Finance and Financial Management Commons^™

Thoughts On Reform Of Fiscal S&T System Under Public Finance System, Wei Xue, Xuan Wang, Yunqiqige Wu

Bulletin of Chinese Academy of Sciences (Chinese Version)

Finance is the foundation and important pillar of national governance, a perfect financial science and technology system is of great significance for promoting scientific and technological progress, optimizing financial science and technology management, and enhancing the effectiveness of financial science and technology funds. This study discusses the main features of the financial science and technology system under the framework of public finance, summarizes the relevant reform achievements in China in recent years, identifies the main problems, clarifies the practices of innovative countries such as the United States, Germany, Britain, and Japan, and puts forward policy suggestions for further deepening the …

Exploring Factors That Influence Artificial Intelligence Adoption In Banks And Credit Unions, Vijaya S. Tumma

USF Tampa Graduate Theses and Dissertations

The importance of Artificial Intelligence (AI) is exploding in the banking sector, fueled by enhanced productivity, improved efficiencies, and personalized services to the consumers. For credit unions, the adoption of AI technologies presents opportunities and challenges. This research explores the factors influencing AI adoption in the banking sector through the lens of Unified Theory of Acceptance and Use of Technology (UTAUT) framework. This study aims to explore the influence of key aspects of UTAUT model, Performance Expectancy (PE), Effort Expectancy (EE), Social Influence (SI), and Facilitating Conditions (FC) on the intention of AI adoption among credit unions, banks, and their …

Financial Analysis, Tina N. Barrett

Cornhusker Economics

The investment in a financial analysis can seem like a painful task of gathering information but the information it provides gives you invaluable information about your operation, especially when you don’t want to see it. I was once told a producer didn’t want to do the analysis anymore because the information made it hard to sleep at night. While not knowing maybe helped him sleep then, the problems that were being highlighted by the analysis didn’t go away and eventually caught up to him.

Comparative Analysis Of Univariate And Deep Learning Models For Stock Market Prediction In Frontier Markets: A Case Study Of Pakistan, Bangladesh, And Sri Lanka, Rabia Sabri, Sobia Iqbal

Business Review

This research is focused on the stock exchanges of Sri Lanka, Pakistan, and Bangladesh due to their significant presence in the Asian region and the unique challenges, opportunities, and presence in these frontier markets. The study assesses both traditional stationary models, Autoregressive Integrated Moving Average (ARIMA) and Theta traditional stationary models, with the contemporary deep learning models Long Short-Term Memory (LSTM) with 1D Convolutional Neural Network (CNN) support. The study covers the sample period of historical data from 2020–2023 to include the in and out of sample forecasting of 2024–2025. The time series comprises linear and nonlinear datasets to capture …

Eurobond Performance In Emerging Markets: Do Economic Freedom, Contagion Effects, And Strategic International Relations Matter?, Nourhan El Rouby

Theses and Dissertations

This paper studies the factors moving the Eurobond prices and credit ratings issued by emerging markets. By observing a set of variables, including economic freedom, contagion effects and strategic international relations, the study was able to provide a thorough analysis of their impact on Eurobond performance. The research was able to identify significant determinants of Eurobond prices and credit ratings through utilizing panel data from 20 emerging markets over a period of April 2018 to September 2023 where we applied fixed effects linear regression and ordered logit models. The findings resulted that economic freedom, in specific enforcement of contracts, and …

The Influence Of News Media On Esg Ratings: Analyzing Media Sentiment Around Esg Rating Changes, David Beverly

Dissertations

This dissertation investigates the complex relationship between media sentiment and Environmental, Social, and Governance (ESG) ratings, a pressing issue highlighted by the lack of transparency in the adjustments to ratings from some agencies and not others. The research aims to empirically examine the extent to which news media narratives influence ESG scores and contribute to discrepancies among rating agencies. With ESG investing becoming increasingly significant, as evidenced by the rise in global assets under management in ESG funds, the accuracy and reliability of ESG scores are of increasing importance to investors, policymakers, and academics.

