Market Fundamentals Research Articles

Decision-Making Amid Economic Uncertainty: Exploring the Key Considerations of Commercial Property Investors

This study explored the key considerations of commercial property investors acting under conditions of economic uncertainty across the following three dimensions: market fundamentals, institutional, and behavioural factors. Over the past few decades, a series of exogenous shocks to the global economy has impacted property performance, investment volumes, and investor perceptions. Acknowledging that uncertainty further complicates investment decision-making, a mixed-methods research approach was adopted to examine the perspectives of 5 experts and 412 property investors. The findings revealed that, while most investors express negative responses to uncertainty and adopt more cautious attitudes, others are more aggressive and attempt to capitalise on emerging opportunities. Market fundamentals are not the only key consideration; access to information and investors’ behaviour all impact how decisions are made under these conditions. In particular, wealthy and more experienced investors make more comprehensive decisions, considering all three dimensions, while aggressive investors may disregard data in favour of intuition. Behavioural biases such as the bandwagon effect and fear of missing out (FOMO) all influence decisions and are sometimes exacerbated by media narratives. Practically, these considerations underscore the complexity of decision-making under conditions of uncertainty and how different investors attempt to navigate market volatility.

"Evolving Horizons: The Journey And Impact Of LIC's Landmark IPO"

The Initial Public Offering (IPO) of the Life Insurance Corporation of India (LIC) in May 2022 marked a pivotal transition for one of India’s largest financial institutions from a state-owned entity to a publicly listed company. This move was part of the government's broader strategy to divest its stakes in public sector enterprises, aiming to enhance operational efficiencies, improve transparency, and maximise shareholder value. Navigating through a series of legislative amendments and complex valuation challenges, the IPO drew substantial attention from both domestic and international investors, reflecting strong confidence in LIC's market fundamentals. This paper provides a detailed review of the IPO process, the subsequent market response, and its impact on LIC’s business operations and governance structure. It discusses the strategic motivations behind the IPO, the execution challenges, and the implications for future economic reforms in India. By analysing LIC’s performance post-IPO, the study highlights the critical role such transformative events play in modernising state-owned enterprises and integrating them with global financial markets, projecting significant implications for similarentities considering public offerings.

The connectedness features of German electricity futures over short and long maturities

This research provides an extensive characterization of the contagion between electricity, energy commodities, financial assets and economic indicators across several maturities. Despite the widespread importance of electricity futures, this has been an under-researched topic. The evolution of connectedness is investigated between 2006 and 2023. With a special focus on electricity forward base and peak contracts, results show that the contagion effects are moderate but evolve through time, with greater impacts observed during the crisis years. We confirm that electricity forward prices are more sensitive to operators’ future expectations on fundamental market conditions than to financial and economic shocks.

Unveiling investor behavior: An investigation into India’s pharmaceutical sector during COVID-19

This study examines the factors influencing retail investors’ decision to invest into the Indian pharmaceutical sector amidst the COVID-19 global health crisis. Confronting the obstacles introduced by the pandemic has helped create a robust foundation for the Indian pharma sector to grow rapidly in the future. As the industry demonstrated signs of considerable future growth, investors favored pharmaceutical investments during COVID-19. Retail investors were mainly the ones who went on a shopping spree during the pandemic. This backdrop provides a unique context to explore the retail investors’ behavior in the Indian pharmaceutical landscape. Leveraging the Theory of Planned Behavior (TPB), this study marks the first attempt to introduce behavior toward market fundamentals as a mediating factor into the TPB framework. To conduct the study, data were collected from 305 retail investors located in Karnataka’s South Canara region, who invested into the Indian pharmaceutical industry during the pandemic, using snowball sampling. The e-survey was employed for data collection. The results reveal that attitudes toward pharmaceutical investments, subjective norms, Perceived Behavioral Control (PBC), and behavior toward market fundamentals have significantly influenced investor decisions. Notably, behavior toward market fundamentals has partially mediated the relationship between attitude toward pharma investment and investment decision and PBC and investment decision. However, the mediation effect of behavior toward market fundamentals was not evident between the subject norm and the investment decision. The study holds pivotal implications for policymakers, government bodies, and industry stakeholders to promote pharmaceutical investments.

