Portfolio and Security Analysis Commons^™

The Effects Of Eps Level And Presentation Format Of Analysts’ Forecast Deviation On Non-Professional Investors’ Investment Judgments, Clarence Goh, Prasart Jongjaroenkamol, Poh-Sun Seow

Research Collection School Of Accountancy

We experimentally investigate how the presentation format of the extent to which a firm's earnings per share (EPS) diverges from analysts' EPS forecasts (i.e. deviation information) and a firm's EPS level affect the investment judgments of non-professional investors (referred to hereafter as “investors”). Our results suggest that investors' investment judgments are more positive when firms with low (high) EPS levels disclose deviation information in percentage (absolute) terms. Furthermore, when the percentage of forecast deviation is held constant, investment judgments are more positive when EPS levels are high versus low if the deviation information is expressed in absolute terms. By contrast, …

The Impact Of Sovereign Wealth Funds On Emerging Markets: A Behavioral Analysis Of Investment Decisions And Market Reactions, Grant A. Mosshart

Senior Honors Theses

Sovereign Wealth Funds (SWFs) are increasingly influential in emerging markets, yet the behavioral drivers behind their investments remain underexplored. In this paper, an analysis of SWF capital’s impact on economic development and the psychological factors, such as optimism bias and herding, that shape these decisions is examined. Utilizing a mixed-methods comparative study, the research analyzes Saudi Arabia’s Public Investment Fund (PIF) and Singapore’s Temasek Holdings. Event study analysis reveals a divergent impact: the PIF’s high-profile developmental commitment to India generated a positive 5-day Cumulative Abnormal Return of +2.05%, confirming a macro-level “seal of approval” signaling effect. By contrast, Temasek’s commercially …

Simple Determinants Of Commercial Bank Failures, Matthrew Qi

Undergraduate Economics Working Paper Series

This study investigates the internal and macroeconomic determinants of commercial banking failures in the United States spanning 1959 to 2025. Using a logit model and a four-quarter lag, two models are estimated: a comprehensive model (1985–2025) and an extended panel model (1960–2025). Empirical results reveal internal CAMELS metrics are primary determinants of survival; profitability and capital adequacy defends against failures, while asset quality deterioration and management inefficiencies accelerates failure. The “too big to fail” paradigm is empirically validated. Contractionary monetary policy and labor market stress increase failure probabilities. Real GDP growth exhibits a role shift predicting commercial bank failures.

An Explanation Of Alternatives Within A Portfolio, Isaac J. Reitman

Finance Undergraduate Honors Theses

This thesis attempts to provide insight into the role of alternative investments within modern portfolio construction for accredited and institutional investors.

The asset classes discussed are as follows: private credit, private equity, venture capital, hedge funds, collectibles, and real estate.

Clawing Back Fraudulent Profits—Investor Protection Or Regulatory Overreach: The Disgorgement Dilemma In Securities Law, Jessica Sun

The Journal of Business, Entrepreneurship & the Law

This comment explores the legal complexities surrounding the Securities and Exchange Commission’s (SEC) use of disgorgement as an enforcement tool, specifically addressing the tension between investor protection and regulatory overreach. Sun examines the evolution of disgorgement from a court-created equitable remedy to a power formally codified by the National Defense Authorization Act of 2021, while highlighting the significant limitations imposed by Supreme Court rulings in Kokesh v. SEC and Liu v. SEC. The comment centers on a current circuit split between the Second Circuit’s decision in SEC v. Govil—which requires a showing of "pecuniary harm" to victims before awarding disgorgement—and …

Digital Transformation And Market Microstructure: Analyzing The Impact Of Algorithmic Trading On National Stock Exchange Of India Price Discovery Mechanisms Through Complex Systems Theory., Mukesh Bhaskar Ahirrao, Harshal Anil Salunkhe, Vishal Sunil Rana

Northeast Journal of Complex Systems (NEJCS)

Abstract

This research examines the evolution of market microstructure at the National Stock Exchange of India (NSE) from 2020 to 2024, a period characterized by substantial growth in algorithmic trading from 35% to 44% of total trading volume. Using market microstructure data and analytical techniques grounded in complex systems perspectives, the study documents temporal patterns in price discovery, liquidity, volatility, and market efficiency associated with this digital transformation.

The analysis reveals several notable changes in market characteristics. Transaction costs improved significantly, with bid-ask spreads declining by 23.4% and market depth increasing by 18.1%. Price adjustment half-life decreased by 50%, indicating …

Assessing Tracking Error Of The Municipal Bond Etfs, Maksym Chikin

Honors Theses

Municipal bond exchange-traded funds (ETFs) provide diversified exposure to state and local government bonds through a single tradable security. They also provide interest that is usually exempt from federal income tax. This thesis examines 31 investment-grade and 3 high-yield municipal bond ETFs from April 2015 to February 2025 and compares them with three passively managed broad-market bond ETFs: BND (investment-grade bonds), SCHR (Treasury bonds), and JNK (high-yield corporate bonds). Using tracking error, volatility, and returns across the pre-COVID, COVID, and post-COVID periods, the results show that municipal bond ETFs—especially high-yield funds—have higher tracking errors, greater volatility, and more variable returns …

Comparing The Risk And Return Characteristics Of Ai Exchange-Traded Funds To Benchmark Stock Market Etfs, Aryan Malhotra

