Financial Practitioners Research Articles

Historical Simulation Systematically Underestimates the Expected Shortfall

Expected Shortfall (ES) is a risk measure that is acquiring an increasingly relevant role in financial risk management. In contrast to Value-at-Risk (VaR), ES considers the severity of the potential losses and reflects the benefits of diversification. ES is often calculated using Historical Simulation (HS), i.e., using observed data without further processing into the formula for its calculation. This has advantages like being parameter-free and has been favored by some regulators. However, the usage of HS for calculating ES presents a potentially serious drawback: It strongly depends on the size of the sample of historical data, being typically reasonable sizes similar to the number of trading days in one year. Moreover, this relationship leads to systematic underestimation: the lower the sample size, the lower the ES tends to be. In this letter, we present examples of this phenomenon for representative stocks and bonds, illustrating how the values of the ES and their averages are affected by the number of chosen data points. In addition, we present a method to mitigate the errors in the ES due to a low sample size, which is suitable for both liquid and illiquid financial products. Our analysis is expected to provide financial practitioners with useful insights about the errors made using Historical Simulation in the calculation of the Expected Shortfall. This, together with the method that we propose to reduce the errors due to finite sample size, is expected to help avoid miscalculations of the actual risk of portfolios.

Forecasting China’s Short-Term Energy Futures Price Using a Novel Secondary Decomposition-Optimized System

AbstractEnergy futures price forecasting is challenging due to the nonlinear and fluctuant characteristics. Existing literature mainly uses decomposition and ensemble method which neglects the intrinsic mode function obtained by the first decomposition could be irregular and thus reduces the prediction accuracy. To fill the research gap, a novel secondary decomposition-optimized-KELM-ensemble forecasting system is proposed to perform short-term forecasting in this study, which synthesizes two-stage data decomposition method, Sparrow search optimization algorithm, and extreme learning machine with kernel. We test the method with two energy futures prices in China, demonstrating that both one-day and three-day ahead forecasting results obtained are more accurate and stable compared to existing models in the literature, such as BPNN (improved by 58.42% on one-day ahead and 56.44% on three-day ahead by MAE) and KELM (improved by 56.40% on one-day ahead and 49.04% on three-day ahead by MAE). Therefore, the forecasting system introduced in this paper can provide useful implications for both policy makers and financial practitioners in the energy sector.

Leveraging Qardhul Hasan Practices from Zakat Funds for Sustainable Development: a Maqasid Sharia Perspective and Its Contribution to SDGs in Malaysia

Objective: This study aims to examine the implementation of qardhul hasan from zakat funds within the framework of maqasid sharia, focusing on its potential contributions to sustainable development, particularly in relation to the achievement of the Sustainable Development Goals (SDGs). Specifically, the study explores how zakat funds, when used for qardhul hasan, can contribute to SDGs related to poverty alleviation, economic inclusion, and social justice in Malaysia. Theoretical Framework: This research applies Islamic finance theory, particularly maqasid sharia, in the context of zakat fund distribution. Maqasid sharia emphasizes the protection and welfare of the community, aligning with the principles of sustainable development. The theory of sustainable development is linked to Islamic financial practices, particularly in how qardhul hasan can serve as a tool for economic empowerment and social equity. Method: A qualitative research approach is employed in this study, utilizing content analysis and semi-structured interviews. Data are collected from various sources, including academic journals, articles, and reports on zakat fund practices in Malaysia. The study evaluates the governance of zakat funds, specifically focusing on the implementation of qardhul hasan as a sustainable financial instrument. Results and Discussion: The study finds that qardhul hasan, when implemented effectively with maqasid sharia principles, can play a crucial role in promoting sustainable development by contributing to poverty alleviation, economic empowerment, and social inclusion. However, challenges remain in the implementation process, including the lack of standardized guidelines for zakat fund governance and the need for greater awareness among stakeholders regarding the potential of qardhul hasan. The study emphasizes the importance of clear governance frameworks and strong partnerships between the government, religious institutions, and the community in ensuring the effectiveness of zakat fund distribution. Research Implications: This research offers practical recommendations for policy makers and practitioners in Islamic finance to enhance the governance of zakat funds. It suggests improving transparency, establishing clear parameters for qardhul hasan, and raising awareness about the role of zakat in achieving SDGs. Collaboration among various stakeholders is essential for maximizing the social and economic benefits of zakat funds. Originality/Value: The originality of this study lies in its exploration of qardhul hasan as a tool for sustainable development, offering insights into its role in advancing the SDGs, particularly in the Malaysian context. This study contributes to the literature on Islamic finance and sustainable development, providing a model for integrating maqasid sharia into zakat fund governance to support sustainable and inclusive societies.

