Finance and Financial Management Commons^™

The Relationship Between Medical Equipment Management Outsourcing And Performance, Sheng Bian

Dissertations and Theses Collection (Open Access)

Medical equipment, as a core component of a hospital’s fixed assets, provides essential support and assurance for the hospital to deliver medical services and enhance competitiveness. The operation of public hospitals in China is a top priority for deepening medical reforms. As hospitals transition from focusing on revenue to centering on costs, comprehensive management of medical equipment becomes a critical aspect of hospital operation management. In the scenario of utilizing the management service outsourcing mode for comprehensive management of medical equipment, equipment performance naturally becomes a topic of special interest in the industry.

Given this, this study aims to investigate …

Research On The Influence Mechanism Of Digitalization Degree On Manufacturing Enterprise Performance, Dandan Wang

Dissertations and Theses Collection (Open Access)

The application of digital technologies has changed the operation model of traditional industries, and promoted the development of emerging industries. More and more manufacturing enterprises have started or completed digital transformation, and tried new ways of development.

With the advancement of digitalization, the influence of the degree of digitalization on high-quality economic development has attracted great attention from scholars at home and abroad. Although significant resources are put into digital transformation, which is deemed as a strategic core, the specific influence paths of the degree of digitalization on enterprise performance have not yet been fully explored. In the digital era, …

Efficiency And Sustainability Of Bond Market: Evidence From Aftermarket Trading Of Us Corporate Bond Offerings, Lisa (Zongfei) Yang, Choo Yong, Jeremy Goh

Research Collection Lee Kong Chian School Of Business

We find that for bond offerings that are non-self-marketed, there is a significantly larger proportion of institutional-sized sell trades than buy. In stark contrast, for self-marketed offerings by underwriters, immediate post-offer trading is characterized by a larger proportion of institutional-sized buy trades than sell. We also find evidence suggesting that retail investors, who are initially shut out of the offering deals, buy bonds in the secondary market at a higher price. Our evidence suggests that certain institutional investors receiving allocations of non-self-marketed offerings flip them for a quick profit. The systematic disparity in aftermarket trading immediately following self-marketed versus non-self-marketed …

Why Did Retail Liquidity Programs Fail?, Thomas Ernst, Chester Spatt, Jian Sun

Research Collection Lee Kong Chian School Of Business

Five U.S. exchanges have Retail Liquidity Programs, which operate a limit order book only accessible to market orders from retail traders. In theory, this allows competition for segmented retail order flow. In practice, volumes executed in RLPs have been very low, and obtain prices inferior to those offered by off-exchange wholesalers. We trace this failure to three distinct issues: (1) cream-skimming by wholesalers, so that ``retail'' trades in RLPs carry high adverse selection risk, (2) an inability by RLPs to display quotes without pre-trade transparency of available prices, and (3) a lack of trade-through protection, with wholesalers executing trades at …

Environmental, Social, And Governance (Esg) And Artificial Intelligence In Finance: State-Of-The-Art And Research Takeaways, Tristan Lim

Research Collection School Of Computing and Information Systems

The rapidly growing research landscape in finance, encompassing environmental, social, and governance (ESG) topics and associated Artificial Intelligence (AI) applications, presents challenges for both new researchers and seasoned practitioners. This study aims to systematically map the research area, identify knowledge gaps, and examine potential research areas for researchers and practitioners. The investigation focuses on three primary research questions: the main research themes concerning ESG and AI in finance, the evolution of research intensity and interest in these areas, and the application and evolution of AI techniques specifically in research studies within the ESG and AI in finance domain. Eight archetypical …

Investing In Climate: A Role For 'Sovereign Climate Funds', Marianna Kozintseva, Thierry Wizman

Sim Kee Boon Institute for Financial Economics

Efforts to address climate change have generally been focused on deploying mitigation technologies. However, it is adaptation technologies (and climate risk transfer) that will have to gain an increasing share of an investment pool dedicated to climate if human systems are to stay resilient to climate forces. Just like mitigation projects, adaptation projects have a strong public goods aspect, wherein public returns exceed private returns, and thus call for the state’s involvement. We argue that sovereign climate funds (SCFs) - new types of sovereign wealth funds with a climate investment mandate - can be critical purpose-built conduits especially for undertaking …

Essays On Empirical Asset Pricing, Luying Wang

Dissertations and Theses Collection (Open Access)

