Search Results (20)

Digital financial literacy is an emerging concept that refers to the ability to effectively use digital tools, platforms, and services to manage personal finances. While previous studies have explored the behavioral effects of digital financial literacy, less is known about its broader well-being implications for financial consumers. In this study, we aim to examine the association between digital financial literacy and life satisfaction in a developed country context. Digital financial literacy was measured using a multidimensional scale that encompasses financial knowledge, digital literacy, digital financial service awareness, practical know-how of digital financial services, and self-protection against digital financial fraud. Using data of 1615 Korean adults who currently use digital financial services, this study estimated a series of regressions linking life satisfaction to digital financial literacy and covariates. The results showed a significant association between digital financial literacy and life satisfaction, with self-protection against fraud being the most influential subdimension. Notably, financial knowledge was not associated with life satisfaction when other dimensions of digital financial literacy were independently included in the regression models. These findings highlight the importance of digital skills and knowledge in navigating digital financial services. They also emphasize the need for targeted policies, financial education initiatives, and consumer protection measures to address the lack of digital financial literacy among marginalized populations. Full article

This study empirically investigates the relationship between realized higher-order moments and the Fear and Greed Index as a measure of sentiments. We estimate daily realized moments using 5 min return data of the S&P 500 index from 3 January 2011 to 18 September 2020. We find that the Fear and Greed Index significantly impacts realized volatility during periods of extreme fear. Additionally, various sentiment indicators influence realized skewness and realized kurtosis. The VIX index significantly reduces realized skewness across all sentiment levels. Bearish and bullish sentiments have a significant negative relationship with negative realized skewness during periods of extreme fear and extreme greed. However, the Fear and Greed Index and bearish and bullish sentiments have a significant positive relationship with positive realized skewness. During extreme fear, the Fear and Greed Index and bearish and bullish sentiments have a significant negative relationship with realized kurtosis. These results remain consistent when considering the non-linear characteristics of the Fear and Greed Index during periods of extreme fear and extreme greed. These findings highlight the relevance of understanding sentiment in financial risk management and its significant relationship with the asymmetric and extremity characteristics of asset returns. Full article

This study aims to analyze and classify the evolution of crowdfunding in Portugal from 2014 to 2020, addressing the central question, “What is the evolution of literature on crowdfunding and its research focuses in Portugal?”. Additionally, it investigates, through the sub-question, if crowdfunding is perceived as an alternative form of financing. The methodology employs a systematic review, covering four thematic areas: (1) research focus—concepts; (2) research method—quantitative/qualitative identification; (3) geographical area—countries of study; (4) innovation—future research areas. The research begins with Google Scholar, followed by a more specific search of the B-On database, focusing on the Portuguese context. Results highlight the scarcity of research in Portugal, emphasizing the nascency of crowdfunding in the country. The study reveals the importance of investor behavior, influenced by platform security and regulations. Growth in crowdfunding in Portugal is anticipated, attracting multidisciplinary interest but emphasizing the need for more comprehensive studies. Despite limitations in data availability, the study provides valuable insights for entrepreneurs seeking alternative financing in Portugal, demonstrating crowdfunding as an alternative financing method. Integration of crowdfunding with technology, especially blockchain, is suggested as a potentially disruptive system, paving the way for future research and innovations. Full article

This study bridges finance and physics by applying thermodynamic concepts to model the limit order book (LOB) with high-frequency trading data on the Bitcoin spot. We derive the measures of Market Temperature and Market Entropy from the kinetic and potential energies in the LOB to provide a deeper understanding of order activities and market participant behavior. Market Temperature emerges as a robust indicator of market liquidity, correlating with liquidity measures such as Active Quote Volume, bid–ask spread and match volume. Market Entropy, on the other hand, quantifies the degree of disorder or randomness in the LOB, providing insights into the instantaneous volatility of price in the high-frequency trading market. Our empirical findings not only broaden the theoretical framework of econophysics but also enhance comprehensive understanding of the market microstructure and order book dynamics. Full article

This paper offers a comprehensive empirical overview of the impact of overconfidence in the stock market, thus contributing to the existing research literature on this topic. The study employs a bibliometric approach that utilizes the VOSviewer to extract and analyze 277 articles registered between 1992 and January 2023. By providing a detailed analysis of the literature, this research expands our understanding of the impact of overconfidence in the stock market and offers avenues for future studies in this area. The results of this analysis are noteworthy, as they reveal several important findings. These include the exponential growth of scientific production in recent decades, the concentration of research in specific journals indexed in the Journal Citation Reports, the presence of institutional co-author networks, and the thematic and temporal segregation of financial behavior concepts. The most significant finding of this study is the identification of six major clusters: investor behavior during times of crisis; behavioral finance; herding and risk-taking concepts; psychological and cognitive decisions; emotions and decision-making; and the performance of stocks. This temporal evolution of research demonstrates the emergence of various perspectives on the relationship between individual financial behavior and the global market. This study represents a pioneering effort in the field of bibliometric analysis as it is the first to specifically examine the subject of overconfidence in the stock market using this method. Full article

