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Full-Text Articles in Business

Financing Just Energy Transitions In Southeast Asia: Application Of The Just Transition Transaction To Indonesia, Vietnam, And Philippines, Abhinav Jindal, Gireesh Shrimali, Bharat Gangwani, Rajiv B. Lall Aug 2024

Financing Just Energy Transitions In Southeast Asia: Application Of The Just Transition Transaction To Indonesia, Vietnam, And Philippines, Abhinav Jindal, Gireesh Shrimali, Bharat Gangwani, Rajiv B. Lall

Sim Kee Boon Institute for Financial Economics

This paper investigates the applicability of the Just Transition Transaction (JTT), initially developed as a financial mechanism for South Africa's energy transition, to Southeast Asian (SEA) countries, including Indonesia, Vietnam, and the Philippines, which heavily rely on coal. Utilizing South Africa as a reference case study, we deconstruct the JTT and develop a novel framework of necessary and conducive features for evaluating its suitability for supporting a just energy transition in SEA. Our findings suggest that the JTT is well-suited for Indonesia and Vietnam but not as well suited for the Philippines. Recommendations for specific research avenues in estimating baselines …


Retail Investors' Activity And Climate Disasters, Marinela Adriana Finta Jun 2024

Retail Investors' Activity And Climate Disasters, Marinela Adriana Finta

Sim Kee Boon Institute for Financial Economics

We analyze the effects of climate disasters on retail investors’ trading activity. Results show that retail investors trade significantly less during and around climate disasters, and retail buyers exhibit higher returns than sellers. Climate disasters weaken the positive return predictability of the past month’s order imbalances while strengthening it for the past six month’s order imbalances. In the short run, firms within climate disaster counties with retail net buying underperform those with negative imbalances. Instead, in the long run, firms within and outside climate disaster counties with positive order flows outperform those with negative order flows. Finally, the estimates on …


Quantum Machine Learning For Credit Scoring, Nikolaos Schetakis, Davit Aghamalyan, Micheael Boguslavsky, Agnieszka Rees, Marc Rakotomalala, Paul Robert Griffin May 2024

Quantum Machine Learning For Credit Scoring, Nikolaos Schetakis, Davit Aghamalyan, Micheael Boguslavsky, Agnieszka Rees, Marc Rakotomalala, Paul Robert Griffin

Research Collection School Of Computing and Information Systems

This study investigates the integration of quantum circuits with classical neural networks for enhancing credit scoring for small- and medium-sized enterprises (SMEs). We introduce a hybrid quantum–classical model, focusing on the synergy between quantum and classical rather than comparing the performance of separate quantum and classical models. Our model incorporates a quantum layer into a traditional neural network, achieving notable reductions in training time. We apply this innovative framework to a binary classification task with a proprietary real-world classical credit default dataset for SMEs in Singapore. The results indicate that our hybrid model achieves efficient training, requiring significantly fewer epochs …


Specifying And Estimating Vector Autoregressions Using Their Eigensystem Representation, Leo Krippner May 2024

Specifying And Estimating Vector Autoregressions Using Their Eigensystem Representation, Leo Krippner

Sim Kee Boon Institute for Financial Economics

This article introduces the principles and mechanics of the eigensystem vector autoregression (EVAR) framework, where a VAR may be specified and estimated directly via its eigenvalue and eigenvector parameters. Using explicit constraints on the eigensystem permits control of a VAR ís allowable dynamics, which is illustrated empirically with standard and time-varying VAR estimations specified to be always non-explosive.


Environmental, Social, And Governance (Esg) And Artificial Intelligence In Finance: State-Of-The-Art And Research Takeaways, Tristan Lim Apr 2024

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 …


Green Transition And Financial Stability: The Role Of Green Monetary And Macroprudential Policies And Vouchers, Ying Tung Chan, Maria Teresa Punzi, Hong Zhao Apr 2024

Green Transition And Financial Stability: The Role Of Green Monetary And Macroprudential Policies And Vouchers, Ying Tung Chan, Maria Teresa Punzi, Hong Zhao

Sim Kee Boon Institute for Financial Economics

This paper analyzes a mix of alternative policies in supporting the green transition and the phase-out of fossil fuels, without compromising financial stability. An environmental dynamic stochastic general equilibrium (E-DSGE) model with two sectors (green and brown) and endogenous default is developed to assess potential climate-induced financial stability threats that can be mainly generated through physical and transition risks mechanism. Those risks are evaluated through a compound capital depreciation shock and a carbon tax shock. The paper offers several findings. First of all, a too stringent carbon tax would increase the medium-term default rate in both sectors, harming financial stability …


