Current Investors Research Articles

Cryptocurrency Security Risk: Awareness Among General Public in Malaysia

In the age of digital payments, cryptocurrencies have gained significant attention as an alternative investment option. However, security risks such as phishing, hacking, and fraudulent exchanges present challenges for investors. This study aims to assess the level of awareness among the general public in Malaysia regarding cryptocurrency security risks. A quantitative research method was employed, using a survey questionnaire distributed to 150 Malaysian citizens via social media platforms. The questionnaire explored respondents' knowledge of cryptocurrencies, awareness of security risks, and protective measures such as security programs, two-factor authentication (2FA), and education. The results of the regression analysis show that the installation of security programs, 2FA, and public education are all significant predictors of increased awareness of cryptocurrency security risks, with a combined R² value of 0.523. This suggests that 52.3% of the variance in awareness is explained by these factors. The study concludes that strengthening security measures and providing education can significantly improve public understanding of cryptocurrency risks, leading to safer investment practices. The implications of these findings highlight the need for targeted education and security initiatives to enhance public confidence in cryptocurrency, making digital currency investments more secure

Behavioral and Psychological Determinants of Cryptocurrency Investment: Expanding UTAUT with Perceived Enjoyment and Risk Factors

With their potential for high returns and expanding role in the financial landscape, cryptocurrency investments have garnered the attention of the financial press and investors. Applying an integrated research model based on the Unified Theory of Acceptance and Use of Technology (UTAUT), this study investigates the factors influencing individual investors’ attitudes toward cryptocurrency investments and their intention to continue investing. The model incorporates constructs such as performance expectancy, effort expectancy, social influence, perceived risk, perceived privacy, technology competency, perceived enjoyment, and prior experience. Data from 506 cryptocurrency investors located in the United States were collected through a 50-item questionnaire. The findings indicate that performance expectancy and perceived enjoyment positively impact attitudes toward cryptocurrency investments, which, in turn, influence the intention to continue investing. Perceived privacy positively affects performance expectancy, while technology competency enhances effort expectancy. These results offer valuable insights for policymakers and cryptocurrency exchanges to foster sustainable growth in the cryptocurrency market. Despite its contributions, the study acknowledges limitations, including a focus on current investors in the US and the exclusion of factors such as optimism and innovativeness. Future research should explore these aspects across different populations and regions to gain a more comprehensive understanding of cryptocurrency investment behavior.

The Effect of Demographics on Investment Choice in Digital Currencies: An Empirical Study of Thai Investors

The purpose of this study is to compare the differences in Thai investors' demographic characteristics that influence their decision to invest in digital currencies. This study was quantitative research. The samples of this study were 400 Thai investors who invest in digitalcurrencies, using non-probability sampling by convenience sampling method. We employed a questionnaire as our research tool, demonstrating content validity of 1.00 and reliability of 0.70 across the entire questionnaire. We analysed the data using a one-way analysis of variance. The research discovered that different demographic factors of Thai investors, such as their age, average monthly income, duration of investments, and amount of money invested, influenced different investment decisions in digital currencies. However, the various demographic factors of Thai investors, such as their gender and level of education, did not influence different investment decisions in digital currencies. Digital currency investment providers can use these research results to develop strategies that accurately and successfully target or qualify investors.

A Study on the Preference of the Three Major Currencies of SDR as an International Financial Investment Currency: Focused on the CNY as an International Financial Investment Currency

A Study on the Preference of the Three Major Currencies of SDR as an International Financial Investment Currency: Focused on the CNY as an International Financial Investment Currency

CSR practices and earnings management: the mediating effect of accounting conservatism and the moderating effect of corporate governance: evidence from Finnish companies

Purpose This study aims to examine the impact of corporate social responsibility (CSR) on earnings management (EM). Furthermore, the authors assessed the mediating effect of accounting conservatism (AC) on the CSR-EM relationship over the long term. The authors also tested the moderating effect of corporate governance (CG) on the AC-EM relationship in the Finnish context. Design/methodology/approach Linear regressions were applied to panel data using Thomson Reuters’ ASSET4 database. Data were collected from 140 Finnish firms between 2005 and 2022. Findings The results confirm that negative CSR has an impact on EM. Moreover, AC mediates the relationship between CSR and EM. Likewise, CG moderates the relationship between AC and EM. Practical implications This paper may interest academic researchers and potential and current investors. This paper will help investors make relevant investment decisions. Managers should pay special attention to their EM. These firms must take social responsibility vis-a-vis all their stakeholders. Originality/value To the best of the authors’ knowledge, this study is the first to use AC as a mediator and CG as a moderating variable in the Finnish context. This research will enrich the literature by providing a comprehensive picture of the relationships between CSR and EM through AC and CG in developed markets. Therefore, it is crucial to understand the implications of CSR in Finnish companies.

