Search Results (60)

Financial literacy plays a crucial role in shaping individual investment decisions by influencing susceptibility to behavioural biases such as heuristics, framing effects, cognitive illusions, and herding mentality. While most existing studies have examined financial literacy as a mediating factor, our study is among the first in the literature to analyse the role of behavioural biases as mediating factors in the relationship between financial literacy and investment decisions. Specifically, we investigate key biases, including overconfidence, herding, disposition effect, self-attribution, anchoring, availability, representativeness, and familiarity. Using purposive sampling, we collected 482 responses through a structured Likert scale questionnaire. The dataset underwent rigorous validation and reliability tests to ensure robustness. We employed Python-based statistical analysis and used Pearson’s correlation and mediation analysis to explore the relationships between financial literacy, behavioural biases, and investment decisions. With the help of these methods, we were able to uncover relationships and causal pathways which further our understanding of the role of behavioural biases in determining the impact of financial literacy on investment behaviour. The findings illustrate a notable positive correlation between investment decisions and financial literacy, implying that people with higher financial literacy levels possess greater and more rational financial decision-making capabilities. Other analyses have revealed that biases have a moderating effect on this relationship, showing another path through which financial literacy impacts behaviour at the level of the investor. By placing behavioural biases as mediating constructs, this research broadens the scope of investor psychology and the body of knowledge in behavioural finance, highlighting the need to change the approach to how financial literacy programs aimed at investors are structured and implemented. Full article

The emergence of online brokerage platforms, mobile banking applications, and commission-free trading has altered the investment landscape, renewing commercial and scholarly interest in retail investors. In light of these changes, the present study aims to provide a structural overview of the current state of research on the behaviour of retail investors. Based on a dataset of 386 articles sourced from the Web of Science database, this study employs a composite bibliometric approach of a co-word and co-citation analysis as well as a network analysis to determine preceding scientific discourses, current research themes, and potential avenues for future research. The co-word analysis identifies seven distinct research themes: (1) implications for financial performance; (2) information behaviour; (3) behavioural biases and investor characteristics; (4) investor attention; (5) attitudes towards financial risks; (6) socially responsible investing; and (7) complex financial retail instruments. Incorporating applicable research on individual investors, private investors, and household investors from referenced articles, the co-citation analysis reveals nine preceding scientific discourses. Additionally, the network analyses highlight the concepts and publications currently shaping and likely to influence future research in this field. The present study contributes to the academic discourse by mapping the intellectual landscape of retail investor behaviour, suggesting avenues for future research, and offering valuable insights for navigating this dynamic field. Full article

The study examines the nexus between AI-driven technology, i.e., robo-advisors, and the behavioural intention of investors towards sustainable investment decisions considering government regulations and sustainable investment awareness as the moderating variables. A total of 372 responses were collected from across India through a structured questionnaire along identified variables from the TAM and UTAUT theories under the select constructs, i.e., trust, perceived risk, user-friendliness, perceived usefulness, and emotional arousal. This is with reference to the use of robo-advisors to unearth the extent to which they influence the behavioural intention and finally the sustainable investment decisions taking into account government regulations and sustainable investment awareness as the moderating variables. The results derived by using PLS-SEM reveal that all the five factors are having a significant impact on the behavioural intention for sustainable investment decisions of the investors. Further, both sustainable investment awareness and government regulations have been found to have a moderating impact on shaping the behavioural intention of the investors with respect to most of the variables. The results of the study come up with significant suggestions for the government, financial institutions, and the investors as well as the academicians, and therefore, have policy implications, managerial implications, and theoretical implications. The constructs and moderating variables considered here can further be used for studying the behavioural intentions. The robo-advisory service providers may emphasize developing the algo ensuring trust, usability, and friendly interface in a manner that tends to minimize the perceived risk and emotional arousal leading to the use of robo-advisors pushing the intention of the investors towards sustainable investment. Full article

