Financial Research Research Articles

Islamic Economics and Finance: Trend Topics and Thematic Evolution

This study aims to determine the development and trend map of research on the theme of Islamic Economic and finance published by reputable journals. The data used in this study are 2498 public indexed research on the theme of Islamic Economic and finance in the period 1976 to 2021. The map of research development in the field of Islamic Economic and finance is obtained through an export process which will be processed and analyzed using the R Biblioshiny application program. This study shows the results that the number of publications on the development of Islamic Economic and finance research has increased significantly. In addition, the results show that the journal that publishes the most and has the greatest impact on Islamic Economic and finance research is the Journal of Islamic and Middle Eastern Finance and Management. The author with the longest publication track record is Wilson R while the author with the highest quantity of publications is Hassan MK. The educational affiliation that has the most and relevant publications is International Islamic University Malaysi. The results also show that the most used topic keywords are Islamic, Finance, Banking, and Financial.

Interpolation of missing swaption volatility data using variational autoencoders

AbstractAlbeit of crucial interest for financial researchers, market-implied volatility data of European swaptions often exhibit large portions of missing quotes due to illiquidity of the underlying swaption instruments. In this case, standard stochastic interpolation tools like the common SABR model cannot be calibrated to observed volatility smiles, due to data being only available for the at-the-money quote of the respective underlying swaption. Here, we propose to infer the geometry of the full unknown implied volatility cube by learning stochastic latent representations of implied volatility cubes via variational autoencoders, enabling inference about the missing volatility data conditional on the observed data by an approximate Gibbs sampling approach. Up to our knowledge, our studies constitute the first-ever completely nonparametric approach to modeling swaption volatility using unsupervised learning methods while simultaneously tackling the issue of missing data. Since training data for the employed variational autoencoder model is usually sparsely available, we propose a novel method to generate synthetic swaption volatility data for training and afterwards test the robustness of our approach on real market quotes. In particular, we show that SABR interpolated volatilities calibrated to reconstructed volatility cubes with artificially imputed missing values differ by not much more than two basis points compared to SABR fits calibrated to the complete cube. Moreover, we demonstrate how the imputation can be used to successfully set up delta-neutral portfolios for hedging purposes.

The Market Efficiency in the Significant Events/Global Events: A Review of Empirical Research

The efficient market hypothesis is a significant theory widely applied in modern economic and financial research about the impact of sudden global emergencies on various markets. Investigating the influence of the Efficient Market Hypothesis on public contingencies can augment the understanding of market behavior and investors decision-making processes. This could enable anticipating market trends and risks, facilitating prudent investment activities. This study examines the empirical research through the methodology chosen, application, and comparison of conclusions to summarize the effects of the crisis on financial market efficiency within a theoretical analysis framework. This study explores the different methodologies and results of research that test market efficiency in response to events impacting economic performance. As market theory evolves, increasingly refined models are being used, leading to more precise measurements of event effects on markets and better forecasting of market impact for effective decision-making.

Research on the Volatility of the S&P 500 Stock Index Based on GARCH Family Models

Volatility is an important issue in financial research. In this paper, in order to study the volatility of the S&P 500 index, which is representative of the American stock market, is used as research object, and the daily closing prices from July 2018 to July 2022 are selected. It has since become widely accepted in the academic community that stock return volatility is slow moving. Therefore, the series cannot accurately capture the characteristics of volatility. Developing the GARCH model gives us an effective way of describing return volatility. The statistical software EViews is initially utilized to take the logarithmic difference of the data and obtain the daily return series of the past five years, and to test if the time series has ARCH effect. The results suggest that the returns in the series are not correlated with each other, and that volatility has an obvious correlation, which makes it suitable to model with a GARCH family model.

Research on Green Finance Facilitating Enterprise ESG Development

While past studies have focused on the emergence and application of green finance as a contemporary financial concept, little attention has been given to its relationship with environmental, social, and governance (ESG) performance. Green finance and ESG intertwine systematically and complexly, making it essential for organizations to employ suitable coordination frameworks to facilitate the control of the relationship. This research paper aims to explore how advancements in green finance research facilitate ESG development. Using a secondary research literature review approach, the research paper expounds on the conceptual foundation of green finance and ESG, the intersection between green finance and ESG, and the influence of green finance in environmental stewardship, corporate social responsibility, and enhancing organizational governance. The assessment identifies and outlines the future investment consequences of green financing, including how it will influence the establishment of circular economies at the organizational and national levels. The results underline the crucial importance of facilitating further research on green financing.