Analysing Risk and Returns: A Study on Selected Crypto Currencies

The present study focuses on "Crypto currency" also called digital money existing on the block chain. It refers to the transactions related to computer-generated currencies which are secured by crypto currencies. The data considered in the project is from 2017 to 2023. The objective of this research is to compute and compare the risk and return performance of the selected crypto. In India, crypto currency investment carries a high degree of risk due to its uncertain legal status and lack of regulation. The Reserve Bank of India has issued warnings about the potential financial, operational, legal, customer protection, and security related risks associated with dealing in crypto currencies. However, the potential for high returns has also attracted many investors. To make informed decisions, Indian investors should conduct thorough research on the market, stay up-to-date on regulatory changes, and diversify their investment portfolios. It is also essential to have a clear understanding of one's risk tolerance and not invest more than one can afford to lose. In conclusion, by taking a balanced and well-informed approach to invest in crypto currencies, Indian investors can make effective decisions that weigh both the potential risks and returns.

Effect of herding behavior and overconfidence bias on investor’s financial decisions: A case of investment in crypto currency in Pakistan

There are various behavioral aspects that influence the financial decisions of individual investors, such as overconfidence, herding behavior, loss aversion, and regret aversion. Other psychological elements may play a substantial influence in deciding the success or failure of any financial action. The primary aims of the present research article are to examine the effects of overconfidence bias and herding behavior on individual financial decisions regarding crypto currency investment. The markets for crypto currencies are extremely sensitive to any minute or significant changes in the economy, as well as to any changes in the individual behaviors of investors. To achieve these aims, 650 questionnaires were distributed to individual investors employed by various financial institutions, multinational corporations, including oil and gas exploration and production companies, operating in Pakistan, individual investors dealing in stocks, and students regardless of investment size. Purposive sampling was used to choose 311 valid responses from a total of 593. Those investors that engage in crypto currency investments were deemed valid responses. Classifications of investments were outlined, and demographic information was requested from respondents. SPSS-based empirical analysis provided the basis for the conclusions. The primary findings indicate that both overconfidence bias and herding tendency have a favorable and statistically significant impact on investors' financial decisions when investing in cryptocurrencies. In this study's sample, however, the majority of investors were overconfident in their crypto currency investing decisions.

The impact of investor sentiment on stock liquidity of listed companies in China

Researchers have scrutinized the link between investor sentiment and stock market liquidity globally, yet few have delved into this dynamic in emerging markets, especially China. Utilizing a sample of 1,839 publicly listed companies in China from 2010 to 2019, this study applies firm- and year-fixed-effects models to explore the nexus between investor sentiment and stock illiquidity, employing the Amihud measure for stock illiquidity assessment. The outcomes of these fixed-effect regressions illustrate a significantly positive relationship between investor sentiment and stock liquidity in the Chinese market. The positive link is more evident in scenarios characterized by high firm leverage, rapid revenue growth, larger corporations, greater institutional ownership, higher stock volatility, and lower book-to-market ratios. Intriguingly, this analysis incorporates the quadratic term of investor sentiment to examine the potential for a nonlinear dynamic between stock illiquidity and investor sentiment. The findings elucidate that the effect of investor sentiment on stock liquidity diminishes at elevated levels of sentiment, revealing a nonlinear inverse U-shaped relationship. The positive correlation between investor sentiment and stock liquidity persists across the three divisions of the Chinese Shenzhen Stock Exchange and remains robust using alternative liquidity measures, such as Roll’s impact and zeros impact. Addressing causality concerns, current investor sentiment appears to influence subsequent liquidity levels. These results provide valuable perspectives for policymakers, business executives, and investors in the stock market. Acknowledgment This research was funded by the Department of Education of Zhejiang Province General Program [Y202353438], the Wenzhou Association for Science and Technology—Service and Technology Innovation Program [jczc0254], the Wenzhou-Kean University Student Partnering with Faculty Research Program [WKUSPF2023004], and the Wenzhou-Kean University International Collaborative Research Program [ICRP2023002].