In this study, we present a novel mathematical framework for pricing financial derivates and modelling asset behaviour by bringing together fractional Brownian motion (fBm), fuzzy logic, and jump processes, all aligned with no-arbitrage principle. In particular, our mathematical developments include fBm defined through Mandelbrot-Van Ness kernels, and advanced mathematical tools such Molchan martingale and BDG inequalities ensuring rigorous theoretical validity. We bring together these different concepts to model uncertainties like sudden market shocks and investor sentiment, providing a fresh perspective in financial mathematics and derivatives pricing. By using fuzzy logic, we incorporate subject factors such as market optimism or pessimism, adjusting volatility dynamically according to the current market environment. Fractal mathematics with the Hurst exponent close to zero reflecting rough market conditions and fuzzy set theory are combined with jumps, representing sudden market changes to capture more realistic asset price movements. We also bridge the gap between complex stochastic equations and solvable differential equations using tools like Feynman-Kac approach and Girsanov transformation. We present simulations illustrating plausible scenarios ranging from pessimistic to optimistic to demonstrate how this model can behave in practice, highlighting potential advantages over classical models like the Merton jump diffusion and Black-Scholes. Overall, our proposed model represents an advancement in mathematical finance by integrating fractional stochastic processes with fuzzy set theory, thus revealing new perspectives on derivative pricing and risk-free valuation in uncertain environments. Full article

There is growing recognition that build-to-rent (BTR), a novel institutional asset class, could improve rental affordability and housing choice in Australia. Despite favourable market conditions and increasing demand, Australia’s BTR sector remains underdeveloped compared to the US and UK. Although the asset class has attracted significant foreign institutional capital, there is little interest from domestic institutional funds. This contrasting investment behaviour between foreign and domestic funds has brought a new dimension to the debates on BTR in Australia. The study uses qualitative research design to examine institutional investor behaviour towards BTR in Australia. Interviews were conducted with experienced BTR investors across three countries—Australia, the US, and the UK—to understand the barriers and investment behaviour towards BTR. The study finds that the key barriers hindering BTR growth in Australia include unfavourable tax treatment, complex planning processes, and insufficient affordable housing incentives. Institutional investors’ decisions are influenced by firm characteristics, operational capabilities, and risk attitudes. Due to risk considerations, Australian superfunds prefer stabilised assets over new developments. Also, sustainability and ESG factors are increasingly important considerations in BTR investment decisions. The research highlights the need for a supportive regulatory environment, efficient property management, and innovative financing solutions to boost BTR investments. To accelerate BTR growth in Australia, policymakers should address tax disparities, streamline planning processes, and enhance affordable housing incentives. Developing BTR-responsive financial instruments could reduce financing costs and attract more institutional capital to the sector. Full article

This study examines the simultaneous relationships among oil prices, oil volatility, and two sub-sectors within alternative energy stocks: renewable energy equipment (REE) and alternative fuels (AF). The results confirm the existence of a bidirectional relationship. While most alternative energy stocks with a long history on the stock exchange exhibit a bidirectional positive correlation with oil prices, they demonstrate a bidirectional negative correlation with oil volatility. In particular, a majority of REEs, as opposed to a minority of AFs, demonstrate a bidirectional positive correlation with oil prices. Conversely, the majority of REEs, contrasted with a minority of AFs, exhibit a bidirectional negative correlation with oil volatility. Notably, newly listed alternative energy stocks show no significant relationship with either oil prices or oil volatility. This suggests that these emerging entities may be influenced by factors beyond traditional energy market dynamics, such as technological innovation, regulatory frameworks, or investor sentiment. Furthermore, the findings highlight that REEs tend to have a more substantial relationship with both oil prices and oil volatility compared to AFs. Recognizing the distinct sensitivities and market behaviours of these sub-sectors can enable more informed decision-making and resource allocation. Full article

This paper presents an innovative approach to financial market modelling by integrating fuzzy discount factors into the decision-making process, thereby reflecting the complexities of human behaviour. Traditional financial models often fail to account for market dynamics’ psychological factors. The proposed method utilizes fuzzy logic to encapsulate the uncertainty and subjective judgment inherent in financial decisions. By representing financial variables as fuzzy numbers, the model better simulates the way humans assess information and make decisions under uncertainty. The incorporation of fuzzy discount factors marks a significant shift from deterministic to a more realistic representation of financial markets, suitable for practical application. This methodology offers a nuanced investment strategy that balances theoretical rigour with real-world applicability, appealing to a broad spectrum of investors. The aim of the following paper is to introduce an alternative to price modelling with the use of fuzzy return rates, which results in some errors in the mathematical model. The solution has the form of introducing fuzzy discount factors (FDFs) that retain the advantages of the fuzzy approach (e.g., encompassing subjectivity and imprecision) while preserving the shape of the fuzzy number modelling a price. Full article