The study explores the potential of …

The Impact Of Cash Holding Decisions On Firm Performance In The It Industry, Jaeseong Lim, Bong Keun Jeong

Accounting

This study examines the relationship between corporate cash holdings and firm performance within the IT industry, which is characterized by intense competition and rapid technological advancements. We propose an integrated framework that combines principal component analysis (PCA), machine learning (ML) algorithms, and Shapley additive explanation (SHAP) values to estimate and interpret model outcomes. Based on 21,051 corporate financial statement data items from 2004 and 2023, the empirical evidence supports an inverted U-shaped relationship between cash holdings and profitability, suggesting that holding either too little or too much cash is suboptimal. Among the tested models, the random forest demonstrates the highest …

Road To Net Zero: Greenness Of Leadership In Energy And Environmental Design And California Green Building Standards Code In The Multifamily Sector, Jamie Jung, Michael Cusumano, Dongshin Kim, Abraham Park

Finance, Banking and Real Estate Faculty Publications

This study evaluates the effectiveness of Leadership in Energy and Environmental Design (LEED) and California Green Building Standards Code (CALGreen) sustainability programs in reducing greenhouse gas (GHG) emissions in multifamily buildings. We find that CALGreen effectively reduces GHG emissions by 7.2%–11.6%. However, among properties completed during the CALGreen period (on or after 2015), LEED-certified properties exhibit 14.1%–20.8% higher GHG emissions compared to non-LEED-certified buildings. We attribute this result to the emphasis on theoretical design versus actual energy performance of those programs. Furthermore, our research reveals that LEED-certified buildings completed before the implementation of CALGreen command a rent premium of 4.7%–5.4%. …

Lead-Lag And Volatility Point Change Estimations For Cryptocurrencies, Jules Clement Mba, Jenipher Mutale, Ehounou Serge Eloge Florentin Angaman

Journal of Banking and Financial Economics

This study investigates the lead-lag relationships and volatility dynamics among four major cryptocurrencies – Bitcoin, Ethereum, Solana, and Polygon – during the turbulent year of 2022. We address three primary research questions: (1) To what extent do lead-lag relationships exist among major cryptocurrencies, and how do they challenge or support the notion of market efficiency in the crypto space? (2) How do volatility change points in different cryptocurrencies relate to each other and to major market events? (3) How can the identification of lead‑lag relationships and volatility change points inform cryptocurrency investment strategies and risk management practices? Using a continuous-time …

A Method To Incorporate Transition Risk Stress Testing Into Probability Of Default (Pd) Models For Retail Portfolios, Aneta Ptak-Chmielewska, Paweł Kopciuszewski, Alvaro Fernandez Toledo

Journal of Banking and Financial Economics

Climate risk is one of the type of risks in a bank’s portfolio which is not fully recognized, and its impact on the future overall risk changes is hidden due to lack of sufficient knowledge at the moment. One of the most common data comes from Network for Greening the Financial System (NGFS) scenarios related to climate change (physical risk) and climate policy and technology trends (transition risk). In the paper we focused on the transition risk scenarios and their impact on the economy and in particular on credit risk. Our main goal was to check the tendency in the …

Fixed Income Fund Report, November 2024, Archway Investment Fund

Archway Investment Fund

No abstract provided.

The Effects Of Antitrust Laws On Horizontal Mergers: International Evidence, Chune Young Chung, Iftekhar Hasan, Jihoon Hwang, Incheol Kim

Finance Faculty Publications

This study examines how antitrust law adoptions affect horizontal merger and acquisition (M&A) outcomes. Using the staggered introduction of competition laws in 20 countries, we find antitrust regulation decreases acquirers’ five-day cumulative abnormal returns surrounding horizontal merger announcements. A decrease in deal value, target book assets, and industry peers' announcement returns are consistent with the market power hypothesis. Exploiting antitrust law adoptions addresses a downward bias to an estimated effect of antitrust enforcement (Baker (2003)). The potential bias from heterogeneous treatment effects does not nullify our results. Overall, antitrust policies seem to deter post-merger monopolistic gains, potentially improving customer welfare.

Equity Fund Monthly Report, November 2024, Archway Investment Fund

Archway Investment Fund

No abstract provided.

Applying Deep Learning To Detect Abnormal Event Log Traces: A Non-Rule-Based Framework, Yunsen Wang, Tiffany Chiu, Miklos A. Vasarhelyi

Department of Accounting and Finance Faculty Scholarship and Creative Works

Process mining is an efficient method that can analyze the full population of transactions using the event log of business processes. Conventional rule-based process mining techniques can detect anomalies; however, it tends to trigger a large number of false alarms. To improve the efficiency of anomaly detection using process mining, this study adopts a deep learning-based classification approach to detect anomalies in the traces of event logs. This approach contributes to the literature by proposing a non-rule-based process mining technique based on deep learning. Results demonstrate that the proposed non-rule-based process mining method can help auditors focus on transactional anomalies.

