence. Changing one's financial concepts, investing in financial education, and generating passive income are the keys to achieving financial freedom, according to this study, which was conducted after extensive research and analysis of the book Rich Dad, Poor Dad. People can also become more financially independent by having a deeper understanding of these concepts.

Evaluative Exploration of Data Monetisation Platform Capabilities

The article explores the capabilities of various data monetization platforms, such as Gener8, Datacoup, Datawallet, and Swash, highlighting their innovative approaches, user benefits, ethical considerations, and privacy implications. Through comparative analysis, the study examines how these platforms transform personal data into economic value, offering users different methods for monetizing online behaviour, social media interactions, and web activity. Gener8, for instance, rewards users for ad viewing and enhances online shopping experiences, while Datacoup allows for direct data sales, emphasizing user consent and transparency. Swash offers a passive income model through a browser extension, prioritizing user privacy and employing blockchain technology for secure transactions. The article delves into the ethical and privacy concerns arising from data commodification, advocating for robust regulatory frameworks and transparency in data transactions. It concludes that while these platforms offer new opportunities for personal data monetization, they also necessitate careful consideration of privacy implications, underscoring the need for ongoing dialogue around the value of personal data and individuals' rights in the digital marketplace.

Profit shifting to tax havens: Withholding tax impact on passive flows from Poland

This paper aims to identify determinants and channels of tax avoidance through passive flows to tax havens using harmful tax competition, considering the effect of changes in withholding tax regulations. For the empirical analysis, we exploit the data of 110 ​907 nonresidents from 134 countries that gain passive flows paid by Polish taxpayers. We utilise data from IFT-2R returns on withholding tax (WHT) for 2012–2019. We use a two-stage Arellano-Bond estimator of the Generalised Method of Moments (GMM) with instrumental variables for dynamic panel data and the difference-in-differences method. We show that the amendment to the withholding tax legislation, preceded by a no-avoidance clause in 2017, reduced passive flows overall and separately from the manufacturing and service sectors, primarily profit-shifting through interest, royalties and intangible services payments. Moreover, our results confirm that the tax system tightening against aggressive tax competition has reduced passive income transfers from service companies, not manufacturing companies. Instead, the latter make higher transfers to tax havens included in both Polish and the E.U. list of countries applying harmful tax competition.

A sentiment analysis approach for understanding users’ perception of metaverse marketplace

This research explores the user perceptions of the Metaverse Marketplace, analyzing a substantial dataset of over 860,000 Twitter posts through sentiment analysis and topic modeling techniques. The study aims to uncover the driving factors behind user engagement and sentiment in this novel digital trading space. Key findings highlight a predominantly positive user sentiment, with significant enthusiasm for the marketplace's revenue generation and entertainment potential, particularly within the gaming sector. Users express appreciation for the innovative opportunities the Metaverse Marketplace offers for artists, designers, and traders in handling and trading digital assets. This positive outlook is tempered by notable concerns regarding security and privacy within the Metaverse, pointing to a critical area for development and assurance. The study also reveals a substantial neutral sentiment, reflecting users’ cautious but interested stance, particularly regarding the marketplace's role in investment and passive income opportunities. This balanced view underscores the evolving nature of user perceptions in this emerging field. Theoretically, the research enriches the discourse on technology adoption, particularly in virtual environments, by highlighting perceived benefits and enjoyment as significant adoption drivers. These insights are invaluable for stakeholders in the Metaverse Marketplace, guiding the development of more secure, engaging, and user-friendly platforms. While providing a pioneering perspective on Metaverse user perceptions, the study acknowledges its limitation to Twitter data, suggesting the need for broader research methodologies for a more holistic understanding.