THE UN ACTIVITIES ON FACILITATING THE APPLICATION OF INFORMATION AND COMMUNICATIONS TECHNOLOGY FOR THE PURPOSES OF DEVELOPMENT IN THE 1990S

In the early 3rd decade in the 21st century, the information and communications technology (hereinafter referred to as ICT) is regarded as an inalienable factor of the international development. This article presents the analysis of the events related to the outset of the UN involvement in this factor promotion at the turn of the 1980s and further until the late 90s. It marks out the most important measures initiated at the UN main and subsidiary bodies aiming at the ICT study as a development factor and the international community’s political will mobilisation on the ICT’s broadest possible adoption and application. Within the period under consideration, three stages marking the expansion of the UN involvement in the ICT issues, from attracting general attention to their importance in the development towards the drafting of recommendations for the international community on bridging the digital divide, are proposed by us. The article finds out that these recommendations just as other UN activities in the development field worked in favour of the globalisation and evidently reflected the neoliberal paradigm. However, in the meantime they counterbalanced market fundamentalists and provided the grounds for the need of planning the international aid for developing nations and guaranteeing social focus in the national ICT policies.

When Polanyi Met Competition Policy: Market Fundamentalism, Crisis, and Reform in The 21ST Century

When Polanyi Met Competition Policy: Market Fundamentalism, Crisis, and Reform in The 21ST Century

Dung beetle optimization with deep learning approach for solving inverse problems in predicting financial futures

Leveraging deep learning (DL) to inverse problems has proven transformative in predicting financial futures, mainly in stock price prediction. In terms of financial markets, where predicting stock price is a challenging inverse problem, DL methods like long short-term memory networks (LSTM) and recurrent neural networks (RNN) demonstrate notable prowess. These techniques successfully capture complex patterns and dependencies in historical stock price information, learning to discern subtle correlations and fundamental market trends. DL facilitates the extraction of nuanced features by leveraging large datasets and sophisticated techniques, enabling accurate prediction of future stock prices. This intersection of advanced ML approaches and financial predicting signifies a paradigm shift in leveraging technology to navigate the complexity of the financial market and improves decision-making for traders and investors. This manuscript introduces a Dung Beetle Optimization with a Deep Learning Approach for Solving Inverse Problems in Predicting Financial Futures (DBODL-SIPPFF) technique. The DBODL-SIPPFF technique resolves the inverse problem and predicts the stock prices adequately. In addition, the DBODL-SIPPFF technique exploits data consistency (DC) optimizer to solve inverse problems. Primarily, linear scaling normalization (LSN) is applied for data normalization. The honey badger algorithm (HBA) is utilized for the feature selection. Moreover, convolutional long short-term memory (ConvLSTM) is used for stock price prediction. Lastly, the DBO technique is utilized for the optimum hyperparameter selection of the ConvLSTM model. The empirical assessment of the DBODL-SIPPFF technique takes place under diverse stock datasets. The obtained values stated that the DBODL-SIPPFF technique performs optimally over compared methods.

CRITICAL REVIEW ON INSTITUTIONAL REAL ESTATE INVESTMENT DECISION-MAKING MODELS

This critical review delves into the underexplored realm of institutional real estate investment decision-making, a domain that holds paramount significance in the financial landscape. Despite the extensive scrutiny of individual real estate investors' decision-making processes, there exists a noticeable lack of research on the pivotal role played by institutional investors. As the primary stakeholders armed with substantial financial resources, institutional investors, encompassing entities such as investment funds, insurance companies, and pension funds, wield unparalleled influence in the market. This paper aims to unravel the complex decision-making models employed by institutional investors, focusing on the period from 2000 to 2024. Employing the PRISMA model, the review meticulously incorporates 21 pertinent articles, and a comprehensive thematic analysis, facilitated by ATLAS.ti version 23.2.1, reveals three prominent decision-making models – the Normative Model, the Descriptive Model, and the Prescriptive Model. In dissecting the factors that shape institutional real estate investment, the study identifies four key influencers: political, economic, legal, and real estate market fundamentals. The intricate interplay of these factors forms the crux of decision-making strategies adopted by institutional investors, as they diligently safeguard the interests of their trustees. Moreover, a noteworthy revelation surfaces regarding the geographical bias in existing research, with a scarcity of studies in developing countries, notably in Malaysia. This observation not only underscores the need for more comprehensive exploration in these regions but also presents a compelling avenue for future research endeavors. This critical review not only contributes to the ongoing discourse but also paves the way for a more nuanced understanding of the dynamic landscape of institutional real estate investment decision-making.