Pendampingan Penyusunan Laporan Keuangan bagi UMKM

This community service aims to strengthen the empowerment of Micro, Small, and Medium Enterprises (MSMEs) in South Sulawesi through assistance in preparing financial statements. Through a series of workshops, trainings, and individual mentoring sessions, we provide an in-depth understanding of the significance of financial statements and equip MSME owners with practical skills to compile, read, and analyze their financial statements. The mentoring method involves organizing interactive workshops led by experienced financial practitioners and individual mentoring sessions tailored to the needs of each MSME. In addition, we provide online resources as a learning platform that MSMEs can access flexibly, including guides, financial statement templates, and relevant case studies. Outcomes of the service include improved MSMEs' understanding of financial reporting, significant financial empowerment, and increased access to external financial support. MSMEs that participated in the program were able to produce clear financial statements, providing a basis for smarter decision-making and increasing their chances of securing financial support from financial institutions. With a focus on the context of South Sulawesi, this service contributes to the strengthening of the MSME sector in the region, supports local economic growth, and positively impacts the financial sustainability of MSMEs. Through assistance in preparing financial statements, it is hoped that MSMEs in South Sulawesi can develop sustainably and contribute optimally to regional economic development

The Transformation of Interest Prohibition

This study aimed to explore the transformation of the concept of riba (usury) within contemporary financial systems, specifically how Islamic jurisprudence has adapted to modern economic practices. The analysis also aimed to understand the evolving interpretation of riba and its implications for Islamic and global financial markets. A comparative analysis was adopted, integrating qualitative methods such as document analysis and a case study of financial systems. This study examined historical and modern interpretations of riba, with a specific focus on the transition from traditional gold and silver standards to fiat money systems. The results showed that the adaptation of riba in modern financial systems required significant transformation, particularly in response to the transition from commodity-based to fiat money. The analysis identified key trends in how riba was reinterpreted within the context of contemporary financial systems as well as discussed the challenges and solutions proposed by Islamic scholars. Additionally, it contributed to the existing body of knowledge by providing a nuanced analysis of how the prohibition of riba was applied in contemporary financial systems, connecting historical perspectives with modern practices. The analysis provided new insights into the dynamic relationship between traditional Islamic financial principles and the evolving global financial landscape. It also showed the importance of continuous investigation of riba in the context of contemporary financial systems. This study suggested that ongoing discourse among Islamic financial practitioners and scholars was crucial for developing solutions to support both traditional principles and contemporary financial realities.

Implementation of Musyarakah Agreement In Profit Sharing Cooperation of Investor In Syariah Finance Business

In the era of global economic development, the Islamic financial system has emerged as an alternative for various groups who wish to conduct economic activities in accordance with Islamic principles. This study aims to explore how musyarakah contracts are implemented in investment partnerships between investors and businesses in the Islamic financial sector and identify the factors that influence their successful implementation. This research uses a descriptive qualitative approach to understand and analyze the implementation of musyarakah contracts in profit-sharing partnerships in the Islamic financial sector. Primary data was obtained through semi-structured interviews with Islamic business actors, investors, and Islamic finance practitioners. Secondary data were obtained from relevant literature, such as scientific journals, books, and annual reports of Islamic financial institutions. The results show that musyarakah contracts based on the principles of profit sharing and risk sharing provide benefits for both parties. Investors can actively participate in business management with better transparency, while business actors get additional capital to support business expansion. The implementation of musyarakah contracts has shown positive developments in the Islamic financial sector, especially in Indonesia, where regulations and policies have supported the development of sharia-based businesses. However, there are still challenges related to investors' and businesses' understanding of the agreement mechanism, as well as the need for strict supervision to ensure compliance with sharia principles. This research is expected to contribute to the further development of musyarakah contracts in the Islamic finance sector and strengthen the position of Islamic finance in the global market.