The dissertation consists of three chapters on empirical asset pricing. The first chapter examines
the market return predictability of media coverage on climate change. Specifically, we introduce a
comprehensive media climate change concern (ΔCMCCC) index, derived from unexpected climate
change coverage across diverse media channels, including print (newspapers), voice (radio), and
video (television). We show that this index negatively predicts aggregate stock market returns, both
in-sample and out-of-sample, offering potential gains for investors. Our findings emphasize the
media’s influence on market returns through climate change discussions, mainly via the cash-flow
channel. This reveals possible shifts in product demand, while demand …

Analysts' Earnings Per Share Forecasts: The Effects Of Forecast Uncertainty And Forecast Precision On Investor Judgements, Clarence Goh

Research Collection School Of Accountancy

This study uses controlled experiments to investigate the joint effects of forecast uncertainty and forecast precision on investor judgements. It finds that forecast precision moderates the effects of forecast uncertainty on investors' forecast reliability judgements such that the effects of forecast uncertainty on investors' judgements of forecast reliability are more negative when an analyst's point earnings per share (EPS) forecast is rounded than when it is precise. In addition, the relationship between forecast precision and investors' judgements of forecast reliability is mediated by investors' perceptions of forecast attributes. The evidence also suggests that while forecast uncertainty exerts a negative effect …

On The Effects Of Information Asymmetry In Digital Currency Trading, Kwansoo Kim, Robert John Kauffman

Research Collection School Of Computing and Information Systems

We report on two studies that examine how social sentiment influences information asymmetry in digital currency markets. We also assess whether cryptocurrency can be an investment vehicle, as opposed to only an instrument for asset speculation. Using a dataset on transactions from an exchange in South Korea and sentiment from Korean social media in 2018, we conducted a study of different trading behavior under two cryptocurrency trading market microstructures: a bid-ask spread dealer's market and a continuous trading buy-sell, immediate trade execution market. Our results highlight the impacts of positive and negative trader social sentiment valences on the effects of …

Analyzing Global Utilization And Missed Opportunities In Debt-For-Nature Swaps With Generative Ai, Nataliya Tkachenko, Simon Frieder, Ryan-Rhys Griffiths, Christoph Nedopil

Sim Kee Boon Institute for Financial Economics

We deploy a prompt-augmented GPT-4 model to distill comprehensive datasets on the global application of debt-for-nature swaps (DNS), a pivotal financial tool for environmental conservation. Our analysis includes 195 nations and identifies 21 countries that have not yet used DNS before as prime candidates for DNS. A significant proportion demonstrates consistent commitments to conservation finance (0.86 accuracy as compared to historical swaps records). Conversely, 35 countries previously active in DNS before 2010 have since been identified as unsuitable. Notably, Argentina, grappling with soaring inflation and a substantial sovereign debt crisis, and Poland, which has achieved economic stability and gained access …

Do Underwriters Short-Change Corporations Issuing Bonds?, Jeremy C. Goh, Lisa (Zongfei) Yang

Research Collection Lee Kong Chian School Of Business

We confirm prior evidence that bonds on average are offered at prices below their immediate post-offer secondary market prices. However, in cases where banks lead–manage their own bond offerings the underpricing is significantly less as compared with other non-self-marketed offerings. These findings are robust across various matched samples and selection models. Our results suggest that the bond offering process is characterized by substantive agency conflicts between shareholders of corporations (issuers) and underwriters.

Legal Risk And Insider Trading, Marcin Kacperczyk, Emiliano Sebastian Pagnotta

Research Collection Lee Kong Chian School Of Business

Do illegal insiders internalize legal risk? We address this question with hand-collected data from 530 SEC (the U.S. Securities and Exchange Commission) investigations. Using two plausibly exogenous shocks to expected penalties, we show that insiders trade less aggressively and earlier and concentrate on tips of greater value when facing a higher risk. The results match the predictions of a model where an insider internalizes the impact of trades on prices and the likelihood of prosecution and anticipates penalties in proportion to trade profits. Our findings lend support to the effectiveness of U.S. regulations' deterrence and the long-standing hypothesis that insider …

Examining Sustainable Overseas Investment Information-Sharing Model For Automobile Enterprises: A Multi-Modal Weight Network Approach, Yuan Cheng, Xiaofang Chen, Changbo Lin, Sheqing Ma, Jie Feng