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. Full article

This paper explores the influence of the risk–return relationship and volatility spillover on stock market returns of emerging economies, with a particular focus on the BRICS countries. This research is undertaken in a context where discussions on de-dollarization and the expansion of BRICS membership are gaining momentum, making it a novel and distinct exercise compared to prior studies. Utilizing econometric techniques to investigate daily market returns from 1 April 2008 to 31 March 2023, a period that witnessed major events like the global financial crisis, the COVID-19 pandemic, and the Russia–Ukraine conflict, linear and non-linear models like ARCH, GARCH, GARCH-M, EGARCH, and TGARCH, are employed to assess stock return volatility behaviour, assuming a Gaussian distribution of error terms. The diagnostic test confirms that the distribution is non-normal, stationary, and heteroscedastic. The key findings indicate a lack of the risk–return relationship across all BRICS stock markets, except for South Africa; a more pronounced effect of unpleasant news over pleasant news; a slow mean-reverting process in volatility; the EGARCH model is the best fit model as evidenced by a higher log likelihood and lower Akaike information criterion and Schwardz information criterion parameters; and finally, the presence of significant bidirectional and unidirectional spillover effects in the majority of instances. These findings are valuable for investors, regulators, and policymakers in enhancing returns and mitigating risk through portfolio diversification and informed decision making. Full article

The excess levels of investor participation coupled with irrational behaviour in the South African bond market causes excess volatility, which in turn exposes investors to losses. Consequently, the study aims to examine the effect of market-wide investor sentiment on government bond index returns of varying maturities under changing market conditions. This study constructs a new market-wide investor sentiment index for South Africa and uses the two-state Markov regime-switching model for the sample period 2007/03 to 2024/01. The findings illustrate that the effect investor sentiment has on government bond indices returns of varying maturities is regime-specific and time-varying. For instance, the 1–3-year government index return and the over-12-year government bond index were negatively affected by investor sentiment in a bull market condition and not in a bear market condition. Moreover, the bullish market condition prevailed among the returns of selected government bond indices of varying maturities. The findings suggest that the government bond market is adaptive, as proposed by AMH, and contains alternating efficiencies. The study contributes to the emerging market literature, which is limited. That being said, it uses market-wide investor sentiment as a tool to make pronunciations on asset selection, portfolio formulation, and portfolio diversification, which assists in limiting investor losses. Moreover, the findings of the study contribute to settling the debate surrounding the efficiency of bond markets and the effect between market-wide sentiment and bond index returns in South Africa. That being said, it is nonlinear, which is a better modelled using nonlinear models and alternates with market conditions, making the government bond market adaptive. Full article

In recent years, cryptocurrencies have received substantial attention from investors, researchers and the media due to their volatile behaviour and potential for high returns. This interest has led to an expanding body of research aimed at predicting cryptocurrency prices, which are notably influenced by a wide array of technical, sentimental, and legal factors. This paper reviews scholarly content from 2014 to 2024, employing a systematic approach to explore advanced quantitative methods for cryptocurrency price prediction. It encompasses a broad spectrum of predictive models, from early statistical analyses to sophisticated machine and deep learning algorithms. Notably, this review identifies and discusses the integration of emerging technologies such as Transformers and hybrid deep learning models, which offer new avenues for enhancing prediction accuracy and practical applicability in real-world scenarios. By thoroughly investigating various methodologies and parameters influencing cryptocurrency price predictions, including market sentiment, technical indicators, and blockchain features, this review highlights the field’s complexity and rapid evolution. The analysis identifies significant research gaps and under-explored areas, providing a foundational guideline for future studies. These guidelines aim to connect theoretical advancements with practical, profit-driven applications in cryptocurrency trading, ensuring that future research is both innovative and applicable. Full article

