Finance and Financial Management Commons^™

Examining Performance Disparities In Palestinian Banks: A Comparative Analysis Of Islamic And Conventional Banks, Ra'fat Al-Jallad, Luai Antari

An-Najah University Journal for Research - B (Humanities)

The study investigates the performance differentials between Islamic and conventional banks operating in Palestine across a number of dimensions. Research Problem: The study addresses the lack of comparative analysis between Islamic and conventional banks in Palestine, specifically examining performance disparities using the CAMEL approach. This is critical due to the recent trend of conventional banks acquiring Islamic banks, raising questions about the underlying performance differences. Purpose: The main purpose of this study is to analyze and compare the performance of Islamic and conventional banks in Palestine from 2011 to 2021, focusing on key performance dimensions such as capital adequacy, asset …

College Students’ Financial Literacy At An Eastern Kentucky Regional University, Hannah Barrett, Steve S. Chen, Christy L. Trent

Atlantic Marketing Journal

Financial literacy is essential knowledge for recent college graduates to be able to manage a stable job, career, and personal wealth. This study examined the financial literacy of 228 college students (49.8% males; 50.2% females) at a regional public university in Eastern Kentucky. The participants were randomly invited to complete a 22-item online financial literacy survey, which was created based on the work of Cude et al. (2006). The survey contents included five demographic questions and 17 five-point Likert scales (1= strongly agree/ always, 5= strongly disagree/ never) to rate participants’ knowledge on investing, saving, budgeting, and credit. The data …

The Impact Of Rising Interest Rates, Bank Deposit Betas, And Credit Risk, Abby Craig, Jarrett Grose, Justin Tersoglio, Noah Vanhoy, Brooke Vivenzio

James Madison Undergraduate Research Journal (JMURJ)

Inflation of the U.S. dollar drove the Federal Reserve Board to enact four interest rate hikes of 0.75% and additional smaller hikes between March 2022 and April 2023. This paper examines how interest rate hikes affect bank deposit betas and credit risk for community banks, hot money banks, and alternative lending institutions based on data from March 2022 to April 2023. After analyzing data from the Federal Reserve Economic Database, this research found that bank deposit betas increase as interest rates rise, that community banks’ betas increase at a slower rate than hot money banks’ betas, and that the level …

An Analysis Of Drivers Of The Federal Funds Rate, Stephen Johnson, Neha Dixit, Martin Selzer Ph.D.

SMU Data Science Review

The Federal Funds Rate (FFR) is a tool used by the Federal Reserve to set monetary policy on borrowing costs for consumers and businesses. The Fed’s primary motivation with the FFR is to control macroeconomic factors such as inflation and unemployment. Over time, policy stances for the Fed have varied in response to events such as the Great Recession, and more recently the COVID-19 pandemic. In light of the Fed’s actions following these events, there is intensified debate over which macroeconomic factors should be prioritized, and what magnitude of change is sufficient to warrant action. Additionally, when action is taken …

Pooling And Winsorizing Machine Learning Forecasts To Predict Stock Returns With High-Dimensional Data, Erik Mekelburg, Jack Strauss

Finance: Faculty Scholarship

We evaluate US market return predictability using a novel data set of several hundred ag- gregated firm-level characteristics. We apply LASSO, Elastic Net, Random Forest, Neural Net, Extreme Gradient Boosting, and Light Gradient Boosting Machine methods and find these models experience large prediction errors that lead to forecast failures. However, winsorizing and pooling machine learning model forecasts provides consistent out-of-sample predictability. To assess robustness, we apply machine learning methods to high-dimensional data for Canada, China, Germany and the UK as well as the Goyal-Welch data. All machine learning models we consider, except for the ensemble pooled methods, fail to significantly …

Notes And Thoughts On Retrieving Historical Members Of The S&P 500 From Wrds, Lip Hwe Tee

Research Collection Library

Retrieving all historical members or constituents of the S&P 500 can be done using Python coding on the CRSP dataset through an API connection with WRDS (Wharton Research Data Services (WRDS), n.d. -f; WRDS, n.d. -e).

Machine Learning As Arbitrage: Can Economics Help Explain Ai?, Huahao Lu, Matthew Spiegel, Hong Zhang

Sim Kee Boon Institute for Financial Economics

Machine learning algorithms have shown to be remarkably successful tools for predicting asset returns. However, the underlying economic mechanisms behind their performance remain unclear. This paper proposes a model-based dynamic arbitrage trading strategy that combines economic and statistical nonstationarity to demystify this black box. In predicting stock returns based on 153 firm characteristics (anomalies), our strategy ranks anomalies similarly to neural networks in the cross-section. Overall, it accounts for approximately 87.9 bps monthly alphas of the high-minus-low portfolios selected by neural networks in the time series. When unpublished anomalies and microcap stocks are excluded from trading, this strategy can fully …