EXPRESS: Self-Donations and Charitable Contributions in Online Crowdfunding: an Empirical Analysis

Many charitable projects have started using online crowdfunding platforms to raise donations. The rise of these platforms as fundraising vehicles has been partially driven by easy access to a large pool of potential donors without the significant marketing costs that commonly accompany traditional fundraising. However, such a low cost of entry also results in a significant "crowding" of projects, making it difficult for donors to decide which projects to donate to. Thus, a charitable project encounters a fundamental marketing challenge of standing out from other projects when conventional techniques like advertising and promotion are limited. In this paper, we posit that a project can credibly signal its quality via a strategy of "self-donation," whereby the project steward donates to her own project. Our empirical setting is an online education crowdfunding platform. By examining millions of donations, we find that self-donations improve the donation pace, contributed amount, and funding success. We show that the self-donation strategy works only when a self-donation is visible to potential donors and is especially effective at the early stage of the funding cycle or when project stewards are inexperienced, where the projects face significant uncertainty. We find evidence for self-donation as a quality signal through various observable proxies like impact letters to donors and corporate matching. Overall, our findings are consistent with a signaling mechanism that allows the separation of high-quality projects from lower-quality ones.

Does “Paper Oil” Matter? Energy Markets’ Financialization and Co-Movements with Equity Markets

We revisit, and document new facts regarding, the financialization of U.S. energy markets in 2000–2010. We show that, after controlling for macroeconomic factors and physical energy market fundamentals, the strength of energy markets’ co-movements with the U.S. stock market is positively related to the energy paper market activity of hedge funds that trade both asset classes. This relation weakens when credit risk is elevated. We find, in contrast, no link with the aggregate positions of commodity index traders in energy futures markets. Our findings have implications for the ongoing debate regarding the financialization of commodities.

Forecasting Indian Trade Trends through LSTM- based Predictive Modeling

The efficacy of Long Short-Term Memory (LSTM) neural networks and attention-based models in predicting next-day closing prices of the MSFT 500index is meticulously examined. A comprehensive suite of nine carefully chosen predictors spanning fundamental market data, macroeconomic indicators, and technical metrics is amalgamated, fostering a holistic comprehension of market behavior. Through rigorous analysis, the research evaluates single-layer and multilayer LSTM architectures alongside attention- based LSTM variants, juxtaposed against traditional ARIMA models. Surprisingly, the single-layer LSTM consistently outperforms its multilayer counterpart, demonstrating superior accuracy and model fit. The integration of corporate accounting statistics augments predictive capabilities, enriching the models' efficacy. Notably, attention-based LSTM models, particularly the Attention-LSTM variant, exhibit markedly lower prediction errors and higherreturns in trading strategies compared to other methodologies. However, the heightened complexity of stacked-LSTM structures fails to surpass the predictive acumen of simpler LSTM architectures.This inquiry underscores the paramount importance of leveraging advanced AI techniques and comprehensive datasets in navigating the intricate nuances of modern financialmarkets, offering invaluable insights for both researchers and practitioners engaged in stock priceforecasting endeavors.

ON SOME APPROACHES TO REGULATING DIGITAL ECOSYSTEMS

The dichotomy of development and regulation of digital ecosystems has attracted the attention of many theorists and practitioners over the past 10 years. The emergence and poorly regulated development of electronic platforms and ecosystems contributed to the formation of a new business model that did not fit into the coordinates of the legal institutions of the functioning of the traditional economy. In the process of their expansion, digital platforms have demonstrated a number of advantages over traditional business models, while simultaneously increasing their fundamental disadvantages. The article reveals the causes of the emergence and rapid development of digital ecosystems, the phenomenon of ecosystem's dependence. The pros and cons of ecosystem's functioning, the formation of their monopolistic essence, the violation of fundamental market laws, and the factors of their destructive influence on the modern economy, society, and consumers are analyzed. The main directions of activity of national regulators in the USA, the EU, and Russia are presented.

Mining activities and housing price nexus: evidence from South Africa

Purpose Several studies have examined the impact of market fundamentals on house prices. However, the effect of economic sectors on housing prices is limited despite the existence of two-speed economies in some countries, such as South Africa. Therefore, this study aims to examine the impact of mining activities on house prices. This intends to understand the direction of house price spreads and their duration so policymakers can provide remediation to the housing market disturbance swiftly. Design/methodology/approach This study investigated the effect of mining activities on house prices in South Africa, using quarterly data from 2000Q1 to 2019Q1 and deploying an auto-regressive distributed lag model. Findings In the short run, we found that changes in mining activities, as measured by the contribution of this sector to gross domestic product, impact the housing price of mining towns directly after the first quarter and after the second quarter in the non-mining cities. Second, we found that inflationary pressure is instantaneous and impacts house prices in mining towns only in the short run but not in the long run, while increasing housing supply will help cushion house prices in both submarkets. This study extended the analysis by examining a possible spillover in house prices between mining and non-mining towns. This study found evidence of spillover in housing prices from mining towns to non-mining towns without any reciprocity. In the long run, a mortgage lending rate and housing supply are significant, while all the explanatory variables in the non-mining towns are insignificant. Originality/value These results reveal that enhanced mining activities will increase housing prices in mining towns after the first quarter, which is expected to spill over to non-mining towns in the next quarter. These findings will inform housing policymakers about stabilising the housing market in mining and non-mining towns. To the best of the authors’ knowledge, this study is the first to measure the contribution of mining to house price spillover.