Impact of firm ESG performance on cost of debt: insights from the Chinese Bond Market

ABSTRACT This study investigates the relationship between environmental, social, and governance (ESG) performance and cost of debt in Chinese corporate bond market from 2010 to 2019. The research aims to address the increasing importance of ESG considerations in financial decision-making. The study reveals the significance of specific ESG factors, such as environmental innovation, CSR committees, in influencing bond spreads. To enhance robustness, the robust tests including PSM, lagged variables, 2SLS, GMM, reinforcing the comprehensive nature of its findings. These results underscore the significance of ESG considerations in debt pricing, contributes valuable insights to academia and practitioners in sustainable finance.

Risk Management As A Determinant Of Indonesian Banking Financial Performance: A Systematic Literature Approach

This study aims to understand how risk management affects financial performance in the Indonesian banking sector. In a business environment full of uncertainty, especially in the banking sector, risk management is key to ensuring financial stability. Systematic Literature This review (SLR) analyzes the findings of articles published between 2016 and 2022, focusing on the main risks faced by banks: credit risk, market risk, liquidity risk, and operational risk. The selected articles were obtained from leading journal sources in the fields of economics and business. The literature selection process includes the stages of identification, screening, and thematic analysis to identify trends and correlations between risk management and financial performance indicators such as Return on Assets (ROA) and Return on Equity (ROE). The results of the study indicate that credit risk and operational risk have the most significant impact on financial performance, while market and liquidity risks show varying effects depending on the market situation and internal conditions of the bank. These findings underline the importance of a proactive approach to risk management, including the implementation of integrated risk mitigation policies and the use of effective internal controls. Thus, risk management not only serves as a safeguard against potential losses but also as a support for business sustainability. This study recommends further research to explore new risks such as cyber threats and regulatory changes, which are increasingly relevant in the context of the modern banking industry. These results are expected to provide insights for financial practitioners and banking leaders in improving the resilience and financial performance of their companies.

The Role of Sharia-Compliant Financial Institutions in Promoting Economic Stability: Insights from Recent Scholarly Contributions

This research examines the role of Islamic financial institutions in promoting economic stability through a literature study of recent scholarly contributions. Islamic financial institutions are seen as alternative financial instruments that operate under Islamic principles, which prohibit usury, excessive speculation, and non-transparent activities. This research aims to understand the mechanisms used by Islamic financial institutions in creating economic stability and evaluate the latest empirical evidence supporting such contributions. The research method used is a literature study with a qualitative approach, where various journals and research reports on Islamic finance, economic stability, and monetary policy are reviewed and analysed. The results show that Islamic financial institutions play an important role in economic stability through asset-based financing, portfolio diversification, as well as the application of risk management in accordance with Islamic principles. This research contributes to providing policy makers, academics, and financial practitioners with a deeper understanding of the potential of Islamic financial institutions as instruments that can strengthen economic stability.

On the Distribution of the Mixed-Lognormal-Weibull Option Pricing Model

This paper intends to test whether the Mixed-Lognormal-Weibull Distribution (MLWD) option pricing model comes from the same distribution and whether the model is a good fit in Black-Scholes option pricing model. The data for this study were obtained from Australian Clearing House of Australian Securities Exchange (ASX) which consist of 50 enlisted stock as products of monthly market summary for long term options collected from January, 3rd 2017 to December, 31st 2017, comprising 720 trading days arranged in accordance to 25, 27, 28, 29 and 30 maturity days. Maximum Likelihood Estimate was used to obtain the parameters of both the lognormal and Weibull distributions which were applied in Black-Scholes model. The data were test Wilcoxon Rank Sum test since the mixture model became distribution and Chi-square goodness-of-fit test for the model fit, and the result shows that the mixture model does not follow any of the lognormal or Weibull distributions. The result also shows that the mixture model is a good fit in Black-Scholes option pricing model with the P-value>0.05 when they are shorter maturity days with small sample sizes than longer maturity days with larger sample sizes. Hence, the model is recommended to be used for financial practitioners who are interested in modeling option pricing.