Volatility Concerns for Crypto Currency Investments in India Amid Fears of Inflation

Volatility Concerns for Crypto Currency Investments in India Amid Fears of Inflation

An interpretable deep learning multi-dimensional integration framework for exchange rate forecasting based on deep and shallow feature selection and snapshot ensemble technology

Accurate exchange rate forecasting is important for the better realization of international economic transactions and international currency investments. However, it is challenging to forecast exchange rates due to their high volatility, nonlinearity, and noisy characteristics. This paper creatively proposes a novel interpretable deep learning multi-dimensional integration framework for foreign exchange rate forecasting based on shallow and deep feature selection and snapshot ensemble technology. The main factors affecting exchange rates are considered at a deep and shallow level, and the feature selection project is implemented. A cluster-based multidimensional learning paradigm is proposed. The framework clusters data and constructs predictive sub-models and then embeds snapshot ensemble techniques into models to improve the robustness of single models. Finally, the results are nonlinearly integrated by a deep learning model. In addition, three datasets and twelve comparative models were used to demonstrate the performance of the models. The empirical results show that the proposed model has the smallest mean absolute percentage error (0.407859%, 0.47134%, and 0.470167%, respectively).

Foreign Investments and Stock Market: Evidence From Palestine

Purpose: This study aims to examine the association between the different forms of inbound foreign investments and the Palestine Exchange (PEX) index to shed light on the nature of that impact.
 
 Theoretical Framework: Several academic studies have examined stock market index factors. Chen, Roll, and Ross's (1986) seminal study on macroeconomic conditions and U.S. stock returns provides an example. Interest rate, inflation, industrial production, risk premium movements, and dividend yield positively explain expected stock return. Abusharbeh and Karim (2016) found that interest and consumer price index positively affect banking and investment firm profits on The Palestine Exchange (PEX). Shahbaz (2013) examined how foreign direct investment affects Pakistan's stock market. Results supported foreign direct investment's stock market complementarity.
 
 Design/Methodology/Approach: The market index and panel quarterly data for inward foreign investments are used in this study. From 2009 to 2022, end-of-quarter data were collected on total inward foreign investments, their sub-components (direct investments, stock portfolio investments, and currency and deposits in Palestine), and the market index (Al-Quds index) closing value. Fifty-six observations were gathered.
 
 Findings: The study found that the overall model integrating all three types of inward foreign investments significantly explains the market index. Foreign portfolio investments (FPI) are significantly associated with the stock market index. However, the results showed that inward foreign direct investments (FDI) and foreign deposits and currency investments (FCI) have no significant impact on the stock market index, indicating that they do not complement or substitute each other.
 
 Research, Practical & Social Implications: This study can help the stock market, regulators, and policymakers create incentives and regulations to attract different forms of inward foreign investments. It also examines why foreign direct investments (FDI) and foreign deposits and currency investments do not complement or substitute stock market development.
 
 Originality/Value: This study provides empirical evidence on the impact of the different forms of foreign investment in Palestine on the stock market. Further research is recommended to explore additional variables that might be significant, such as market capitalization and market volume.

Stock market reactions and optimism bias in analysts’ earnings forecasts: An analysis of China's stock markets

This paper examines analysts’ catering behavior to current investor demand, proxied by the unbalanced stock market reaction toward optimistic forecasts and non-optimistic forecasts (i.e., optimism premium). Using data on earnings forecasts issued by sell-side analysts in China from 2014 to 2018, we show that the optimism premium significantly increases analysts’ tendency to issue optimistic forecasts—in short, that analysts do cater to investor demand. The implications of our findings for theory and practices are discussed.