Research Collection School Of Accountancy

In an era of globalization, automotive companies are increasingly looking to make overseas investments to expand their production capacity and explore foreign markets. However, the outcomes of such investments are often influenced by a myriad of factors, including policy changes, social dynamics, and market conditions. To address the need for a comprehensive overseas investment information-sharing model, this research proposes an innovative approach based on a multi-modal weight network. This model aims to provide users with a global perspective on overseas investment opportunities, encompassing policy insights, and market dynamics. It integrates data from various sources, offering multi-dimensional information on investment regions, …

Diverse Hedge Funds, Yan Lu, Narayan Y. Naik, Melvyn Teo

Research Collection Lee Kong Chian School Of Business

Hedge fund teams with heterogeneous educational backgrounds, academic specializations, work experiences, genders, and races, outperform homogeneous teams after adjusting for risk and fund characteristics. An event study of manager team transitions, instrumental variable regressions, and an analysis of managers who simultaneously operate solo- and team-managed funds address endogeneity concerns. Diverse teams deliver superior returns by arbitraging more stock anomalies, avoiding behavioral biases, and minimizing downside risks. Moreover, diversity allows hedge funds to circumvent capacity constraints and generate persistent performance. Our results suggest that diversity adds value in asset management. Authors have furnished an Internet Appendix, which is available on the …

What Difference Do The New Factor Models Make In Portfolio Allocation?, Frank J. Fabozzi, Dashan Huang, Fuwei Jiang, Jiexun Wang

Research Collection Lee Kong Chian School Of Business

This paper compares the Hou-Xue-Zhang four-factor model with the Fama-French five-factor model from an investing perspective both in- and out-of-sample. Without margin requirements and model uncertainty, the Hou-Xue-Zhang model outperforms the Fama-French model. However, the outperformance could become negligible if an investor is subject to margin requirements and model uncertainty. The Hou-Xue-Zhang model shows similar power as the Fama-French model in describing the covariance matrix of asset returns. Overall, the two models do not make a difference for investing in a realistic setting.

Robust Permissioned Blockchain Consensus For Unstable Communication In Fanet, Zihao Wang, Hang Wang, Zhuowen Li, Xinghua Li, Yinbin Miao, Yanbing Ren, Yunwei Wang, Zhe Ren, Deng, Robert H.

Research Collection School Of Computing and Information Systems

The utilization of blockchain technology as a distributed information sharing system has gained widespread adoption across various domains. However, its application to Flying Ad-Hoc Network (FANET), characterized by severe packet loss, poses significant challenges. The high packet loss rates in FANETs can result in decreased consensus success rates and negatively impact information sharing consistency and efficiency. In this paper, we proposed RoUBC, a novel consensus scheme for Flying Ad-Hoc Networks (FANET), which is based on the Raft protocol and is designed to address the challenges posed by the severe packet loss network in FANET. The proposed scheme consists of two …

Earnhft: Efficient Hierarchical Reinforcement Learning For High Frequency Trading, Molei Qin, Shuo Sun, Wentao Zhang, Haochong Xia, Xinrun Wang, Bo An

Research Collection School Of Computing and Information Systems

High-frequency trading (HFT) is using computer algorithms to make trading decisions in short time scales (e.g., second-level), which is widely used in the Cryptocurrency (Crypto) market, (e.g., Bitcoin). Reinforcement learning (RL) in financial research has shown stellar performance on many quantitative trading tasks. However, most methods focus on low-frequency trading, e.g., day-level, which cannot be directly applied to HFT because of two challenges. First, RL for HFT involves dealing with extremely long trajectories (e.g., 2.4 million steps per month), which is hard to optimize and evaluate. Second, the dramatic price fluctuations and market trend changes of Crypto make existing algorithms …

Market-Gan: Adding Control To Financial Market Data Generation With Semantic Context, Haochong Xia, Shuo Sun, Xinrun Wang, Bo An

Research Collection School Of Computing and Information Systems

Financial simulators play an important role in enhancing forecasting accuracy, managing risks, and fostering strategic financial decision-making. Despite the development of financial market simulation methodologies, existing frameworks often struggle with adapting to specialized simulation context. We pinpoint the challenges as i) current financial datasets do not contain context labels; ii) current techniques are not designed to generate financial data with context as control, which demands greater precision compared to other modalities; iii) the inherent difficulties in generating context-aligned, high-fidelity data given the non-stationary, noisy nature of financial data. To address these challenges, our contributions are: i) we proposed the Contextual …

