Finance Commons^™

Locally Robust Implementation Of Efficient Bilateral Trade With Correlated Beliefs, Takashi Kunimoto, Cuiling Zhang

Research Collection School Of Economics

We identify the ex ante welfare (EAW) condition as a necessary requirement to implement ex post efficient bilateral trade in any finite type space with interdependent values and correlated beliefs. As these finite settings become finer to approximate a continuous type space, we derive a limit EAW condition by taking the EAW condition in finite settings to its limit. We show that this limit condition trivially holds in the benchmark continuous setting admitting a full-support density function. We then insist on locally robust implementation by requiring efficient trade to be implemented uniformly across all finite type spaces that approximate the …

Modeling And Forecasting Intraday Spot Volatility, Adam Clements, Daniel P. A. Preve

Research Collection School Of Economics

We propose a multiple-equation regression-based method for modeling and forecasting intraday spot volatility. In this approach, intraday intervals are treated as individual time series, deviating from the common practice of treating the data as one continuous sample. Our empirical study, which spans more than two decades and encompasses six US blue-chip stocks, employs the recent OK volatility estimator developed by Li, Wang, and Zhang (2024) to expose the dynamics of latent intraday spot volatility over time. We demonstrate that the proposed method effectively captures the intricate dynamics of intraday spot volatility and find strong evidence that it outperforms a competing …

Bitcoin Options Risk-Reversal Predictability, Meng Hwee Neo

Dissertations and Theses Collection (Open Access)

This dissertation examines whether Bitcoin options risk-reversal (RR) spreads predict future Bitcoin returns, using daily Deribit data from April 2021 to December 2025 (1,723 observations).

In the primary 25-delta, 90-day specification, the RR coefficient is significant at the 1% level in a thirteen-variable baseline regression with Newey–West standard errors. Robustness tests across all available delta–tenor specifications show statistically significant RR coefficients in the majority of configurations, concentrating in the 30–180-day maturity band.

The butterfly spread (BF) also predicts returns. Both remain significant after controls are added: the RR t-statistic increases from 1.91 (univariate) to 3.73 (full baseline), and the BF …

Essays On Money Search Models, Fangfang Gong

Dissertations and Theses Collection (Open Access)

This dissertation comprises three papers that use money search models to revisit the distributional welfare costs of inflation, study the optimal design of a central bank digital currency (CBDC), and investigate the role of liquidity and monetary policy in initial investment and capital reallocation in secondary markets.

The second chapter develops a micro-founded general equilibrium model of payments to revisit the distributional welfare costs of inflation. We consider different cost structures incurred by merchants when accepting cash and deposits. In equilibrium, there exists a cutoff for buyers’ money holdings, above which card payments are accepted by merchants. We calibrate the …

Financial Technology And Household Wealth, Rongbo Zhou

Dissertations and Theses Collection (Open Access)

With the spread of mobile payment platforms in China, the micro-foundations of household financial behaviour have been reshaped, and this change is increasingly reflected in household property income. Based on microdata from the China Household Finance Survey (CHFS) for 2015, 2017, 2019, and 2021, this dissertation examines how mobile payment use affects household property income, through which channels this effect is transmitted, and how its impact differs across household groups, regional conditions, and macro-financial environments.

The empirical results show a positive association between the use of mobile payment platforms and household property income. This conclusion remains robust after controlling for …

Relationship Between Change In Unrealized Gains Or Losses Of Afs Securities And Credit Spreads Of U.S. Life Insurance Companies, Kwang Liang Yeo

Dissertations and Theses Collection (Open Access)

This study evaluates the transmission of unrealized fair value accounting losses to credit default risk within the United States life insurance sector during a period of unprecedented monetary tightening. Integrating a pre-specified confirmatory econometric framework with a text-based exploratory analysis of regulatory filings, we examine how changes in Other Comprehensive Income (OCI) and benchmark interest rate dynamics shape market perceptions of insurer default probability. Our findings reveal that credit default swap markets do not price OCI variations contemporaneously; instead, they reflect a structural one-quarter pricing lag that aligns with the regulatory timeline of financial disclosures. Furthermore, the relationship between interest …