Determinants of the Selection of Accounting Conservatism in Indonesia: A Systematic Literature Review Approach

In the current era of globalization and the internationalization of capital markets, it is crucial to have clear and prompt financial reporting. Accounting conservatism is an essential qualitative characteristic in the field of accounting information. This study employs the Systematic Literature Review (SLR) approach to examine the factors influencing the selection of accounting conservatism within the framework of recognized national journals. By implementing rigorous inclusion and exclusion criteria, this study utilized Google Scholar to identify 10 nationally recognized journals that have received accreditation. The literature search process was meticulously overseen and employed the Publish or Perish application to guarantee precision and consistency in data compilation. The research findings indicate that managerial ownership of shares has a substantial and favorable impact on implementing accounting conservatism practices. Specifically, 81.22% of the companies in the sample were in a state of non-financial distress. Also, factors such as profitability, capital intensity, CEO gender, and board size impact accounting conservatism. Financial and non-financial factors influence such policies, including financial stress, leverage, and institutional ownership. These findings offer valuable insights into the dynamics of accounting conservatism in companies, inform financial decisions and the development of company policies, as well as provide guidance for future research in accounting and finance.

Enhancing Crypto Success via Heatmap Visualization of Big Data Analytics for Numerous Variable Moving Average Strategies

This study employed variable moving average (VMA) trading rules and heatmap visualization because the flexibility advantage of the VMA technique and the presentation of numerous outcomes using the heatmap visualization technique may not have been thoroughly considered in prior financial research. We not only employ multiple VMA trading rules in trading crypto futures but also present our overall results through heatmap visualization, which will aid investors in selecting an appropriate VMA trading rule, thereby likely generating profits after screening the results generated from various VMA trading rules. Unexpectedly, we demonstrate in this study that our results may impress Ethereum futures traders by disclosing a heatmap matrix that displays multiple geometric average returns (GARs) exceeding 40%, in accordance with various VMA trading rules. Thus, we argue that this study extracted the diverse trading performance of various VMA trading rules, utilized a big data analytics technique for knowledge extraction to observe and evaluate numerous results via heatmap visualization, and then employed this knowledge for investments, thereby contributing to the extant literature. Consequently, this study may cast light on the significance of decision making via big data analytics.

CSR research in corporate finance: a comment on Gillan et al., “firms and social responsibility: a review of ESG and CSR research in corporate finance”

PurposeBy providing a critical analysis of a recent literature review concerning environmental, social and governance (ESG) and corporate social responsibility (CSR) research in finance which was published in the Journal of Corporate Finance (Gillan et al., 2021), examining it in the light of several reviews on the same or similar lines of research, this paper aims to serve those who wish to do research in the CSR/ESG/corporate sustainability and the reporting thereof areas in finance.Design/methodology/approachThis note serves to comment on Gillan et al.’s review.FindingsIrrespective of the merits of the review, it should not be used by newcomers to the research on CSR in corporate finance given that it provides a very biased view of it.Originality/valueThis commentary serves the purpose of cautioning those interested in becoming acquainted with CSR-related research in corporate finance that the review on which it focuses should be used only as an entry point, given that it offers an incomplete and biased picture.

Reviewer Acknowledgements for Accounting and Finance Research, Vol. 12, No. 4, 2023

Reviewer Acknowledgements for Accounting and Finance Research, Vol. 12, No. 4, 2023

Developments from the PSLRA: Beyond the Lead Plaintiff Provision in Financial Research

Since the passage of the Private Securities Litigation Reform Act in 1995, a robust literature has analyzed the impact of the lead plaintiff provision, which made it more likely for institutional investors to take on the role of lead plaintiff. Recently, less investigated provisions in the PSLRA have had an increasingly relevant role in shareholder litigation, corporate governance, and how firms choose to go public. In this article, we review the law, finance, accounting, and economics literature to show how these other provisions have evolved over time, affecting the incentives for corporate disclosure, how firms go public, and corporate governance.

Has Italy Won or Lose in the European Monetary Union

The transformation of the European Monetary System into the European Monetary Union is a significant event in the development of the world economy and a major issue of concern in international financial research. The establishment of the European Monetary Union is the basis and guarantee for the establishment of the European Economic Union and Political Union. In this study, by analyzing various economic indicators of Italy, the author can determine whether it is a winner or loser in terms of gains and losses in the European Monetary Union and then can also infer the changes in the economies of various countries under the union policies. In terms of economic development, it can be seen from the Gini coefficient and GDP growth rate that Italy has long been in a predicament of a large wealth gap and weak economic development. In terms of economic security, it can also be inferred that Italy is trapped in a quagmire of foreign debts and perennial fiscal deficits through the two data of the percentage of foreign debt to GDP and the ratio of fiscal revenue and expenditure, resulting in insufficient amplitude credibility and large economic loopholes. From this, it can be judged that Italy is in the position of a loser in the European Monetary Union.