Navigating Geopolitical Crises For Energy Security: Evaluating Optimal Subsidy Policies Via A Markov Switching Dsge Model, Ying Tung Chan, Maria Teresa Punzi, Hong Zhao

Sim Kee Boon Institute for Financial Economics

This paper aims to provide insights on the design of optimal subsidy policies to enhance energy security amidst energy disruptions triggered by geopolitical conflicts. We introduce a novel Markov switching dynamic stochastic general equilibrium (MS-DSGE) model to address the limitations of existing integrated assessment models in environmental evaluation. These models often fail to adequately consider the environmental and economic impacts of geopolitical conflicts and do not prioritize energy security sufficiently in policymaking. Our application of the MS-DSGE model to the Russia–Ukraine conflict reveals significant decreases in output, social welfare, and energy consumption during disruptions. The mere anticipation of an energy …

Local Institutional Investors And Corporate Monitoring: Evidence From Cross-Listed Korean Stocks In The Us Market, Changhwan Choi, Chune Young Chung, Jun Myung Song

Sim Kee Boon Institute for Financial Economics

Using Korean firms that are cross-listed in the US market, this paper investigates whether there are standalone effects of geographic and market proximity of institutional investors on monitoring performance. We find that Korean institutional ownership is negatively associated with earnings management while the US institutional ownership has no impact on earnings management. This suggests that there is the geographic proximity advantage over the market proximity advantage in the emerging markets. Furthermore, we also show that the impact of geographic proximity is stronger for firms with high informational opacity

Special Issues In Support Of Evidence-Based Policy Making In Sustainable Banking And Finance, Lucia Alessi, Theodor Florian Cojoianu, Declan French, Andreas G. F. Hoepner

Research Collection College of Integrative Studies

BackgroundIn December 2015, 195 countries around the world signed the Paris Agreement and pledged to work towards limiting global greenhouse gas emissions in order to limit the average global temperature increase to 1.5 °C above preindustrial levels. From a scientific perspective, the stabilisation of global warming under any target requires the achievement of a net-zero emissions economy (Matthews & Caldeira, 2008). In support of global investors looking to provide capital towards green solutions andSustainability disclosures – a means to what end?A significant body of literature has suggested that many of the voluntary sustainability disclosures of companies come from the need …

Climate Change Concerns And Mortgage Lending, Tinghua Duan, Frank Weikai Li

Research Collection Lee Kong Chian School Of Business

We examine whether beliefs about climate change affect loan officers’ mortgage lending decisions. We show that abnormally high local temperature leads to elevated attention to and belief in climate change in a region. Loan officers approve fewer mortgage applications and originate lower amounts of loans in abnormally warm weather. This effect is stronger among counties heavily exposed to the risk of sea-level rise, during periods of heightened public attention to climate change, and for loans originated by small lenders. Additional tests suggest that the negative relation between temperature and approval rate is not fully explained by changes in local economic …

Shadow Bank, Risk-Taking, And Real Estate Financing: Evidence From The Online Loan Market, Xiaoying Deng, Chong Liu, Eng Seow Ong

Research Collection Lee Kong Chian School Of Business

This paper examines whether and how individual risk-taking behavior affects real estate financing through shadow banks. Using the loan data from an online platform in China, we show that riskier households tend to employ online loans to meet the increasing down-payment in their home purchase. Individual investors are likely to fund riskier real estate loans with higher expected returns. Real estate loans experience higher ex-post default rates than other types of loans. The effect is more pronounced during the period of credit constraints.

Derivatives And Market (Il)Liquidity, Shiyang Huang, Bart Zhou Yueshen, Cheng Zhang

Research Collection Lee Kong Chian School Of Business

We study how derivatives (with nonlinear payoffs) affect the underlying assets liquidity. In a rational expectations equilibrium, informed investors expect low conditional volatility and sell derivatives to the others. These derivative trades affect different investors utility differently, possibly amplifying liquidity risk. As investors delta hedge their derivative positions, price impact in the underlying drops, suggesting improved liquidity, because informed trading is diluted. In contrast, effects on price reversal are ambiguous, depending on investors relative delta hedging sensitivity, i.e., the gamma of the derivatives. The model cautions of potential disconnections between illiquidity measures and liquidity risk premium due to derivatives trading.