Systemic Risks in the Derivatives Market: Origins, Impacts, and Mitigation Strategies

Derivative markets play an indispensable role in the contemporary financial system. The global financial markets have been repeatedly riddled with turbulence instigated by derivative trading in recent years, underscoring the urgency and necessity for in-depth study in this field. The subject matter of this paper is to delve into systemic risk in the derivative markets, including its genesis, impact, and mitigation strategies. This paper aims to proffer valuable insights and recommendations to policymakers and financial practitioners through comprehensive analysis. To achieve this objective, this study utilizes research methodologies such as literature review, analysis of historical cases, and empirical analysis. The findings suggest that the systemic risk in the derivative markets primarily stems from high leverage operations, market information asymmetry, and complex financial product structures. These risks became particularly prominent during the financial crisis, leading to an upsurge in market volatility, liquidity crises, and a domino collapse of financial institutions. Based on these findings, the paper proposes a gamut of strategies to mitigate systemic risk, including enhancing market transparency, optimizing risk models, augmenting capital requirements, and fostering international regulatory cooperation. Additionally, technological innovations such as blockchain and big data analysis are considered to hold significant potential in enhancing market transparency and improving the accuracy of risk prediction.

Application and Empirical Analysis of Random Volatility Model in Financial Markets

The Stochastic Volatility Model (SVM), as a key innovation in modern financial engineering, has profoundly changed our understanding of the volatility characteristics of financial markets. This model not only considers the volatility of asset prices as a time-varying random variable, but also simulates this uncertainty by introducing stochastic processes such as Brownian motion or more complex stochastic differential equations, thereby achieving a precise characterization of the dynamic characteristics of volatility. Compared to traditional fixed or historical average volatility assumptions, SVM can capture sudden changes in market sentiment, the impact of news events, and the influence of macroeconomic factors on volatility, providing investors with a more realistic perspective on the market. This article not only deeply analyzes the theoretical basis and construction methods of SVM, but also verifies its effectiveness and applicability in different financial market environments through empirical analysis and actual market data, providing valuable references and insights for financial practitioners, scholars, and policy makers.

Pension funds in Colombia and implications: A bibliometric analysis from Scopus

This study delves into the dynamic landscape of pension funds in Colombia, examining both its current research status and practical implications. Understanding the state of pension systems is crucial for individuals' financial security and a country's overall economic stability, especially given factors such as an aging population and evolving socio-economic dynamics. By comprehensively analyzing scholarly publications on Colombian pension funds using the Scopus database, this research sheds light on key trends and contributors shaping policy formulation and financial planning. The analysis covers a period from 1987 to 2023, identifying 71 relevant articles through keyword searches and filters. Various metrics, including publication trends, citations, international collaboration, and authorship dynamics, were quantitatively assessed. The results reveal an annual growth rate of 5.37%, with research articles comprising 81.69%, review articles 7.04%, and other formats like books, book chapters, and conference papers making up 11.27% of the total documents. Notably, countries such as the UK, the USA, Spain, and Colombia emerge as key contributors to the literature. Among authors, Mesa-Lago, L., stands out as a significant figure, with one of the earliest publications on the topic. The findings underscore the growing importance of pension funds in Colombia, particularly in the context of fund performance research amid financial crises. The prevalence of international collaboration suggests a global interest in understanding and contributing to the development of Colombian pension systems. Furthermore, the study identifies research gaps, particularly in areas concerning the socio-economic impact of pension policies, providing a roadmap for future investigations. Policymakers, financial practitioners, and researchers can leverage these insights to inform strategic decision-making and address critical challenges in optimizing pension fund management in Colombia.