Edukasi Ragam Investasi Digital untuk Meningkatkan Peluang Passive Income UMKM Kota Malang

Purpose – This activity aims to provide understanding to Micro, Small and Medium Enterprises (MSMEs) in managing their income and capital flows Design/methodology/approach – This service method is carried out by involving a combination of socialization and education programs that emphasize the importance of investing, providing practical guidance, and supervising digital investments made by MSME participants. Findings – After the service activities are carried out, it can increase knowledge and interest in digital investment among MSME players in the city of Malang so that MSME enthusiasm for investment as a passive income stream increases, while protecting them from fraud in investment Originality/value – Activities focus on the goal of broadening the perspective of MSME players regarding digital investment

Real estate investment funds: a proposal for dividend distribution in Brazil

This article discusses the current challenges faced by Real Estate Investment Funds (REITs) in Brazil, particularly regarding the mandatory dividend distribution based on the "cash" result, which can pose financial risks for managers, especially when future obligations exist. While this practice benefits passive income for investors, it may jeopardize the financial health of the funds. The Brazilian Securities and Exchange Commission (CVM) is keen on revising the current model but will have to overcome resistance from parts of the market. This article suggests a technological solution inspired by models used in developed countries such as the United States, the United Kingdom, and Spain, where dividends are distributed according to accounting profits with the option for dividend reinvestment. Implementing this model in Brazil would necessitate changes in market regulation and investors adapting to the investment platforms' modus operandi—proper accounting of distributions. This model would enhance transparency in resource management and financial stability for REITs. The article emphasizes the role of technological innovation in evolving Brazil's REIT market.

An Analytical Study on Investment Awareness and Pattern of Different Class of Investors

In Today’s era, Individuals are earning a lot with the help of Investment or Passive income rather than active income. People start searching new ways of income generation because of increased expenses and inflation. Investment helps in achieving income, additional growth and creates value. The return and risk are totally dependent on chosen avenue of Investment. This research measures and analyze the awareness of respondents regarding different investment avenues in relation with the occupation of the respondents. For the fulfilment of the objectives of the study, data were collected from 100 respondents of Haryana, who have diverse demographic and socio-economic profile. The findings of the study revealed that there is no significant difference between awareness of respondents regarding different investment options and the occupation of the respondents except Recurring deposit, KVP, Derivatives, FOREX Trading and PPF. The results also found that investors of same income level donot have same knowledge of the investment but the investors lie in same age group generally have same knowledge about investment. The investors of same occupation donot have same knowledge of the investment but investors who comes under same category of annual income usually invest same percentage of their income. This study further concluded that different investors have diverse knowledge and time horizon of investment according to their income level, age, gender and occupation.

Factors Influencing Investment Decisions among College Students: A Comparative Analysis Between India & Nigeria

Investment is done for the purpose to gain profitable returns. Investing in a well-diversified portfolio offers a multitude of benefits, including capital appreciation to grow wealth over time. As a student, managing finance can be challenging, but exploring opportunities for passive income can make a significant difference in financial stability and independence. This study endeavors to comparatively analyze the factors influencing investment decisions among college students in India and Nigeria. Demographics play a pivotal role in shaping investment choices, and understanding the differences in the attitude of these countries is vital for effective financial education initiatives. The study reveals that there is a positive relationship between different factors that students consider when making these decisions. Factors such as financial security, return on investment (ROI), and risk minimization are found to have a significant impact on their choices.

“GETTING PAID TO TAKE CARE FOR THE ONES YOU LOVE”: SOCIAL MEDIA INFLUENCING AS A MEANS FOR PAID SOCIAL REPRODUCTION LABOR