Market For Manipulable Information, Hui Chen, Jian Sun

Research Collection Lee Kong Chian School Of Business

We study how investors, firms, and information sellers interact in a market with manipulable information. To better predict the firm characteristics they care about, investors can buy a score from a monopolistic information seller, which aggregates signals that are subject to firm manipulation. The average degree of signal manipulability has no effect on the equilibrium, while the uncertainty about manipulability becomes a new source of noise. Its contribution depends on firms' incentive to manipulate the signals, which in turn depends on the equilibrium price sensitivity to the score. The optimal design of the score weighs signal precision against the endogenous …

Partisanship In Loan Pricing, Ramona Dagostino, Janet Gao, Pengfei Ma

Research Collection Lee Kong Chian School Of Business

Does partisanship influence the way investors price financial assets? Using voter registration data of bankers originating large corporate loans, we show that bankers whose party differs from that of the U.S. President charge 7% higher loan spreads than other bankers. This effect holds regardless of borrowers’ partisanship, and becomes stronger for politically active bankers and when partisan media exhibit greater disagreement. Bankers do not match disproportionately with co-partisan borrowers but they lead syndicates more frequently with co-partisan bankers. Our results are not driven by bank or borrower fundamentals, but suggest that investor optimism, driven by political alignment, shapes asset prices.

In Search Of Cryptocurrency Failure, Donglian Ma, Jun Tu, Zhaobo Zhu

Research Collection Lee Kong Chian School Of Business

This paper explores the determinants of cryptocurrency failure and the pricing of crypto failure risk. We document different significant market- and characteristic-based predictors for coin and token failures. The introduction of Bitcoin futures and the outbreak of COVID19 affect the importance of many predictors. Investors require extra return for bearing high failure risk of crypto assets. The return difference across high and low failure risk crypto assets is not explained by the market, size and momentum factors in the cryptocurrency market. Finally, investors benefit from diversifying into high failure risk crypto assets that is little correlated with the stock market.

Modelling Sentiment And Trader Aggressiveness In Cryptocurrency Markets: An Empirical Analysis Of The Bitcoin Limit Order Book., Angelique Nicole Huei Yin Thang

Dissertations and Theses Collection (Open Access)

Cryptocurrency assets are inherently susceptible to social sentiment. Due to emotional contagion, extreme emotions influence and drive traders’ order execution behaviour. This study aims to empirically model the relationship between sentiment and trader aggressiveness for two types of traders: Whales and Retails. Additionally, I uncover the mediating roles of momentum, mean reversion, and market timing underpinning the dynamics of the off-chain Bitcoin market. Time series data collected from the Coinbase level 3 Bitcoin limit order book is first reconstructed to access its core structure. Next, sentiment data from Reddit is extracted and processed using an internal Natural Language Processing pipeline. …

The Relationship Between Reits Industry Characteristics And Project Performance: The Moderating Role Of Macroeconomic Fluctuations, Ying Cai

Dissertations and Theses Collection (Open Access)

As a distinct investment vehicle, Publicly Listed Real Estate Investment Trusts (REITs) projects enable real estate projects to be listed on the stock market. This study begins with the industry attributes of the underlying assets of Publicly Listed REITs projects. Using econometric methods, it analyzes the variances in market performance between growth and defensive REITs, based on annual data from 1,674 REITs products in the United States from 2005 to 2022 and 27 listed REITs in China from Q3 2021 to Q1 2023. The study also leverages the data from China to explore the moderating effects of macroeconomic factors such …

Are Bond Returns Predictable With Real-Time Macro Data?, Dashan Huang, Fuwei Jiang, Kunpeng Li, Guoshi Tong, Guofu Zhou

Research Collection Lee Kong Chian School Of Business

We investigate the predictability of bond returns using real-time macro variables and consider the possibility of a nonlinear predictive relationship and the presence of weak factors. To address these issues, we propose a scaled sufficient forecasting (sSUFF) method and analyze its asymptotic properties. Using both the existing and the new method, we find empirically that real-time macro variables have significant forecasting power both in-sample and out-of-sample. Moreover, they generate sizable economic values, and their predictability is not spanned by the yield curve. We also observe that the forecasted bond returns are countercyclical, and the magnitude of predictability is stronger during …