Current Account Uncertainty and Currency Premia

We empirically study the relationship between currency excess returns and current account uncertainty, measured as forecast dispersion. We find that investment currencies deliver low returns, whereas funding currencies offer a hedge when current account uncertainty is unexpectedly high. Moreover, an increase in current account uncertainty is associated with higher expected future excess returns on investment currencies. This mechanism is consistent with the recent advances in exchange rate theory based on capital flows in imperfect financial markets. This paper was accepted by Gustavo Manso, finance. Funding: A. Krecetovs thanks the Brevan Howard Centre at Imperial College London for financial support. Supplemental Material: The data files and online appendix are available at https://doi.org/10.1287/mnsc.2023.4949 .

Impression Management in Voluntary Narrative Disclosure through Length and Tone, Stakeholder Theory Lens

Purpose: The use of impression management in corporate reporting is mostly in pursuit of value creation for stakeholders. The study exposes the use of impression management practices in voluntary narrative disclosures. The study focused on Top 40 Johannesburg Stock Exchange (JSE) listed companies. Impression management was examined through the length of the chairperson’s statement and use of positive tone. The chairperson’s statement focuses on the future and strategic direction. Stakeholders focus on the chairperson’s statement for investment decision-making purposes.
 Approach: Quantitative content analysis is used on secondary data extracted from integrated reports.
 Findings: The study found that profitable and nonprofitable JSE-listed companies use impression management through the length of the chairperson’s statement and the use of a positive tone.
 Value: The study attempts to provides notice of the use of impression management to prospective and current investors who to some extent rely on voluntary narrative disclosure for investment decision making purposes and adds the debate on stakeholder theory in corporate reporting.

INVESTMENT BEHAVIOUR AND RISK PERCEPTION: AN ANALYSIS FOR TURKISH MARKET

Purpose- The cognitive comprehension of financial indicators, risk aversion, risk perception, and investment behavior is defined as financial literacy. It's possible that a variety of characteristics, such as gender, age, income level, social standing, education, etc., will affect an investor's behavior. The purpose of this study is to highlight the behavior of investors in Turkish capital markets. The analysis is done on the results of two surveys, the first conducted in the fourth quarter of 2022 and the second in the first quarter of 2023. Methodology- This study's objective is to highlight investor behavior and risk perception in Turkish financial markets. In the most recent two consecutive quarters, the results of two surveys are analyzed and compared. Three sections comprise the surveys. A demographic question is asked in the first section. The second section asks questions concerning investment behavior, signs of financial stress, and confidence in regard to one's financial literacy. The final aspect contributes to the analysis of what people think of the Bitcoin market. In this study, Graphic analysis, Cronbach Alpha, Normality, and Mann-Whitney U tests are performed, respectively. First, the graphical analysis of the selected questions is made. Based on these graphs, the similarities and differences between the surveys are shown. Second, The reliability test is applied to the selected questions for the statistical modeling of the analysis. This test is determined as the Cronbach Alpha test. Third, the Normality test is applied to reveal which test to use in the next step. Two different tests are used for this analysis. These are the Kolmogorov-Smirnov and Shapiro-Wilk tests. Fourth, the Mann-Whitney U test is applied. At this stage, firstly, Mann-Whitney U and Wilcoxon W test statistics are examined. The ranks are calculated for each variable. Finally, the Mann-Whitney U test is applied, and the results are interpreted. Fifth, The results of the two surveys are compared. Findings- The findings show both similarities and differences among numerous variables. For instance, holding time is defined as the amount of time an investor holds an investment or as the time between purchasing it and selling it. Investors' risk aversion and financial literacy both influence the holding period. Riskier assets force investors to adjust their purchase or sell actions dynamically. The results show various portfolio diversification behaviours. While men prefer to start with foreign currency investments, women are more interested in making gold investments. Also, middle-aged investors invest more in cryptocurrencies and take more risks than younger investors. Conclusion- based upon the analysis, findings it may be concluded that respondents do differ in their investment preferences and risk-taking over the years. The findings show various portfolio diversification behaviors. While men prefer to invest in foreign currency, women are more interested in purchasing gold. Keywords: Investor behavior, risk perception, cryptocurrency market, Bitcoin, Mann-Whitney U test. JEL Codes: G1, G4, C4

Estimating Value-at-Risk in the EURUSD Currency Cross from Implied Volatilities Using Machine Learning Methods and Quantile Regression