QRIS dalam Meningkatkan Kinerja Sistem Informasi Penerimaan Kas dan Dampaknya terhadap Rekonsiliasi Kas di Indonesia

QRIS (Quick Response Code Indonesian Standard) has become the national standard in digital payment transactions in Indonesia, offering convenience and efficiency in cash receipt processing. This system not only facilitates the transaction process for consumers but also has a significant impact on cash receipt information systems and cash reconciliation processes. A descriptive qualitative approach was used in this research to analyze the integration of QRIS with cash receipt information systems and its impact on the cash reconciliation process. Data were collected through literature reviews, interviews with financial practitioners, and transaction data analysis generated from the use of QRIS. The results of the research indicate that the use of QRIS significantly improves the performance of cash receipt information systems. QRIS allows transaction data to be sent simultaneously to the QRIS owner's bank and the cash receipt information system. This integration ensures that transaction data is recorded in real-time, which reduces errors in recording and accelerates the cash reconciliation process. The cash receipt process becomes more structured and transparent, while cash reconciliation is carried out more efficiently and accurately.

Enhancing Financial Decision-Making: Real Options Complementing the Net Present Value Technique in the Financial Services Sector

This study investigates the effectiveness of integrating real options with the Net Present Value (NPV) technique in the context of the financial services sector. The study aimed to assess how this approach enhances decision-making among financial practitioners. Using a quantitative research approach, data was collected via a questionnaire from 286 financial service participants with prior experience evaluating projects and making decisions. The results concluded that incorporating real options into traditional NPV analysis significantly improves decision-making, offering decision-makers greater flexibility and efficiency. The results suggest that when faced with hypothetical projects where initial NPV turns negative with the adoption of real options, decision-makers are more likely to make rational choices that optimize the outcome. Based on the findings, adopting a combined NPV and real options strategy for practitioners in the financial services sector is recommended to make more informed and flexible investment decisions, which would ultimately benefit their organizations and stakeholders. Future research should explore the qualitative aspects of decision-making and expand the analysis to different nations and industries.

Enhanced Foreign Exchange Volatility Forecasting Using Ceemdan with Optuna-Optimized Ensemble Deep Learning Model

Foreign Exchange (FX) is the largest financial market in the world, with a daily trading volume that significantly exceeds that of stock and futures markets. The prediction of FX volatility is a critical financial concern that has garnered significant attention from researchers and practitioners due to its far-reaching implications in the financial markets. This paper presents a novel hybrid ensemble forecasting model integrating a decomposition strategy and three deep learning (DL) models: Long Short-Term Memory (LSTM), Bidirectional LSTM (BiLSTM), and Convolutional Neural Network (CNN). This combination addresses individual models' limitations and further improves the accuracy and stability of FX volatility forecasting. The proposed approach utilizes the CEEMDAN technique to decompose volatility into multiple distinct intrinsic mode functions (IMFs) and merges these IMFs with GARCH and EGARCH volatilities to form the input dataset for the DL models. In addition, we employed an attention mechanism to improve the effectiveness of the DL techniques. Furthermore, the hyperparameters for the DL models are optimized using the Optuna algorithm. Finally, a hybrid ensemble model for forecasting exchange rate volatility is developed by combining the predictions of three distinct DL models. The proposed approach is evaluated against various benchmark models using evaluation measures such as MSE, MAE, HMSE, HMAE, RMSE, Q-LIKE, and the model confidence set (MCS) approach. The results demonstrate that our proposed approach provides accurate and reliable forecasts of FX volatility under different forecasting regimes, making it a valuable tool for financial practitioners and researchers.