Numerous studies have shown digital platforms commodify social reproduction labor. How social media platforms and the influencers’ activities intersect with the field of social reproduction has received scant academic attention. This study explores platform capitalism's expansion to the domestic sphere in the semi-peripheral socio-economic context. Fifty semi-structured interviews with influencers, their business partners, and other stakeholders in Slovenia were conducted. Results show that social media influencing intersects with the social reproduction sphere in two different ways, depending on whether the household is time- or money-poor. Time-poor households employ influencing to find an optimal temporal equilibrium between influencer activities and household responsibilities. Money-poor households employ influencing as a side hustle besides regular employment to have one household expense less. These two groups converge as they all create content "on the go" while completing social reproduction tasks. Influencing is peering into the cracks between work and leisure, creating a novel dimension of time: monetized leisure. Under the traditional 8-8-8 rule (work, leisure, sleep), only 8 hours were paid. With influencing activities on social media, leisure gets monetized, resulting in more hours of work and passive income. Our study shows that influencing activities on social media in Slovenia are less about getting paid to do what you love, as demonstrated by Duffy (2017) and more about getting paid to care for those you love. The study contributes to the varieties of platform capitalism and to the de-westernization of platform and creator studies.

Stock Price Movement Classification Using Ensembled Model of Long Short-Term Memory (LSTM) and Random Forest (RF)

Stock investing is known worldwide as a passive income available for everyone. To increase the profit possibly gained, many researchers and investors brainstorm to gain a strategy with the most profit. Machine learning and deep learning are two of these approaches to predicting the stock's movement and deciding the strategy to gain as much as possible. To reach this goal, the researcher experiments with Random Forest (RF) and Long Short-Term Memory (LSTM) by trying them individually and merging them into an ensembled model. The researcher used RF to classify the results from LSTM models obtained throughout the Hyperparameter Optimization (HPO) process. This idea is implemented to lessen the time needed to train and optimize each LSTM model inside the ensembled model. Another anticipation done in this research to overcome the time needed to train the model is classifying the return for longer periods. The dataset used in this model is 45 stocks listed in LQ45 as of August 2021 This research results in showing that LSTM gives better results than RF model especially when using Bayesian Optimization as the HPO method, and that the ensembled model can return better precision in predicting stocks in comparison to the LSTM model itself. Future improvement can focus on the model structure, additional model types as the ensemble model estimator, improvement on the model efficiency, and datasets research to be used in predicting the stock movement prediction

Automated Passive Income from Stock Market Using Machine Learning and Big Data Analytics with Security Aspects

With the evolution of Machine Learning, the Internet of Things (IoT), and Big Data Technologies, digital data has increased exponentially. To handle and process such a large bunch of data, high-performance computers are used across various fields. One of the fields has been the financial capital market of stocks, bonds, commodities, foreign exchange, and cryptocurrencies, where supercomputers essentially trade securities with high computational ability and intelligent algorithms. Large financial institutions with significant capital spend a lot of money on programmers and data analysts to develop the best accuracy trading algorithms to drive the overall market. A novice trader or investor with less to no experience in financial markets feels it difficult to search for good trades or stocks to invest their hard-earned money on a short to long-term time horizon. They rely on expert advice for stock recommendations and sometimes end up making significant losses. This paper focuses on developing a universal trend trading indicator that can analyze and predict the overall future trend of any stock, bond, commodity, forex, or cryptocurrency with the highest possible profitability. The historically traded extensive dataset of stock prices and investment reports of large financial institutions worldwide are gathered. Various machine learning and decision-making models are employed to perform technical and fundamental analysis across multiple securities. The output of the trend trading indicator is displayed on charting platforms, which can provide entry-exit levels at which even novice investors can decide where to invest their money. Multi timeframe analysis is deployed to predict short-term, mediumterm, and long-term overall trends, thus increasing the output accuracy. The indicator is helpful for all kinds of retail traders and investors worldwide who struggle to earn profits from financial markets. Our proposed system was able to achieve a profitability of 86.28% annual returns. The entire system, along with the trading orders, is automated so that anyone can earn extra passive income every month from the stock market.