Research On The Influence Mechanism Of Value Co-Creation On Enterprise Performance: Empirical Evidence From China's Motorsport Culture Industry, Xiaodong Weng

Dissertations and Theses Collection (Open Access)

We are in an era of digital economy and enterprise change management. The application of digital technologies such as Artificial Intelligence (AI), Blockchain, Cloud Computing, and Big Data (collectively known as ABCD technologies) has increased the competition in the value chain and value network between customers and enterprises. Users can now intervene in product design, transaction, and feedback before, during, and after the process, breaking through the limitations of time and space. They leverage their low-cost advantage to draw attention, shifting from a traditional, unidirectional supply logic to a value co-creation logic. This influences both enterprises and customers to produce …

Advancing Sustainable Investing: A Deep Learning Model For Multi-Source Stock Prediction, Hongxuan Yu, Tingting Zhang, Murat Kizildag

Journal of Global Business Insights

The burgeoning role of the stock market within the national economy elevates the importance of precise stock price analysis and prediction, a field that has garnered substantial interest in academic research. Stock price fluctuations, influenced by many factors, including company fundamentals, market sentiment, capital flows, industry news, and macroeconomic policies, present a highly dynamic and complex challenge for predictive modeling. Addressing this challenge, our study introduces an innovative method that capitalizes on the synthesis of news text and stock price data for forecasting market movements. We employ GloVe embeddings to capture semantic nuances from news text and integrate them with …

Millennials’ Perception Towards Adaption And Intention Of M-Banking: Experience From A Developing Country, Noman Hasan, Md. Shahed Mahmud, Abdul Gaffar Khan, Reshma Pervin Lima, Shiblu Miah

Journal of Global Business Insights

In recent years, m-banking has been developed rapidly around the world. The research aims to measure millennials’ perception towards adaption and intention of m-banking from a developing country’s perspective. A PLS-SEM modeling approach was performed to test the hypothetical model. The empirical results reveal that perceived ease of use, perceived security and privacy, and perceived cost significantly affect the millennials’ attitude to adopt m-banking. In contrast, perceived usefulness and perceived self-efficacy have an insignificant effect. Furthermore, attitude towards adopting m-banking significantly impacts adoption and intention among millennials. Practical and theoretical implications have been identified based on the study results.

Improving Volatility Forecasting: A Study Through Hybrid Deep Learning Methods With Wgan, Adel Hassan A. Gadhi, Shelton Peiris, David E. Allen

Research outputs 2022 to 2026

This paper examines the predictive ability of volatility in time series and investigates the effect of tradition learning methods blending with the Wasserstein generative adversarial network with gradient penalty (WGAN-GP). Using Brent crude oil returns price volatility and environmental temperature for the city of Sydney in Australia, we have shown that the corresponding forecasts have improved when combined with WGAN-GP models (i.e., ANN-(WGAN-GP), LSTM-ANN-(WGAN-GP) and BLSTM-ANN (WGAN-GP)). As a result, we conclude that incorporating with WGAN-GP will’ significantly improve the capabilities of volatility forecasting in standard econometric models and deep learning techniques.

Tail Risk Network Analysis Of Asian Banks, Thach N. Pham, Robert Powell, Deepa Bannigidadmath

Research outputs 2022 to 2026

This study aims to investigate the tail risk dependence of individual banks in Asian emerging markets. Using value at risk and conditional value at risk to measure tail risk and employing the least absolute shrinkage and selection operator regression to build the network, this study analysed interconnectedness at three levels: system-wide, country level and individual bank level. This study yields three key findings. First, banks in Asian emerging markets have a notably high tail risk network, particularly during more extreme market conditions. Second, the smaller and more interconnected banks are the most systemically important in the region, rather than the …

Essays On Corporate Finance, Su Hee Yun

Dissertations and Theses Collection (Open Access)

Chapter 1. The impact of ESG disasters on Green and Brown firms

I investigate the effect of a firm’s prior ESG reputation on the market impact of ESG incidents. I find that firms with a better ESG reputation, i.e., higher ESG ratings, experience less negative stock-market reactions and analysts' forecast revisions compared to firms with a poorer ESG reputation. But managers of Greener firms, when producing earnings guidance, do not forecast a lower impact of these incidents on future earnings. Similarly, actual decreases in future earnings following these incidents are not significantly different between Green and Brown firms. Altogether, the …

The Impact Of Instrumental Attribution In Ai-Enabled Monitoring On Counterproductive Work Behavior, Qiang Zhang

Dissertations and Theses Collection (Open Access)