This article explores the significance of Bitcoin halving events within the cryptocurrency ecosystem and their impact on market dynamics. While the existing literature addresses the periods before and after Bitcoin halving, as well as financial bubbles, there is an absence of forecasting regarding Bitcoin price in the time after halving. To address this gap and provide predictions of Bitcoin price development, we conducted a rigorous analysis of past halving events in 2012, 2016, and 2020, focusing on Bitcoin price behaviour before and after each occurrence. What interests us is not only the change in the price level of Bitcoins (top and bottom), but also when this turn occurs. Through synthesizing data and trends from previous events, this article aims to uncover patterns and insights that illuminate the impact of Bitcoin halving on market dynamics and sustainability, movement of the price level, the peaks reached, and price troughs. Our approach involved employing methods such as RSI, MACD, and regression analysis. We looked for the relationship between the price of Bitcoin (top and bottom) and the number of days after the halving. We have uncovered a mathematical model, according to which the next peak will be reached 19 months (in November 2025) and the trough 31 months after Bitcoin halving 2024 (in November 2026). Looking towards the future, this study estimates predictions and expectations for the upcoming Bitcoin halving. These discoveries significantly enhance our understanding of Bitcoin’s trajectory and its implications for the finance cryptocurrency market. By offering novel insights into cryptocurrency market dynamics, this study contributes to advancing knowledge in the field and provides valuable information for cryptocurrency markets, investors, and stakeholders. Full article

Market turbulences and their impact on the financial market, particularly on the stock market, is a financial topic that has received significant research attention recently. This study compared the characteristics of stock return and volatility in selected developed and emerging markets between the 2008 financial crisis and the 2019 worldwide pandemic. In this sense, we seek to answer two concerns. First, do the developed and emerging markets behave similarly during crisis periods? Second, does economic strength always shield markets from poor economic circumstances? For this purpose, the daily return data of E7 (Emerging 7) and G7 (Developed 7) countries for two sample periods—namely, the financial crisis period of 2007–2009 and the global pandemic period of 2019–2021—were chosen. By using univariate GARCH models, namely GARCH, EGARCH, and TGARCH, the study discovered that developing and developed markets reacted differently to these two financial crises. While emerging markets responded similarly to these two crises, developed economies acted differently, being more volatile and sensitive to the worldwide pandemic of 2019 than the financial crisis of 2008. Moreover, a country’s economic prowess does not always shield it from economic turmoil. This study will help investors identify diversification opportunities among the developed and emerging markets during a crisis period. Additionally, this will help portfolio and fund managers understand the behaviour of stock markets during times of market crisis and thus give advice to investors. Full article

Financial technology is quickly developing, making the financial industry more accessible and encouraging individual investor engagement in the investing process. Generation Z, characterised by a high level of digital literacy, curiosity, and receptivity to innovation, tends to very quickly make decisions and rapidly consume. Since 2007, there has been an increase in the number of articles analysing investor behaviour, drawing on insights from financial and psychological theories. The purpose of this exploratory study is to categorise the behaviour of students surveyed by the type of their investments, while at the same time assessing their willingness to choose green investments. The survey used in the analysis not only aims at collecting data but also educates students on the importance of critical self-awareness and the identification of their emotions to make rational, responsible investment decisions and, at the same time, to form a responsible investor who understands that investing is not only a way to earn a return but also can make a positive impact on the world when green investments are chosen. This study shows that studying students tend to be very rational and interested in contributing to greening the world; however, they are still hesitant to put their theoretical skills into practise and are more likely to provide theoretical support for green investments rather than actually invest. Respondents are grouped according to their potential investment behaviour. The proportions of groups are assessed using statistical inference with a precision of 95% that allowed to propose the method of deriving confidence intervals for each group estimation and, thus, making estimates both reliable and available as statistical estimations. Full article

The present study investigates the decision-making process of investors on the Pakistan Stock Exchange with regard to portfolio construction, explicitly focusing on the incorporation of ESG concerns. A quantitative research approach has been implemented for this paper. The hypotheses have been developed and tested through the adapted questionnaires. The data were collected from individual Pakistani investors. The present study employed SmartPLS-SEM to quantitatively assess data received from a sample of 421 out of 500 respondents. Based on the available data, investors participating in the Pakistan Stock Exchange are notably impacted by ESG aspects. The findings of this study hold significance for emerging economy firms, regulators, and investors, in terms of both theoretical and practical ramifications. The study’s findings demonstrate a clear indication of investors’ significant emphasis on ESG matters. This research made a significant contribution to the field of behavioural finance with a focus on ESG-related issues. This work contributes to the literature on ESG elements by using the Theory of Planned Behaviour (TPB) to adapt the ESG components from the United Nations Global Compact (UNGC) and Thomson Reuters Corporate Responsibility Index (TRCRI). Furthermore, it provides valuable insights for stakeholders who are involved in the ever-evolving realm of sustainable finance within developing countries. Full article