Legal analysis of derivative transactions in islamic economics

The legal position regarding derivative transactions in Islamic economic practices has attracted significant attention from Islamic financial institutions such as AAOIFI and DSN-MUI. Derivative instruments can be incorporated into the sharia framework as long as they fulfil the core principles of sharia such as being free from elements of riba (interest), gharar (uncertainty), and maysir (gambling). These bodies have issued guidelines and fatwas such as the DSN-MUI fatwa No. 96/DSN-MUI/IV/2015, which permits the use of derivatives for hedging purposes under a number of strict requirements that ensure transparency and fairness and emphasizes that transactions are based on real needs and not speculation. However, implementing these legal guidelines on the ground faces various challenges. Key challenges include correctly applying derivative instruments so that they do not turn into prohibited tools of malicious speculation. Strict supervision and audit systems are needed to ensure compliance with Shariah principles on an ongoing basis, as well as ensuring transparency in the execution of transactions. In addition, in-depth training and education for Islamic finance practitioners is essential to support proper and effective implementation. Thus, the legal position regarding derivative transactions in the Islamic economy is clear and feasible to implement with strict supervision and supported by continuing education.

Stock Market Prediction in Nepali Stock Market using Machine Learning Model

The stock market, a key driver of the global economy, presents a formidable challenge for accurate prediction due to its intricate, chaotic, and dynamic nature. This study explores machine learning approaches, specifically comparing three prediction models—Back Propagation Neural Network (BPNN), Long Short-Term Memory (LSTM), and Gated Recurrent Unit (GRU). The analysis incorporates historical stock trading data, including open, high, low, and close prices, and technical analysis indicators such as moving average, Relative Strength Index (RSI), Moving Average Convergence Divergence (MACD), and Commodity Channel Index (CCI) so on. The evaluation focuses on the performance of these models in predicting future trends in stock prices, utilizing data from the Nepal Stock market spanning from 2013 to 2023. The selected stocks for analysis include two stock NIC Asia Bank Limited and, NMB Bank Limited, two index NEPSE and Hydropower index. Through rigorous assessment, it is determined that LSTM demonstrates superior overall performance compared to GRU and BPNN. This research contributes valuable insights into the effectiveness of machine learning models in forecasting stock market trends, with implications for investors and financial practitioners.

The Effect of Profitability, Liquidity and Company Size on Capital Structure in Companies Listed on the Indonesian Stock Exchange

This study investigates the effect of profitability, liquidity, and firm size on the capital structure of firms listed on the Indonesia Stock Exchange (IDX). Using data from manufacturing firms, the study found that profitability and liquidity have a negative and significant influence on capital structure decisions, with more profitable firms tending to rely on less debt and more internal sources of funds. However, firm size does not consistently have a significant negative impact on capital structure, suggesting that external factors such as capital market conditions and economic policies have a more dominant role in determining a firm's capital structure. These results provide important insights for financial practitioners in designing appropriate funding strategies to maximise firm value and effectively manage financial risk in the Indonesian capital market.

Inklusi Keuangan dan Pemberdayaan Ekonomi: Evaluasi Efektivitas Produk Keuangan Syariah dalam Meningkatkan Akses Keuangan bagi Masyarakat Marginal

Financial inclusion and economic empowerment have become major focal points in efforts to improve financial access for marginalized communities. This is particularly crucial in the current global context where economic inequality and access to financial services remain serious issues. This article aims to evaluate the role of Shariah-compliant financial products in supporting financial inclusion and economic empowerment among marginalized groups. The literature review method used in this article provides a strong foundation for collecting and analyzing various related articles, including policy reviews and market analyses. Through in-depth review, this article illustrates that Shariah-compliant financial products have significant potential to provide more inclusive, transparent, and sustainable solutions in enhancing financial access for marginalized communities. Key factors such as trust, understanding of Shariah principles, and supportive regulations are also emphasized as essential elements in strengthening the effectiveness of these financial products. Additionally, the implications of the findings in this article are crucial in providing guidance for stakeholders, regulators, and financial practitioners. By understanding the potential and advantages of Shariah-compliant financial products, stakeholders can develop more effective strategies to improve financial inclusion and economic empowerment among marginalized communities. Thus, this article not only provides insights but also offers a clear direction for further steps in strengthening financial access for all layers of society, while promoting sustainable and inclusive economic development.