How do responsible universities perceive their social engagement? In search of signs of Creating Shared Value by the University

ObjectivesUniversity social responsibility still lacks legitimisation and is perceived as a burden that hinders academics from doing research and teaching. Creating Shared Value by the University may serve as a tool to motivate universities to engage in initiatives for society, as this is beneficial for both parties. Yet, some researchers perceive the creation of economic value as inappropriate for academia. Thus, it was interesting to examine how the world's best universities elaborate on this matter.Material and methodsA thematic analysis of textual data published online by universities in the top 30 in THE Impact Rankings 2022 has been conducted to determine if they create shared value and what benefits they create or expect.ResultsSigns of indirect Creating Shared Value by the University were observed in the dataset. Some universities create social and economic benefits from the same initiatives, mainly strategic. The observed benefits are both intangible and tangible, but most are related to increasing brand value: receiving recognition and awards, building reputation, strengthening competitive advantage, boosting brand attractiveness, and employer branding. Universities modestly mention that they gain tangible benefits, such as an expansion of research funds, and earned or passive income, which may point out that such values are not perceived as suitable in an academic context yet.ConclusionsThe results shed new light on the perception of creating economic value in academia, indicating that CSVU could be a legitimate tool to develop the theory and practice of USR. Still, results suggest that any CSVU framework should focus primarily on intangible benefits.

How Does Real Estate Investor Ownership Mediate Accessory Dwelling Unit (ADU) Asking Rents? Evidence from Austin, TX

Scholarly and popular discourse often describe accessory dwelling units (ADUs) as one of the last bastions of housing affordability, framing “mom and pop” landlords as historically renting out ADUs as a means to earn a passive income, offset mortgage costs, or age in place. As real estate investors enter the market for ADUs, this raises the question of whether ADUs will continue to represent relatively affordable housing packages. Despite growing interest in ADUs among real estate investors, research to date has not examined how investor ownership impacts ADU affordability. This paper investigates how real estate investor ownership mediates unit-level asking rents for ADUs advertised online on the “open market” in Austin, Texas. This analysis finds that owner-occupied and investor-owned ADUs are not listed for significantly different amounts at vacancy, all else equal. However, these results might not translate to the “closed” market for ADUs, which continues to represent a critical source of below-market rate housing. Further, the gap between investor and owner-occupied rents could widen over time, as owner-occupiers provide deeper discounts to tenants they wish to retain. After conducting interviews with owner-occupiers and real estate investors that own ADUs, this research identifies that the rent-setting strategies of the two groups both diverge and converge, further shedding light on findings from the empirical analysis.

Pengaruh Perilaku Keuangan Terhadap Minat Investasi Pada Nasabah Bank Syariah Indonesia KCP Johan Pahlawan

Investment interest is an individual's desire to invest to achieve long-term financial goals. The general goal of investing is to generate passive income, capital growth, or both. The purpose of this research is to see whether financial behavior influences investment interest among BSI KCP Johan Pahlawan customers. This research uses quantitative methods with a descriptive type. The population in this study were all customers of Bank Syariah Indonesia Johan Pahlawan Sub-Branch Office. The sample used in this research was 100 customers, taken from this population. The data collection technique in this research was to use a questionnaire which was distributed to the entire research sample. The data analysis technique used is simple linear regression analysis, with the help of SPSS software. The collected questionnaire data will be analyzed using simple linear regression analysis techniques to test the research hypothesis. SPSS software was used to assist statistical calculations in analyzing the data. The results of this research show that financial behavior has a positive and significant influence on the investment interest of the Johan Pahlawan community, this is proven by the acquisition of a sig of 0.00 < 0.05. In other words, Johan Pahlawan's financial behavior in managing their personal finances has an impact on their interest in investing.