In the field of financial investment, accurate prediction of financial market values can increase investor profits. Investor personality affects specific portfolio solutions, which keeps them symmetrical in the process of investment competition. However, information is often asymmetric in financial markets, and this information bias often results in different future returns for investors. Nowadays, machine learning algorithms are widely used in the field of financial investment. Many advanced machine learning algorithms can effectively predict future market changes and provide a scientific basis for investor decisions. The purpose of this paper is to study the problem of optimal matching of financial investment by using machine learning algorithms combined with finance and to reduce the impact of information asymmetry for investors effectively. Moreover, based on the model results, we study the effects of different investor personalities on factors such as expected investment returns and the number of transactions. Based on the time-series characteristics of price data, through multi-model comparison, we select the ARIMA model combined with particle swarm algorithm to determine the optimal prediction model and introduce the concepts of mean-variance model, Sharpe ratio, and efficient frontier to find the balance point of risk and return. In this study, we use gold and bitcoin price data from 2016–2021 to develop optimal investment strategies and study the impact of investor behavior on trading strategies. Full article

The steady growing of online financial services due to the vanishing of on-site banking offers is changing the socio-economic framework individuals make financial decisions in. Financial literacy as an essential part of basic education is therefore also subject to changes. In order to investigate the individual competence of the respondents with regard to financially determined life situations, a digital questionnaire survey with integrated simulation sequences was conducted. For this purpose, a testing instrument (FILSA—Financial Literacy Study of Adults) has been developed to measure the financial literacy of adults. The validity of the construct including its five content areas was tested and the relationships between the manifest exogenous variables and financial literacy were mapped in a structural equation model. It introduces the participants (N = 212) to various financial problems and offers specific aids for founded decision-making. The study’s evaluation system takes into account the participants’ individual behavior in three case studies as well as the impact of attitude and socio-demographic factors on their decisions and behaviors, such as gender, age, and their degree of internet affinity. FILSA examines how adults make decisions with regard to finances and what benefit or impact online tools and financial advisors have on the decision-making process. Furthermore, it is possible to develop concepts for self-learning that are comprised in online tools for decision-making. Full article

Recent disasters have emphasized the need for further action to protect businesses and society from long-term sustainability threats. We believe that the crisis is hastening nascent ESG trends, and that the increased focus on a company’s environmental and social impact will last long after crises have passed. We refined three fundamental concepts that guide our thinking on investing based on environmental, social, and governance factors as our approach to sustainable investing has evolved. The ESG factor assessments are more of an inherent aspect of a sound investment process than a separate investment discipline. When ESG variables are considered, the focus is on long-term risk adjusted investment returns. Investors should choose the strategy that best matches with their goals and interests. ESG investing is not a simple yes or no answer. The research gap extracted from the previous studies is to determine the relationship among the influencing factors of ESG and its priority with their driving and dependence capabilities. We used an ISM Approach to uncover the interrelationships and influencing behavior among the elements for considering ESG in investment after conducting a thorough literature research and consulting with experts. Here interpretive structural modeling (ISM) was used to explore the links among such extracted factors and its interdependencies. There was also focus on the short-term and long-term factors to achieve our desired objective. Our research will assist businesses in attracting and obtaining finance. The results of this analysis will be helpful for leaders to understand the impact of ESG on the investment aspects of an organization. Full article

In the socio-economic field, it is not surprising that decision-making is based on asymmetric information. Economic agents make decisions to forecast in primary and secondary industries related to the tourism sector. This study aims to provide knowledge in situations of asymmetric information with increasing randomness using time series for tourism accommodation markets. We are trying to solve the question of how consumers exchange their preferences for tourist accommodation between tourist apartments and hotel accommodation in Spain. The emergence of the sharing economy concept has emerged as a competitor to the traditional hotel accommodation in the tourist market. To do this, we will develop a theoretical framework to measure situations of uncertainty and their temporal evolution. Information Theory (IT) is the central axis of the study, particularly the concept of entropy. The Shannon entropy (SE) concept is a static measure of information. This work proposes to model the temporal arrangement of SE to discover the behaviors of the systems. The study in the domain of time and frequency allows us to understand the cycles of uncertainty between systems. To apply the theoretical framework, we will work with data from official Spanish sources for tourist accommodation from January 2008 to December 2019. The results of the empirical analysis show the decision changes of economic agents according to a seasonal pattern. Consumers have new accommodation options, and the answer we get from this work is that consumers have different preferences depending on seasonality. The use of SE allows us to make better predictions compared to SARIMA models, the traditional modelling of seasonal dummy variables, and VAR models. The results of the Matrix U1 Theil verify this hypothesis. The theoretical framework and empirical analysis find an answer to asymmetric information. The implications of this work contribute to the field of social sciences related to the tourism sector, in particular to thermodynamics, statistical mechanics, and IT. The modelling of uncertainty allows for the forecasting and control of accommodation tourist markets in random situations. The applications of this study can be tested in other areas of the economy such as finance, transportation, or investment. Full article