창업의도를 넘어 사업화로 가는길

This study investigates the challenges hindering student entrepreneurs from commercializing their ventures despite having entrepreneurial intentions, and it explores the role of marketing capabilities in overcoming these obstacles. We observed 145 students at University A, which offers a semester-long intensive entrepreneurship course, across three instances to examine their entrepreneurial intentions, marketing competencies, and the journey to business startup post-course. The findings reveal that strong entrepreneurial intentions do not directly lead to business commercialization through business registration. Instead, there is a significant positive correlation between entrepreneurial intentions and marketing capabilities related to understanding markets and customers. Moreover, both general and specialized marketing competencies play a crucial mediating role in bridging entrepreneurial intentions and he actual commercialization of businesses. This research highlights the gap between the intention to start a business and actual startup activities among student entrepreneurs, underscoring the need for educational content and methodologies that bolster marketing skills in university entrepreneurship programs. The study suggests that while it is vital to enhance customer-oriented skills based on fundamental marketing principles, developing specialized abilities to analyze markets and competitors and leveraging these insights in the entrepreneurial process is equally important. The implications of this study point towards the integration of practice-oriented marketing projects and curricula that go beyond basic customer analysis, offering a comprehensive approach to entrepreneurship education.

Bursting the bitcoin bubble: Do market prices reflect fundamental bitcoin value?

This paper develops a theoretical model of the bitcoin market and demonstrates that the bitcoin’s volatile and explosive price path is a consequence of the Bitcoin protocol’s system of supply management. The model implies that the marginal cost of mining the target supply of bitcoins is the fundamental value of the bitcoin since it corresponds to an equilibrium in the Bitcoin protocol and the rent-seeking tournament among miners. The data provide strong empirical evidence of cointegration between the bitcoin’s price and the marginal cost of mining the target supply of bitcoins, demonstrating the existence of their long-run equilibrium relationship. Current bubble detection techniques indicate that there is no evidence of explosive departures in the price of the bitcoin from its model-implied fundamental value. Since the raw price data exhibit explosive behavior, the apparent bubbles in the price of the bitcoin can be attributed to its nonstationary market fundamentals.

A Mediating Effect of News Information on the Driver of Green Investment and Herding Behaviour in China's A-Share Market

In recent years, the surge in interest and investment towards environmentally sustainable initiatives, particularly in emerging economies like China, has garnered significant attention. This paper investigates the intricate dynamics between green investment drivers, herd behaviour, and the mediating role of news information in China's A-share market. Drawing upon a comprehensive dataset spanning the recent years, this study employs advanced statistical techniques, including structural equation modelling, to analyse the relationships between the aforementioned variables. Firstly, it examines the primary drivers behind green investment in China, considering factors such as regulatory policies, corporate social responsibility initiatives, and market demand for sustainable products and services. Subsequently, the paper delves into the phenomenon of herd behaviour within the A-share market, exploring how investor decisions are influenced by the actions of others rather than fundamental market indicators. This aspect is particularly pertinent in the context of green investment, where social proof and conformity may play a significant role in shaping investment decisions. Moreover, the study elucidates the mediating effect of news information in this relationship. News media serves as a critical intermediary, disseminating information about regulatory changes, corporate sustainability initiatives, and market trends, which in turn influence investor sentiment and decision-making processes. By uncovering the mediating role of news information, this research provides valuable insights into the mechanisms driving green investment and herd behaviour in China's A-share market. Understanding these dynamics is crucial for policymakers, market participants, and sustainability advocates alike, as they seek to promote environmentally responsible investment practices and mitigate the adverse effects of herd behaviour on market stability and efficiency. Overall, this paper contributes to the growing body of literature on sustainable finance and behavioural economics by shedding light on the complex interplay between green investment drivers, herd behaviour, and the role of news information in shaping investor decisions in China's rapidly evolving financial landscape.