Research On The Impact Of Industrial-Financial Cooperation On Corporate R&D Investment, Jiayin Yin

Dissertations and Theses Collection (Open Access)

The national industrial-financial cooperation pilot policy represents a key strategic initiative to implement China's strategy of building a "financial powerhouse" and guide financial resources toward empowering high-quality development in the real economy. In December 2016, four central government departments in China jointly announced the first batch of national industrial-financial cooperation pilot cities. Leveraging this quasi-natural experiment, this study comprehensively evaluates the impact of the pilot policy on corporate R&D investment activities using a sample of Chinese A-share listed companies from 2014 to 2019.

Research findings indicate: (1) The industrial-financial cooperation pilot policy significantly increases enterprises' R&D investment levels. Specifically, compared …

Reasoning On Time-Series For Financial Technical Analysis, Kelvin J. L. Koa, Jan Chen, Yunshan Ma, Huanhuan Zheng, Tat-Seng Chua

Research Collection School Of Computing and Information Systems

While Large Language Models have been used to produce interpretable stock forecasts, they mainly focus on analyzing textual reports but not historical price data, also known as Technical Analysis. This task is challenging as it switches between domains: the stock price inputs and outputs lie in the time-series domain, while the reasoning step should be in natural language. In this work, we introduce Verbal Technical Analysis (VTA), a novel framework that combine verbal and latent reasoning to produce stock time-series forecasts that are both accurate and interpretable. To reason over time-series, we convert stock price data into textual annotations and …

Art Pricing And Anti-Corruption Campaigns: Evidence From Repeat Sales Of Chinese Paintings, Yihan Wang

Dissertations and Theses Collection (Open Access)

My dissertation investigates the impact of China’s anti-corruption campaign on the pricing of traditional Chinese paintings, leveraging a unique dataset of repeat sales transactions. Since the 1990s, China’s art market has experienced explosive growth, becoming the world’s largest by 2011. However, this market is characterized by extreme opacity, facilitating elegant bribery (“ya hui” in Chinese), where artworks serve as vehicles for implicit corruption through inflated auctions or disguised gifts to officials. The launch of the "Eight-point Regulation" in December 2012 marked a significant intensification of anti-corruption efforts, raising the critical question of how such political shocks affect asset pricing in …

Agency Mbs As Safe Assets, Zhiguo He, Zhaogang Song

Research Collection Lee Kong Chian School Of Business

Measured as yield spreads against Treasury securities and AAA corporate bonds, the convenience premium of newly issued agency MBS averages more than half of the long-term Treasury convenience premium. The agency MBS convenience premium and issuance amount vary negatively with mortgage rate, consistent with a prepayment-driven channel. Placing agencies into conservatorship in 2008 and introducing liquidity regulations in 2013 significantly affected MBS convenience premium, consistent with government guarantee and regulatory treatment channels. Analyses of dispersion of dealers’ prepayment forecasts, seasoned MBS, and investors’ MBS holdings deliver further economic implications for agency MBS as safe assets.

Assessing Ethereum’S Diversification Role With Bitcoin And Major Equity Index – A Bayesian Mixture Copula Approach, Jackie Li, Jacie Jia Liu

Research Collection School Of Economics

With the introduction of spot Ethereum ETFs, Ethereum plays an increasingly important role in the cryptocurrency market. In this paper, we propose a Bayesian modelling framework incorporating a mixture copula for co-modelling Ethereum returns with Bitcoin or FTSE 100 returns. The mixture copula is designed as a combination of the Clayton copula and its three rotations, Frank, and Gaussian copulas. It provides substantial flexibility for handling a variety of dependency structures. The Bayesian approach offers the advantage of jointly estimating both the margins and copulas and simulating future returns in a coherent procedure. Using 10 different risk or risk-return measures, …

Privately Owned Companies Dominate Renewable Energy Generation Ownership Around The World, Dyaran Bansraj, Theodor Florian Cojoianu, Xi Hu, Khaladdin Rzayev, Francisco Urzua