An Empirical Research of Asset Pricing Models in the US Market under COVID-19

Asset pricing theory has been a key area of research in finance. Since the in-troduction of CAPM, asset pricing models have been very widely used. Re-searchers have discovered many phenomena that cannot be explained by the CAPM model, so they have made many refinements to the asset pricing model and developed various improved versions that can better explain stock returns. The Fama and French three-factor model (FFTFM) and the five-factor model (FFFFM) are two of the most classic and most used asset pricing models. However, as time goes by and financial markets continue to evolve, many scholars have questioned whether traditional asset pricing models are still valid. Starting from the theoretical explanation of CAPM, FFTFM, and FFFFM factor selection, this paper uses the stock market data from 2000 to March 2023 to divide stocks into six portfolios based on their size and book value and conduct regressions according to the above three models respectively to evaluate and compare the recent performance of these models. In addition, this paper also performs separate regressions using data from the novel coronavirus epidemic period in particular to verify the robustness of the model to different market environments. According to the results of this paper, the FFFFM model has the best explanatory power. The role of the factors in the model on stock returns varies with portfolio selec-tion, i.e., firm size and book value, and the market environment also has an impact on the significance of the factors, leaving room for improvement in the model to cope with particular markets, but overall, FFFFM is still effec-tive in explaining present market stock prices.

A Comparative Study on Measuring Similarity between Companies Based on Financial Statements

It is important for financial researchers to measure similarity between companies. This passage classifies references in this area based on research objects and research methods. To be more specific, there are four research objects based on data structure and data connectivity. Research methods can also be classified into four types based on data form and modeling type. It can be concluded that there are academic blanks on models based on graph theory: no matter independent data or unstructured data should be used more wildly. Moreover, interconnected structured data should be used more often when vectors are introduced into predictive modeling.

Forecasting International Stock Market Trends: XGBoost, LSTM, LSTM-XGBoost, and Backtesting XGBoost Models


 
 
 Forecasting time series is crucial for financial research and decision-making in business. The nonlinearity of stock market prices profoundly impacts global economic and financial sectors. This study focuses on modeling and forecasting the daily prices of key stock indices - MASI, CAC 40, DAX, FTSE 250, NASDAQ, and HKEX, representing the Moroccan, French, German, British, US, and Hong Kong markets, respectively. We compare the performance of machine learning models, including Long Short-Term Memory (LSTM), eXtreme Gradient Boosting (XGBoost), and the hybrid LSTM-XGBoost, and utilize the skforecast library for backtesting. Results show that the hybrid LSTM-XGBoost model, optimized using Grid Search (GS), outperforms other models, achieving high accuracy in forecasting daily prices. This contribution offers financial analysts and investors valuable insights, facilitating informed decision-making through precise forecasts of international stock prices.
 
 
 

Bibliometric Analysis of MSME Accounting and Finance Research in Indonesia

To support MSME in various ways, a deep understanding of it is necessary to recover from the post-pandemic period. Research is a good starting point to resolve the issue, as it has a huge impact on society. This research was conducted using bibliometric analysis. The stages carried out in this research included data collection, data reduction, and data mapping. Data collection were started with the keywords: “UMKM Akuntansi Keuangan” in the crossref dataset. This result also showed that the limited generalizability of the results to the research on these topics. There has been a change in trend in the topic of discussion, research methods, and research subjects with regards to the topic of discussion in research in the field of accounting and financing MSMEs over time. In the past, research mostly discussed financial performance, using secondary data provided by the entity and financial statements. Meanwhile, recent research often discusses the conformity of MSMEs financial reporting.
 Keywords: bibliometric analysis, MSME, accounting, finance, research

Women empowerment in Africa: can we rely on Islamic finance?