Time–frequency correlation and risk spillovers between Euramerican mature and Asian emerging crude oil futures markets

PurposeThis paper aims to empirically investigate time–frequency linkages between Euramerican mature and Asian emerging crude oil futures markets in terms of correlation and risk spillovers.Design/methodology/approachWith daily data, the authors first undertake the MODWT method to decompose yield series into four different timescales, and then use the R-Vine Copula-CoVaR to analyze correlation and risk spillovers between Euramerican mature and Asian emerging crude oil futures markets.FindingsThe empirical results are as follows: (a) short-term trading is the primary driver of price volatility in crude oil futures markets. (b) The crude oil futures markets exhibit certain regional aggregation characteristics, with the Indian crude oil futures market playing an important role in connecting Euramerican mature and Asian emerging crude oil futures markets. What’s more, Oman crude oil serves as a bridge to link Asian emerging crude oil futures markets. (c) There are significant tail correlations among different futures markets, making them susceptible to “same fall but different rise” scenarios. The volatility behavior of the Indian and Euramerican markets is highly correlated in extreme incidents. (d) Those markets exhibit asymmetric bidirectional risk spillovers. Specifically, the Euramerican mature crude oil futures markets demonstrate significant risk spillovers in the extreme short term, with a relatively larger spillover effect observed on the Indian crude oil futures market. Compared with India and Japan in Asian emerging crude oil futures markets, China's crude oil futures market places more emphasis on changes in market fundamentals and prefers to hold long-term positions rather than short-term technical factors.Originality/valueThe MODWT model is utilized to capture the multiscale coordinated motion characteristics of the data in the time–frequency perspective. What’s more, compared to traditional methods, the R-Vine Copula model exhibits greater flexibility and higher measurement accuracy, enabling it to more accurately capture correlation structures among multiple markets. The proposed methodology can provide evidence for whether crude oil futures markets exhibit integration characteristics and can deepen our understanding of connections among crude oil futures prices.

Financial Position and its Global Impact on Performance of First Bank of Nigeria

First bank is Nigeria’s oldest bank established since 1894 with global business network ranking within the top five hundred global banking brands. The bank’s core business is providing financial services to individuals, corporate customers and public institutions. The business segment includes the Group’s domestic, international and representative offices offering commercial banking services in ten countries including the UK, Gambia, Senegal, Sierra Leone, China, etc. First Bank has taken the lead in stimulating the Nigerian economy with the roll out of an array of products such as First Advance, USSD banking service, First gem, and Agent banking; to empower customers and boost their business initiatives. With over eighteen million customers, the bank specializes in retail banking and has the largest client base in West Africa. First Bank has played a critical role in financing and supporting the economic growth of Nigeria through Agricultural expansion support, providing multi sectoral business solutions, enterprise elevation of small and medium scale enterprises geared towards fostering sustainable socio-economic value in Nigeria This report aims to determine the bank's global impact and profitability using cash flow analysis and results reveal that the bank is currently thriving on strong market fundamentals and will make giant strides in future.

Pushing through the pandemic portal with care ethics: Possibilities for change

AbstractThis paper begins with specific articulations of ‘care’ by three prominent care theorists - Eva Kittay (1999), Joan Tronto (2013), and Maria Puig de la Bellacasa (2017) - to analyze aspects of the Covid-19 reality in the US and in India. The central concern is to explore whether a care analysis of the pandemic can initiate radically different imaginings of ‘living with’ in a post-Covid world. After examining some roadblocks to adopting the deeply relational nature of life that Covid-19 foregrounded, I explore whether our response to the crises contains an implicit self-refutation of entrenched neoliberal frameworks based on atomized selfhood, individualized responsibility, and the values of market fundamentalism.

Microfoundations of dominance of fundamentalism in economic policy: Is there an antidote?

The article examines the possible reasons for the dominance of fundamentalism( in the form of Pigouvianism or market fundamentalism) over functionalism (Coasianism) in the practice of decision-making in economic policy. Continuing the study of the relationship between Coasianism, Pigouvianism and market fundamentalism, presented in previous works, the article focuses on finding the basis for the dominance of fundamentalism at the level of individual decisions and actions — in particular, in the field of cognitive bias and behavioral effects. Decision-making using an automatic cognitive system, subject to cognitive bias, as opposed to a reflective system, can lead to the choice of a fundamentalist solution to a problem where it is not the most efficient, and also reduces the efficiency of functionalism, since it prevents the correct identification of the problem itself, of the structural alternatives for its solution, as well as identifying and comparing the effects associatedwith each of the alternatives. The microfoundations of insufficient supply and demand of the Coasian approach are explored. Based on the identified problems of supply and demand for Coasianism, as one of the possible ways to promote it, it is proposed to consider the primary socialization of the individual in the learning process, the formation of substantive critical thinking. It is emphasized that adjustments to the socialization process are a matter of long-term strategy