In this study, we propose a semiparametric, parsimonious value-at-risk forecasting model, based on quantile regression and machine learning methods, combined with readily available market prices of option contracts from the over-the-counter foreign exchange rate interbank market. We aim at improving existing methods for VaR prediction of currency investments using machine learning. We employ two different methods, i.e., ensemble methods and neural networks. Explanatory variables are implied volatilities with plausible economic interpretation. The forward-looking nature of the model, achieved by the application of implied volatilities as risk factors, ensures that new information is rapidly reflected in value-at-risk estimates. To the best of our knowledge, this study is the first to utilize information in the volatility surface, combined with machine learning and quantile regression, for VaR prediction of currency investments. The proposed ensemble models achieve good estimates across all quantiles. The light gradient boosting machine model and the categorical boosting model both yield estimates which are better than, or equal to, those of the benchmark model. In general, neural network models are quite unstable.

A Review on the Comparison and Analysis of Major Cryptocurrencies

With the increasing demand of virtual currency, cryptocurrencies are gaining popularity throughout the world for transactions be it legal or illegal. The yields returned from investment in crypto currency these days are huge but their existence and reliability has always been questioned. A cryptocurrency uses cryptography for implementing security. In spite of several problems in crypto currencies, the growing success of Bitcoin since its launch has emerged in a number of organizations coming forward with substitute cryptocurrencies .This study tries to present a comparison of six famous cryptocurrencies - Bitcoin, Ethereum, Litecoin, Dash, Monero and IOTA in the light of their volatility and strengths in present times and also discusses their current trends. A thorough study of literature showed that no paper has been presented keeping in mind only these six currencies, so this article is the first of its kind to present a comparison of technicalities of these cryptocurrencies.

Study the Impact of the Epidemic on the Stock Market from the Perspective of Behavioral Economic

Since the successful development of COVID-19 vaccine and the launch of some related drugs. The epidemic has gradually become less terrible and let us see the hope of economic recovery. In the past three years, quite a few industries in China have suffered losses or even closures due to the epidemic. Does the normalization of the epidemic represent the gradual improvement of the market? Similarly, will the stock market also be affected and fluctuate accordingly? If you know the im-pact parameters of the stock market and the epidemic situation, can you make profits in the stock market? After generating these questions, we first analyze the current investors and summarize the characteristics of age, occupation and marital status, which is an important part of the analysis of the stock market. Then, the relationship between the epidemic and enterprises concluded that the tertiary in-dustry was most closely related to the epidemic situation. Put forward a concept of "epidemic stock" that is to say, the stock that affected obviously by the epidem-ic situation. In the use of behavior financial knowledge, I will have no rich in-vestment experience of retail investors, outbreak reference, and suit the remedy to the case at the same time, keep a result will never just a factor decision attitude. For example, "epidemic stock" analysis about the model and supplement of profes-sional knowledge, to introduce the analysis of outbreak. In order to help you grasp the proportion of the epidemic impact on the epidemic stocks, convenient for investment reference.

Pengaruh Kompetensi, Teknologi Informasi, Persepsi Resiko Dan Tingkat Literasi Keuangan Terhadap Minat Investasi Crypto Currency

The research started from the development of crypo investment so that it has become a cornerstone in this study is to analyze the influence of competence, Information Technology, Risk Perception and level of financial literacy on crypto currency investment interests. To complete this study there are 98 respondents and use simple random sampling. The conclusion of this study is that simultaneously and partially competence, information technology, risk perception and level of financial literacy have a positive and significant effect on crypto currency investment interested.
 Keywords: Competence, Information Technology, Risk Perception, Financial Literacy Level, Investment Interest.

Regime-dependent drivers of the EUR/CHF exchange rate

We analyze drivers of the EUR/CHF exchange rate in different regimes between 2000 and 2020. Structural breaks between these subperiods are estimated in an integrated way together with the drivers that are relevant during these subperiods. Overall, the main drivers of the exchange rate include European equity and volatility indices, interest rate and term structure slope differentials, as well as monetary policy interventions. For the “peg period” September 2011–January 2015, in addition to the observed exchange rate we also analyze the drivers of the latent exchange rate that could have been observed in the absence of the peg. Interestingly, the SNB’s foreign currency investments became a significant driver of the EUR/CHF exchange rate only after the end of the peg period when there was no longer an officially communicated target rate.