Stock Price Movement Classification Using Ensembled Model of Long Short-Term Memory (LSTM) and Random Forest (RF)

Stock investing is known worldwide as a passive income available for everyone. To increase the profit possibly gained, many researchers and investors brainstorm to gain a strategy with the most profit. Machine learning and deep learning are two of these approaches to predicting the stock's movement and deciding the strategy to gain as much as possible. To reach this goal, the researcher experiments with Random Forest (RF) and Long Short-Term Memory (LSTM) by trying them individually and merging them into an ensembled model. The researcher used RF to classify the results from LSTM models obtained throughout the Hyperparameter Optimization (HPO) process. This idea is implemented to lessen the time needed to train and optimize each LSTM model inside the ensembled model. Another anticipation done in this research to overcome the time needed to train the model is classifying the return for longer periods. The dataset used in this model is 45 stocks listed in LQ45 as of August 2021 This research results in showing that LSTM gives better results than RF model especially when using Bayesian Optimization as the HPO method, and that the ensembled model can return better precision in predicting stocks in comparison to the LSTM model itself. Future improvement can focus on the model structure, additional model types as the ensemble model estimator, improvement on the model efficiency, and datasets research to be used in predicting the stock movement prediction

Edukasi Pasar Modal Bagi Siswa SMK PGRI 2 Kertosono

Investment is investing money into an asset to generate profits. Therefore, it is important to start investing early by educating the younger generation about the capital market so that the future is more secure because they have passive income. Capital market education is an effort to provide knowledge about investing in the capital market. The partner in this community service is SMK PGRI 2 Kertosono, Nganjuk Regency. The activity aims to introduce younger students to investing in the capital market. So they can improve their knowledge and investment skills at an early age for future profits. The activities carried out to achieve this goal are socialization methods, active participation of participants, and direct activity assistance by the service team. After the service activity ends, it is hoped that participants will be able to understand the procedures for trading shares in the capital market and how to analyze and know the risks of investing in shares.

Financial Freedom in PAYTREN Multi Level Marketing Practice

Financial freedom is a process to obtain passive income, cancellation, receipt and sale of goods or services, then there is someone who is involved in the Multi Level Marketing business. One company that provides passive financial freedom with a Multi Level Marketing system as PT. Veritra Sentosa Internasional by creating a product called PayTren. PayTren is a mobile transaction application created.The purpose of this study is to find out how the forms and ways of obtaining financial freedom in the practice of Multi Level Marketing PayTren and know the review of the theory of maṣlahah and mafsadah on the forms and ways of obtaining financial freedom Multi Level Marketing PayTren. This research uses descriptive qualitative method. Data sources are taken from primary and secondary data. The acquisition and form of financial freedom achieved leads to greater mafsadah, the main cause is the company making the dominant market opportunity for success it is not clear so it leads to gambling, fraud, usury and tyranny. While the basic services of the PayTren application such as electricity, bpjs, top up the balance, speedy payment and others are not included at all from the main purpose of this contract.

Can financial literacy and asset ownership affect retirement planning? Insights from the Indonesian family life survey

Research aims: In today's world, financial literacy plays a crucial role in planning for retirement. This study, therefore, investigates the connection between financial knowledge, household asset ownership, and retirement planning.Design/Methodology/Approach: The study considered variables, such as education level, age, gender, marital status, and household location, using data from the Indonesian Family Life Survey (IFLS)-5 at the household level. This study used a sample of 18,627 households spread across 13 provinces in Indonesia to represent the relationship between the variables. The Logit estimation model then examined the impact of financial literacy and household asset ownership on retirement planning.Research findings: The results suggest that individuals with higher financial knowledge are better equipped to plan for their retirement needs. Furthermore, significant asset ownership is also positively linked to retirement planning, as it indicates that an individual is better prepared to face the challenges of old age. Theoretical contribution/Originality: This study contributes to the Life Cycle Hypothesis, which states that individuals will try to keep consumption patterns/needs expenditures and ensure that individual consumption trends remain consistent/constant.Practitioner/Policy implication: This research is expected to be useful as additional information for policy actors, practitioners, and academics in the financial sector to continue actively introducing and disseminating the importance of financial knowledge to the public. Thus, people have alternative and passive income in their old age that does not require working.Research limitation/Implication: The descriptive results found a reasonably large gap between households where there are households with no savings or assets at all. The discrepancy is expected to affect the outcomes of the research.