Research Collection College of Integrative Studies

Global sustainable finance policies are premised on publicly listed companies driving decarbonization through transparency, investor pressure, and capital market access. Analysing c. 20,000 corporate owners of renewable and fossil-fuel assets worldwide, we show the opposite: private firms own approximately 75% of global renewable generation capacity. This private dominance holds across all major technologies and regions, with listed ownership of renewable assets being the majority only in the oil & gas and technology sectors. The Paris Agreement did not alter this balance. Instead, ownership of the energy transition reflects countries' financial structures, with similar patterns observed across manufacturing, construction, and financial …

Can Limited Partners Mitigate Negative Externalities In Private Equity?, Teodor Duevski, Chhavi Rastogi, Tianhao Yao

Sim Kee Boon Institute for Financial Economics

We show how Limited Partners' (LPs) environmental and social (E&S) concerns transmit to private equity (PE) rms through capital supply. E&S incidents in portfolio companies reduce PE fundraising, as E&S-concerned relationship LPs refrain from recommitting and are not easily substituted. Using a legal reform that expands E&S-concerned public pension capital to PE, we causally show that PE rms internalise LPs' E&S concerns, reducing dirty sector portfolio allocation and increasing ESG hiring. Additionally, PE rms with E&S- concerned relationship LPs engage with portfolio companies to manage E&S risks. Limited capital substitutability enables LPs to delegate E&S preferences, shaping PE allocation and …

Unlocking Private Equity Investing, Yin Wang, Steve Balaban

Asian Management Insights

Myths and market shifts to take note of.

Price Dislocations: Insights From Trade Repository Data, Albert Menkveld, Lucas Saru, Shihao Yu

Research Collection Lee Kong Chian School Of Business

This paper identifies price dislocation events in EuroSTOXX 50 futures, i.e., periods marked by high absolute returns. Combining public limit order book data with confidential trade repository data collected under the European Market Infrastructure Regulation (EMIR), we analyze market conditions around such dislocations. We find that price dislocations are accompanied by an increase in trading volume, and in the number of trades. EMIR data enables us to identify who participates in these trades, which allows us to tell if the volume increase is driven by fewer investors trading more, i.e., a more concentrated market, or by more investors participating. The …

Case Series Overview: Analysis Of Innovation Applications And Value Driven By Aigc Technology—An Early Investment Perspective In The Chinese Market, Siyuan Ma, Mengyu Wang, Tianyi Zhang

Sim Kee Boon Institute for Financial Economics

This case series explores the innovative applications and value analysis driven by AIGC (AI-generated content) technology from the perspective of early-stage investments in the Chinese market. We analyse the influence of core factors such as technology progression, market demand, policy environment, industry cycles and data on AIGC-driven value creation; case studies are provided to illustrate how AIGC has varying applications across different industries depending on market conditions. This series contains four cases: first, we first explore the investment opportunities of AIGC by combining the core technological value and industrial application status of generative AI, using China’s energy industry as a …

4 Of 4: Impact Of Policy And Technological Factors On Ai Innovation And Investment: The 2b Model Service Industry, Siyuan Ma, Mengyu Wang, Tianyi Zhang

Sim Kee Boon Institute for Financial Economics

This case explores AI investment opportunities in 2B model services, particularly in sectors that intrinsically benefit from the reduction in human error. We will analyse applications in the legal industry as an example of overarching 2B model service trends.

3 Of 4: Analysis Of Innovation Applications And Value Driven By Aigc Technology: An Early Investment Perspective In The Chinese Market, Siyuan Ma, Mengyu Wang, Tianyi Zhang

Sim Kee Boon Institute for Financial Economics

This case series explores the innovative applications and value analysis driven by AIGC (AI-generated content) technology from the perspective of early-stage investments in the Chinese market. We analyse the influence of core factors such as technology progression, market demand, policy environment, industry cycles and data on AIGC-driven value creation; case studies are provided to illustrate how AIGC has varying applications across different industries depending on market conditions. This series contains four cases: first, we first explore the investment opportunities of AIGC by combining the core technological value and industrial application status of generative AI, using China’s energy industry as a …

2 Of 4: Impact Of Human Resource Factors On Ai Investment: Ai In The Human Resource Market, Siyuan Ma, Mengyu Wang, Tianyi Zhang

Sim Kee Boon Institute for Financial Economics

This case will explore the implications that AIGC trends have on the development of the Chinese Human Resource (HR) market. While previous generation internet products were based on common needs and provided standardized products, the development of large AI models has opened doors to personalized custom products and services. Take AI applications in online education as an example: AI education models are developing to tailor to individual needs, since almost everything is not only digitalised but also based on dynamic database analysis for each user, including traffic distribution, sales conversion and service evaluation.