AI-enabled monitoring tools are theoretically expected to suppress unethical employee behavior. However, in practice, employees may perceive such monitoring as being driven by leaders' instrumental motives, primarily focused on personal performance evaluation and self-interest. This perception can foster feelings of job insecurity and moral disengagement, ultimately leading to counterproductive work behavior (CWB), which includes unethical employee behavior and turnover. These outcomes may undermine the intended effectiveness of AI-enabled monitoring tools. This study aims to explore the impact of Instrumental Attribution in AIenabled Monitoring (IAAIM) on CWB, specifically focusing on unethical employee behavior and turnover, through both theoretical and empirical lenses. …

Low/No-Code And Traditional Code Integration In Digital Banking, Kim Siang Yeo, Alan @ Ali Madjelisi Megargel

Research Collection School Of Computing and Information Systems

This paper seeks to combine the merits of Low/No-Code Programming (LNCP) with Traditional Programming (TP) systems to achieve true “agility” when creating banking infrastructure. While it is easy to fall prey to Shiny Object Syndrome in today’s dynamic and fast-paced banking technology world, it is not easy to pick out the right technology for today and tomorrow’s financial industry. Instead, LNCPs allow us to hedge all bets by equally lowering the technical entry barriers for each technology. The added integration of TP, when needed, also rounds out the faults related to sole LNCP use and provides any bank with a …

The Downstream Impact Of Upstream Tariffs: Evidence From Investment Decisions In Supply Chains, Thorsten Martin, Clemens A. Otto

Research Collection Lee Kong Chian School Of Business

We study how US manufacturing firms' investment responds to tariff reductions in supplier industries. Our estimates, based on tariff reductions following multinational trade agreements, suggest that a hypothetical 10% reduction of all upstream tariffs would increase downstream investment by 4% to 6%. This estimate is not explained by decreasing uncertainty and stems from tariff reductions for homogeneous and low-R\&D inputs, consistent with the investment response resulting from cost reductions rather than superior foreign technology embodied in imported inputs. Evidence from an instrumental variable estimation using the sudden increase in Chinese import penetration suggests that import competition also increases downstream investment.

Cash Holding And Corporate Governance On Company Financial Performance: Case Study Of Construction Infrastructure Project Supporting Industries On The Indonesian Stock Exchange, Mariana Ing Malelak, Zeplin Jiwa Husada Tarigan, Sautma Ronni Basana, Ferry Jie

Research outputs 2022 to 2026

The Indonesian government currently focuses on high infrastructure development to prepare for connectivity between one city and another. The massive construction of the new government capital is also called the archipelago's capital. This condition impacts companies supporting construction projects, which are growing rapidly. This growth is supported by corporate governance and the cash-holding industry, which supports infrastructure projects for the company's financial performance. This research aims to determine the role of cash holding and corporate governance (board skill, independent director, managerial ownership) on the financial performance of infrastructure-supporting manufacturing companies in Indonesia. The sample used in this research was 83 …

Attracting Foreign Direct Investment (Fdi) In Madani Economy: What Factors Matter?, Yi-Shan Chong, Chee-Lip Tee

International Journal of Management, Finance and Accounting

Foreign Direct Investment (FDI) has long been acknowledged as a vital driver of economic development, and Southeast Asia stands out as a prime destination for such investments. However, Malaysia's share of FDI in the region has been diminishing, signalling a loss of competitiveness. In response, the Malaysian government has prioritized enhancing competitive strength in its recent development framework, Madani Economy. This study aims to shed light on the factors that require greater attention to achieve these objectives. Utilizing the Autoregressive Distributed Lag (ARDL) approach and monthly data spanning from 2010 to 2019, the findings underscore the importance of growing market …

A Study On The Impact Of Financial Incentives And Work Environment On Employee Motivation To Work: A Case Study Of Employees Of Paradise Estate Management Company, Okoye Shedrach Obumneme, Farha Ghapar

International Journal of Management, Finance and Accounting

The study aims to investigate the impact of financial incentives and workplace environment on employee work motivation. Individually, the study examines the impact of work allowances, employee wages, organisational culture, and internal communication on employee motivation to work in an organisation. The research employed a survey research design. The population of the study focused on the employees of Paradise Estate Management Company. A total of 79 respondents were selected from a pool of 120 employees in the organisation. The questionnaires were administered and distributed to respondents through Google Form. Multiple regression analysis was adopted to test the different hypotheses. The …

Cooperative Preschool Education In Ethnic China: Ulanqab Case Study, Yu Dong, Siow-Hooi Tan, Hway-Boon Ong

International Journal of Management, Finance and Accounting

The integrated education of family, kindergarten, and community is crucial for children’s development. However, in China’s ethnic regions, preschool education faces significant shortcomings, with limited community involvement and consideration of ethnic characteristics. This study aims to address these gaps by proposing a conceptual framework tailored for ethnic areas, focusing on the Ulanqab region. Drawing on domestic and international research, we develop a model comprising family, preschool, and community inputs, emphasising the importance of community participation. The model includes educational inputs, educational processes, and target outcomes, with the goal of improving preschool education quality. Through this research, we seek to understand …