Siphoned Apart: A Portfolio Perspective On Order Flow Segmentation, Markus Baldauf, Joshua Mollner, Bart Zhou Yueshen Apr 2024

Siphoned Apart: A Portfolio Perspective On Order Flow Segmentation, Markus Baldauf, Joshua Mollner, Bart Zhou Yueshen

Research Collection Lee Kong Chian School Of Business

We study liquidity supply in fragmented markets. Market makers intermediate heterogeneous order flows, trading off spread revenue against inventory costs. Applying our model to payment for order flow (PFOF), we demonstrate that portfolio-based considerations of inventory management incentivize market makers to segment retail orders by siphoning them off-exchange. Banning order flow segmentation reduces total welfare, can make trading more costly for all investors, and can resolve a prisoner's dilemma among market makers. These results differentiate our inventory-based model from the existing information-based theories of PFOF.


Investing In Climate: A Role For 'Sovereign Climate Funds', Marianna Kozintseva, Thierry Wizman Mar 2024

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 …


On The Effects Of Information Asymmetry In Digital Currency Trading, Kwansoo Kim, Robert John Kauffman Mar 2024

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 …


Do Underwriters Short-Change Corporations Issuing Bonds?, Jeremy C. Goh, Lisa (Zongfei) Yang Feb 2024

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.


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 Feb 2024

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, …


Analyzing Global Utilization And Missed Opportunities In Debt-For-Nature Swaps With Generative Ai, Nataliya Tkachenko, Simon Frieder, Ryan-Rhys Griffiths, Christoph Nedopil Feb 2024

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 …


Diverse Hedge Funds, Yan Lu, Narayan Y. Naik, Melvyn Teo Feb 2024

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 Feb 2024

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.


Legal Risk And Insider Trading, Marcin Kacperczyk, Emiliano Sebastian Pagnotta Feb 2024

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 …


Navigating Geopolitical Crises For Energy Security: Evaluating Optimal Subsidy Policies Via A Markov Switching Dsge Model, Ying Tung Chan, Maria Teresa Punzi, Hong Zhao Jan 2024

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 Jan 2024

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


Market For Manipulable Information, Hui Chen, Jian Sun Jan 2024

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 …


Climate Change Concerns And Mortgage Lending, Tinghua Duan, Frank Weikai Li Jan 2024

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 Jan 2024

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.


Geographic Links And Predictable Returns, Zuben Jin, Frank Weikai Li Jan 2024

Geographic Links And Predictable Returns, Zuben Jin, Frank Weikai Li

Research Collection Lee Kong Chian School Of Business

Using establishment-level data of U.S. public firms, we construct a novel measure of geographic linkage between firms. We show that the returns of geography-linked firms have strong predictive power for focal firm returns and fundamentals. This effect is distinct from other cross-firm return predictability and is not easily attributable to risk-based explanations. It is more pronounced for focal firms that receive lower investor attention, are more costly to arbitrage, and during high sentiment periods. The cross-firm information spillovers and return predictability are also stronger for geographic peers with economic linkages and with positive information. Our results are broadly consistent with …


Derivatives And Market (Il)Liquidity, Shiyang Huang, Bart Zhou Yueshen, Cheng Zhang Jan 2024

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.


On Sgx’S Voyage To Corporate Sustainability: Exploring Emerging Topics In Multi-Industry Corpora, Xinwen Ni, Min Bin Lin, Simon J.D. Schillebeeckx, Wolfgang Karl Hardle Jan 2024

On Sgx’S Voyage To Corporate Sustainability: Exploring Emerging Topics In Multi-Industry Corpora, Xinwen Ni, Min Bin Lin, Simon J.D. Schillebeeckx, Wolfgang Karl Hardle

Research Collection Lee Kong Chian School Of Business

Topic modeling and LDA (Latent Dirichlet Allocation) have proven valuable in various fields as an innovative approach to studying areas of interest and identifying topics in a dynamic content. The underlying assumption is that techniques like LDA can swiftly capture emerging topics in textual documents compared to other categorization tools. These unsupervised approaches have been used to identify new industries and technological domains. However, our study on the nascent topic of “sustainability” within the corpora of SGX-listed companies highlights clear limitations in employing techniques like LDA on sparse data. The dynamic LDA approach, also called DTM (Dynamic Topic Modelling),based on …