1 Of 4: Aigc Technology And Applications: Policy And Industry Development, Siyuan Ma, Mengyu Wang, Tianyi Zhang

Sim Kee Boon Institute for Financial Economics

This case explores the investment opportunities of AIGC by combining the core technological value and industrial application status of generative AI. We then analyse the impacts of these large-scale sectoral changes in a study of AI in China’s energy industry. We are currently in the early stage of the generative AI industry, thus it is analysed more from the perspective of early value investment, including trend investment opportunities brought by macro cycles, inflection point investment opportunities brought by industry transformation and application, and value creation brought by disruptive innovation. The early investment in the Chinese market is also at a …

Technical Appendix: Analysis Of Innovation Applications And Value Driven By Aigc Technology—An Early Investment Perspective In The Chinese Market, Siyuan Ma, Mengyu Wang, Tianyi Zhang

Sim Kee Boon Institute for Financial Economics

Following the introduction of generative AI/AIGC concepts and applications, it is necessary to clarify two related technical concepts: machine vision (CV) and convolutional neural networks (CNN). Computer Vision (CV) is a discipline that studies how to convert inputs such as images, sounds, and videos into a language that computers can understand. Taking 2D images as an example, all images can be broken down into very small pixels, each of which can be converted into a number (based on grayscale) or a combination of numbers. The number represented by each pixel is the feature of that pixel, and combining these numbers …

Is R&D Rivalry Slowing The Growth Of Productive Firms?, Yoshiki Ando, James Bessen, Xiupeng Wang

Research Collection School Of Economics

The reallocation of jobs to more productive firms is a substantial component of aggregate productivity growth, yet job reallocation rates have declined substantially in the United States. This paper explores the hypothesis that greater technological rivalry has exacerbated adjustment costs, slowing reallocation. Using microdata at the US Census and estimates of technological rivalry in firm growth regressions, we find that technological rivalry slows firm responses to productivity shocks. Firms do not expand as rapidly in the face of higher obsolescence risk. Estimating counterfactual firm growth from 1997-2018, we find that growing technological rivalry accounts for most of the decline in …

Multi-Period Portfolio Allocation: A One-Shot Stochastic Optimization Approach, Peng Liu, Chyng Wen Tee, Xiaofei Xu

Research Collection Lee Kong Chian School Of Business

Multi-period portfolio optimization is a central problem in finance, yet it is computationally intractable for traditional dynamic programming methods due to the curse of dimensionality. This paper develops a tractable and theoretically grounded 'one-shot' stochastic optimization framework that recasts the sequential decision problem into a single, high-dimensional optimization task. Our approach models the predictive distribution of factor returns using Gaussian Processes (GPs), allowing it to capture complex, non-linear market dynamics. We make three primary contributions. First, for the special case of a linear GP kernel, we derive an analytical solution for the optimal portfolio path, providing a clear economic interpretation …

Do Search Costs Explain Persistent Investment In Active Mutual Funds?, Aljoscha Janssen, Jurre Thiel

Research Collection School Of Economics

Active funds, though losing market share since the 1990s, make up nearly half of all mutual funds but charge more without better performance. We analyze fund data and a search model, highlighting the impact of search costs and active fund preferences. From 1993 to 2018, reduced search costs expanded the market and heightened competition, while a preference shift from active to passive funds increased the latter's market share. However, investors who choose active funds, facing higher search costs, and continue to show a strong preference for them, allow these funds to keep charging higher fees.