Improved Estimation Of The Correlation Matrix Using Reinforcement Learning And Text-Based Networks, Cheng Lu, Papa Momar Ndiaye, Majeed Simaan

Department of Accounting and Finance Faculty Scholarship and Creative Works

We propose a data-driven methodology to shrink the correlation matrix and, hence, the covariance matrix using reinforcement learning (RL). Our approach does not impose any assumptions on the stock returns and can be applied to any covariance matrix target. It focuses on the special case of the global minimum variance portfolio and investigates the economic value of our methodology by utilizing text-based networks (Hoberg and Phillips, 2016). The portfolio selection problem, hence, boils down to determining the optimal shrinkage policy using RL. The empirical analysis utilizes a large universe of stocks covering more than 400 assets and 20 years as …

Estimating Models For Engineering Costs On The State Highway Operation And Protection Program (Shopp) Portfolio Of Projects, Elhami Nasr, Tariq Shehab, Nigel Blampied, Vinit Kanani

Mineta Transportation Institute

The State Highway Operation and Protection Program (SHOPP) is crucial for maintaining California’s 15,000-mile state highway system, which includes projects like pavement rehabilitation, bridge repair, safety enhancements, and traffic management systems. Administered by Caltrans, SHOPP aims to preserve highway efficiency and safety, supporting economic growth and public safety. This research aimed to develop robust cost-estimating models to improve budgeting and financial planning, aiding Caltrans, the California Transportation Commission (CTC), and the Legislature. The research team collected and refined comprehensive data from Caltrans project expenditures from 1983 to 2021, ensuring a high-quality dataset. Subject matter experts validated the data, enhancing its …

Predictors Of Audit Quality: A Confirmatory Study, Joseph Philip Kambey, Williams Kwasi Peprah [email protected], Lenny Leorina Evinta, Cecilia Lelly Kewo

Faculty Publications

This study investigated the predictors of audit quality according to registered external auditors in Indonesia. Even though there are improvements in audit reports and practices, there is still some fraud and audit risk that affects the credibility of financial reports. This research is based on a random sample technique where 304 registered external auditors in Indonesia answered self-constructed research instruments and their validity was ascertained with exploratory factor analysis, where they resulted as good. The first-party distributed data were analyzed with multiple regression to determine the predictors of audit quality. The study revealed that internal controls, governance, and audit culture …

A Practical Guide To Driving Financial Inclusion Through Cbdcs, Heng Wang

Research Collection Yong Pung How School Of Law

Welcome back to our blog series exploring the potential that central bank digital currencies (CBDCs) hold to positively impact individuals that are currently unserved or underserved by financial systems globally. Together with Professor Wang, we first delved into the challenges and opportunities of driving financial inclusion, and how CBDCs could serve as an important mechanism in ensuring that no one is excluded from financial services – or our increasingly digital economies and societies. In our second blog we then examined how CBDCs can be intentionally designed to drive financial inclusion. In this third and final piece, Professor Wang offers a …

An Empirical Test Of Auction Efficiency: Evidence From Mbs Auctions Of The Federal Reserve, Pietro Bonadi, Ali Hortacsu, Zhaogang Song

Research Collection Lee Kong Chian School Of Business

PurposeWe estimate the marginal cost curve of each dealer in each auction, based on structural models of the multiunit discriminatory-price auction.Design/methodology/approachAuction theory has ambiguous implications regarding the relative performance of three formats of multiunit auctions: uniform-price, discriminatory-price and Vickrey auctions. We evaluate the performance of these three auction formats using bid-level data of the Federal Reserve’s purchase auctions of agency MBS from June 2014 through November 2014.FindingsOur results suggest that neither uniform-price nor Vickrey auctions outperform discriminatory-price auctions in terms of the total expenditure. However, Vickrey auctions outperform discriminatory-price auctions in terms of efficiency, with the efficiency gain around 0.74% …

Syariah Security Crowdfunding: A Risk Analysis For Alternative Funding Solution For Indonesian Small And Medium Enterprises, Mochammad Salman Alfarisi, Mulawarman Hannase

Journal Of Middle East and Islamic Studies

Micro, Small and Medium Enterprises (MSMEs) are currently a sector that plays an important role in increasing economic stability in Indonesia. However, one of the crucial obstacles related to the development of micro businesses is limited capital and low access to sources of capital. Sharia securities crowdfunding is a form of innovation in the field of financial technology that offers alternative solutions for MSME players in obtaining funding. However, sharia securities crowdfunding is not without risk analysis. Some of the other risks of crowdfunding are inadequate regulatory and regulatory frameworks, low public awareness and trust, and the risk of dehumanization …