Purpose The purpose of this paper is to examine the effects of Islamic finance on women empowerment in Africa between the periods of 1975 and 2021. Design/methodology/approach This paper uses secondary data for 27 African countries obtained from the World Development Indicators, World Population Review and the Varieties of Democracy databases. Four dimensions of women empowerment, namely, economic, social, political and household, are considered while Islamic finance is proxied by a binary variable with 1 and 0 representing the presence and the absence of Islamic finance, respectively. The two-staged least square estimation technique is used to control for the problem of endogeneity. Findings This study revealed that Islamic finance positively affects women empowerment in Africa. Specifically, Islamic finance has positive and significant effects on women political empowerment, women economic empowerment and women social empowerment in Africa but nonsignificant effect on home empowerment. These effects are more pronounced in middle-income than in low-income countries and in countries with higher penetration rate of Islamic finance. Practical implications Policymakers should put in place the necessary mechanisms for the promotion of Islamic finance such as the enacting of laws that ensures the creation of full-fledged Islamic banks, encouraging research in Islamic finance and Islamic economics. These policies should equally be backed by the creation of some accompanying measures such as the abolition of social norms that limit women’s ability to take part in decision-making. Originality/value To the best of the authors’ knowledge, this is the first study involving an Africa continent-wide analysis of the effects of Islamic finance on women empowerment.

Cryptocurrencies from a behavioural finance perspective

In today's world, cryptocurrencies are no longer a technological miracle for a small group of programmers. They have become a very common investment instrument that attracts the attention of both traditional investors (funds and traders) and those who are not interested in classical markets and investing in general. This is especially true for bitcoin. The purpose of the study was to investigate the influence of behavioural psychology in making investment decisions in cryptocurrency markets. The research methods included analysing historical data on cryptocurrency prices, as well as observing investors' reactions to important events and news related to cryptocurrencies. In addition, behavioural analysis methods were used to understand and predict investors' reactions to various incentives and situations in the cryptocurrency markets. The results of the article describe the main provisions of behavioural finance, which are necessary for an overview of the cryptocurrency market. The impact of the main topics of behavioural finance research is also considered. It should be noted that in the absence of a large amount of data, the study of the cryptocurrency market and the behaviour of participants is mainly a hypothetical assessment, and the empirical aspects of the study are copied from the behavioural finance of the classical market. Considering the cryptocurrency market from the point of view of behavioural finance, the main points of view of different parties were considered: both supporters of cryptocurrency and those who consider this phenomenon to be an economic bubble in a technological wrapper. The information reflecting the main biases of behavioural finance, which relate to both classical markets and cryptocurrency markets, is systematised. The study of cryptocurrencies from the point of view of behavioural finance reflects the practical value in understanding the impact of behavioural factors on price dynamics and investment decisions in cryptocurrency markets

Comparative Analysis of Sell-In-May-And-Go-Away and Monthly Effect Before and During COVID-19 Pandemic at LQ45 IDX

In 2022, the number of investors in the Indonesian stock market experienced a four-fold growth compared to 2019. This surge occurred during the epidemic period. This financial research aims to analyze the impact of the COVID-19 pandemic on the monthly average return and risk pattern of LQ45, as well as the presence of the Sell-in-May-and-Go-Away (SIMAGA) effect and the optimal investment strategy for LQ45. The study uses a descriptive-comparative methodology and employs mathematical and statistical frameworks. The sample consists of LQ45 companies from 1997 to 2022. Data analysis techniques include the Normality Test, Wilcoxon Rank Test, F Test, and investment strategy simulation. The results indicate that COVID-19 did not have a negative effect on the monthly returns and risk patterns of LQ45, except in 2002. Additionally, the SIMAGA phenomenon is not present in LQ45, but the Sell in August-Buy in November (SIABIN) strategy has been identified as the most effective. These findings provide valuable insights for investors in allocating their investments and determining the best strategy for buying stocks. It is important to consider monthly return variance as a key metric for measuring investment risk and its impact on overall returns.

Is corporate finance research in decline?1

AbstractThere has been a secular decline in published research on corporate finance topics over the past decade or so. While this raises questions about the vitality of the field going forward, I argue that a number of recent developments represent important new directions for research in corporate finance. These developments have begun to have an impact on scholarly activity and I expect this to continue in the near future.

Gender Social Bonds in the Latin American Market

Although issuances of sustainable debt are growing worldwide, there is a lack of studies that allow a better understanding the social bond issuances, particularly those with a gender focus, which are directly related to the achievement of the Sustainable Development Goals 5, 8, 9, and 10. This study addresses the identified knowledge gap by examining the overall state of the gender social bonds in the Latin American market between 2019 and 2022. The results revealed that a total of USD 1 billion was issued by 12 issuers conducting 14 issuances across six countries. Also, most issuances were financial corporations (58.4%) and supranational banks had a pivotal role in this market by being buyers and/or lead managers. As the first study conducted on this topic, this represents a milestone in sustainable finance research. Finally, this study will allow policy makers, regulators, and researchers to promote the issuance of gender social bonds.