The Pricing Of Green Bonds And The Determinants Of The Green Bond Premium In The Asia-Pacific And European Markets, Parath Wongaree, Chiyachantana N. Chiraphol, Kuan Yong David Ding, Pattarawan Prasarnphanich, Wasin Siwasarit

Research Collection Lee Kong Chian School Of Business

This study examines the sources of capital for sustainable development and investigates the existence of a green bond premium in both primary and secondary bond markets across the Asia-Pacific and European regions. Utilizing the robust Coarsened Exact Matching (CEM) method in conjunction with the Synthetic Minority Oversampling Technique (SMOTE), our analysis reveals a significant disparity in yields between green bonds and conventional bonds within the Asia-Pacific markets, indicating the existence of a green bond premium. In contrast, this distinction is not observed in Europe. These findings suggest that investors in the Asia-Pacific region display a willingness to accept lower yields …

Intraday Volatility In Financial Markets: Evidence From High-Frequency Data, Haolin Wang

Dissertations and Theses Collection (Open Access)

In this study, we conduct an analysis of intraday spot volatility using high-frequency data from the SPDR S&P 500 ETF (SPY). We begin with the assumption that the intraday volatility of asset prices exhibits time-variation. To capture this dynamic behavior, we construct proxies for the unobserved spot volatility by applying appropriate estimators to the high-frequency price data. Following the estimation procedure, we employ various forecasting models to generate volatility forecasts. Finally, we evaluate and compare the predictive performance of these models using established forecast evaluation metrics, and analyze the results.

Essays On Financial Econometrics, Yuexuan Ren

Dissertations and Theses Collection (Open Access)

This dissertation consists of two papers that contribute to the theory of estimation, inference, and prediction using high-frequency financial data. In the first chapter, time-varying betas from return regressions, commonly used to measure systematic financial market risk, are studied using high-frequency data. A novel econometric framework is introduced for the nonparametric estimation of these betas. The optimal finite-sample inference, in a well-defined sense, is enabled by the local Gaussian property of a generic continuous-time benchmark model under the fixed-k framework. Furthermore, a uniform functional inference theory for spot regressions is developed. The proposed methodology is broadly applicable in empirical settings, …

Valuation Of Crypto Assets On Blockchain With Deep Learning Approach, Xi Zhou, Yin Pang, Esther Ying Yang, Jing Rong Goh, Shaun Shuxun Wang

Research Collection School Of Economics

With the rapid expansion of the blockchain ecosystem, crypto asset valuation has become an essential area of study for investors and institutions. Here, we introduce a deep learning framework that was designed to predict the value index of crypto assets by integrating intrinsic value variables and decomposing market prices into value and sentiment components. The Crypto Asset Value-indexing Model (CAVM) was applied to Ethereum’s cryptocurrency ETH to demonstrate its effectiveness. Four econometric tests were conducted to verify the informativeness, predictiveness, and reasonability of the generated value indices, as well as the efficiency of price decomposition. Our findings suggested that the …

Tba Trading And Security Issuance In The Agency Mbs Market, Yu An, Wei Li, Zhaogang Song

Research Collection Lee Kong Chian School Of Business

In addition to the standard individual-security-based specified pool (SP) contract, agency mortgage-backed securities (MBS) are actively traded via the to-be-announced (TBA) contract that sets a uniform price for a cohort of heterogeneous securities. We provide empirical support for the economic impact of TBA trading on MBS issuers' security design: issuers pick low-quality loans and pool them together into few TBA MBS. We then conduct a quantitative analysis and show that TBA-trading-induced strategic MBS design increases issuers' selling revenue by about 55% of the SP transaction costs. Finally, we show that smaller issuers are less able to package low-quality loans separately …

Essays On Empirical Asset Pricing, Qi Fan

Dissertations and Theses Collection (Open Access)

My dissertation consists of three studies on how investor behavior affects the outcomes in financial markets. The first study focuses on the investors’ limited capacity on processing the complicated information transmitted through interconnected firms. The other two studies explore the investor heterogeneity on preferred time of trading, due to their personal traits or irrational judgements on the market conditions.

In Chapter 2, I focus on the return predictability across economically linked firms, due to investor limited attention. I document significant outperformance of stocks whose industry peers currently experience salient (attention-grabbing) gains, especially for those with strong social ties. The long-short …