Honors Theses

Artificial intelligence exchange-traded funds (AI ETFs) have expanded rapidly as investors seek targeted exposure to firms developing or benefiting from AI technologies. This study compares the performance of 50 AI ETFs with two broad-market ETFs, SPY (S&P 500) and RSP (equal-weight S&P 500), from January 2018 to January 2026. AI ETFs exhibit higher expense ratios and strong correlations with both benchmarks, reflecting their concentration in large-cap technology stocks. Over the full sample, AI ETFs generated higher cumulative returns but with substantially greater volatility. Sub-period analysis further decomposes the post-COVID period into pre-ChatGPT (April 2020–November 2022) and post-ChatGPT (December 2022–January 2026) …

Woulda, Shoulda, Coulda? The Impact Of Predictive, Prescriptive, And Prospective Expectations On Stakeholder Reactions, Yuri Mishina, Maxine Yu, David Gomulya

Research Collection Lee Kong Chian School Of Business

When and why might stakeholders react to firm activities in ways that might be different than, or even contradictory to, what we might expect based on the extant research? We draw on expectancy violation theory (EVT) and bring in the notion of heuristics and future-oriented expectations to examine this question, using a sample of investor reactions to earnings surprises from 2013 to 2019. We find that, in addition to comparing earnings to consensus earnings estimates, investors appear to compare the earnings surprises to the firm’s past performance and to its peers. Importantly, their expectations regarding future interactions with the firm …

Ai-Scm Cmm: A Capability Maturity Model For Artificial Intelligence Integration In Supply Chain Management, Lordt Becklines, Omar F. El-Gayar, Patti Brooks, Insu Park

Annual Research Symposium

Artificial intelligence is increasingly deployed in supply chain management, yet many organizations struggle to align adoption efforts with process readiness, data quality, governance, and workforce capabilities, and they still lack validated supply chain specific roadmap for assessing readiness, sequencing investments, and reducing implementation risk. This study develops and evaluates a Capability Maturity Model for Artificial Intelligence Integration in Supply Chain Management to address that gap. Using a design science research approach, the study synthesizes prior literature and practitioner knowledge to define maturity dimensions, capability indicators, and staged progression levels for AI integration in supply chain contexts. The artifact and assessment …

Nominal Prices, Retail Investor Participation, And Return Momentum, Jun Du, Dashan Huang, Yu-Jane Liu, Yushui Shi, Avanidhar Subrahmanyam, Huacheng Zhang

Research Collection Lee Kong Chian School Of Business

We employ an identification strategy for retail participation to explore the link between return momentum and investing clientele. This scheme relies on strictly enforced round-lot rules in China, which financially constrain retail investors from participating in stocks with high nominal prices. We find that there is strong momentum in high-priced stocks, but no momentum on aggregate. This result supports the idea that noise trades of retail investors mask momentum, while other, more sophisticated investors contribute to momentum. We validate this notion by showing that retail investors with small (large) portfolios are less (more) prone to participating in stocks with high …

A Capability Maturity Model For Artificial Intelligence Integration In Supply Chain Management, Lordt Becklines

Dissertations

Artificial Intelligence (AI) is transforming Supply Chain Management (SCM), yet many organizations struggle to assess their readiness for AI adoption and to understand how AI capabilities develop across maturity stages. This dissertation addresses this gap by developing a Capability Maturity Model (CMM) for AI integration in SCM, grounded in Organizational Information Processing Theory (OIPT), the Resource-Based View, and related capability frameworks. The model provides a structured approach for evaluating an organization's information-processing requirements, resource configurations, and alignment needed for effective AI-enabled supply chain operations.

Using a design science research approach, the AI-SCM CMM and its associated assessment instrument were derived …

Information Sharing Within Institutional Investor Networks, Wei Ting Loh

Research Collection School Of Accountancy

This study examines whether information sharing occurs within institutional investor networks. I identify networks of institutional investors who share common investments and find that in-network investors earn significantly higher returns than other investors of the same firm, suggesting that valuable private information is shared within these networks. I also find that ownership by investor networks is associated with speedier price discovery and incorporation of more firm-specific news in prices, consistent with information sharing facilitating efficient price formation. In addition, ownership by network investors is associated with higher information risk as reflected in the probability of informed trading and market liquidity. …

Beyond The Stream: Valuing Music Catalogs As An Alternative Asset Class, Amelia Jade Magay

Honors Theses and Capstones

This thesis builds a quantitative valuation framework for music catalog transactions and tests its limits systematically. The goal is not to produce a formula that perfectly prices every deal. The goal is to identify where streaming-based financial analysis is a useful underwriting tool, where it breaks down, and what categories of value investors appear to be pricing beyond publicly available streaming data.

From Static Λ To Moving Penalties: Dynamic Regularization In Mean-Variance Portfolio Choice, Ariel Santiago

CMC Senior Theses

This thesis evaluates whether dynamically tuned weight penalties can improve high-dimensional mean-variance portfolio choice. Classical Markowitz portfolios perform poorly when the number of assets is large relative to the data, because small estimation errors in means and covariances can generate extreme, fragile allocations. A common remedy is to regularize the weights using L1 (lasso), L2 (ridge), or elastic-net penalties, but these are typically chosen once and held fixed. Using monthly excess returns on the 48 Fama-French industry portfolios from January 2010 to June 2025, this thesis compares penalized mean-variance and minimum-variance strategies under long-only and long-short constraints, with and without …

Impact Of Attention And Yield Curve On Term Structure Of Equity, Matthew C. Aved

CMC Senior Theses

This paper examines the term structure of equity and specifically focuses on the impact of term spread and market attention. The paper builds on prior work that developed the concept by adding behavioral explanations for differences between the short-term and long-term returns while also attempting to link the term structure of equity and the bond yield curve. The study examines these influences by running t-tests and regressions on dividend strip and S&P 500 return data (1996-2017) and attention data collected by Bloomberg (2010-2017). The results provide some insight into how these variables influence short-term and long-term returns; however, limited instances …