Owing to the globalization of the economy, the concept of entangled markets started to form, and this occurrence has smoothed the entrance of quantum mechanics into behavioral finance. In this manuscript, we introduce quantum risk and perform an analysis on portfolio optimization by controlling the quantum potential. We apply this method to eight major indices and construct a portfolio with a minimum quantum risk. The results show quantum risk has a power law behavior with a time-scale just as a standard deviation with different exponents. Full article

Behavioral finance is an area or sub-discipline of behavioral economics that examines the real financial behavior and decision-making of people, including the knowledge of psychology and sociology. The objective of this paper was to identify and investigate the impact of significant cognitive, psychological and emotional factors affecting the financial decision-making of the shareholders of woodworking and furniture manufacturing and trading enterprises. This could lead to the design of decision-making concepts which take into account not only cognitive but also psychological and emotional factors and their influences on decision-making process, which could positively affect the sustainable development of the aforementioned types of enterprises. The mapping of the addressed issue was carried out by means of an empirical survey in the practice of the Slovak woodworking and furniture manufacturing and trading enterprises in the form of a questionnaire. The results of the survey were evaluated by descriptive, graphical and mathematical-statistical methods. Conclusions and recommendations were formulated based on the identification of key behavioral aspects (knowledge, security, freedom and sadness), the implementation of which could contribute to eliminating negative deviations and errors in the financial decision-making process of shareholders of woodworking and furniture manufacturing and trading enterprises. Full article

The framework of this paper is intertemporal choice, which traditionally has been studied with preference relations and discount functions. However, the interest of econophysics in this topic makes time become a central magnitude. Therefore, the aim of this paper is to introduce the concept of delay function and, by using this tool, to analyze the concept of impatience and the different types of inconsistency. In behavioral finance, consistency is correlated with the concept of symmetry because, in this case, the indifference between two rewards does not change when the same delay is added to their respective availability dates. Moreover, we have shown the way to derive a discount (respectively, delay) function starting from the expression of its corresponding delay (respectively, discount) function by requiring some suitable conditions for this construction. Finally, we have deduced the concept of instantaneous variation rate and Prelec’s measure of inconsistency in terms of the delay function. Full article

The framework of this paper is the concept of derivative from the point of view of abstract algebra and differential calculus. The objective of this paper is to introduce a novel concept of derivative which arises in certain economic problems, specifically in intertemporal choice when trying to characterize moderately and strongly decreasing impatience. To do this, we have employed the usual tools and magnitudes of financial mathematics with an algebraic nomenclature. The main contribution of this paper is twofold. On the one hand, we have proposed a novel framework and a different approach to the concept of relative derivation which satisfies the so-called generalized Leibniz’s rule. On the other hand, in spite of the fact that this peculiar approach can be applied to other disciplines, we have presented the mathematical characterization of the two main types of decreasing impatience in the ambit of behavioral finance, based on a previous characterization involving the proportional increasing of the variable “time”. Finally, this paper points out other patterns of variation which could be applied in economics and other scientific disciplines. Full article

The efficient-market hypothesis (EMH) is one of the most important economic and financial hypotheses that have been tested over the past century. Due to many abnormal phenomena and conflicting evidence, otherwise known as anomalies against EMH, some academics have questioned whether EMH is valid, and pointed out that the financial literature has substantial evidence of anomalies, so that many theories have been developed to explain some anomalies. To address the issue, this paper reviews the theory and literature on market efficiency and market anomalies. We give a brief review on market efficiency and clearly define the concept of market efficiency and the EMH. We discuss some efforts that challenge the EMH. We review different market anomalies and different theories of Behavioral Finance that could be used to explain such market anomalies. This review is useful to academics for developing cutting-edge treatments of financial theory that EMH, anomalies, and Behavioral Finance underlie. The review is also beneficial to investors for making choices of investment products and strategies that suit their risk preferences and behavioral traits predicted from behavioral models. Finally, when EMH, anomalies and Behavioral Finance are used to explain the impacts of investor behavior on stock price movements, it is invaluable to policy makers, when reviewing their policies, to avoid excessive fluctuations in stock markets. Full article

Nonlinear time series analysis gained prominence from the late 1980s on, primarily because of its ability to characterize, analyze, and predict nontrivial features in data sets that stem from a wide range of fields such as finance, music, human physiology, cognitive science, astrophysics, climate, and engineering. More recently, recurrence plots, initially proposed as a visual tool for the analysis of complex systems, have proven to be a powerful framework to quantify and reveal nontrivial dynamical features in time series data. This tutorial review provides a brief introduction to the fundamentals of nonlinear time series analysis, before discussing in greater detail a few (out of the many existing) approaches of recurrence plot-based analysis of time series. In particular, it focusses on recurrence plot-based measures which characterize dynamical features such as determinism, synchronization, and regime changes. The concept of surrogate-based hypothesis testing, which is crucial to drawing any inference from data analyses, is also discussed. Finally, the presented recurrence plot approaches are applied to two climatic indices related to the equatorial and North Pacific regions, and their dynamical behavior and their interrelations are investigated. Full article