Portfolio and Security Analysis Commons^™

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 …

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 …

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 …

The Startup Ecosystem In Southern Nevada: Growth, Energy, And Emerging Entrepreneurship In 2025, Len Jessup, Sean Curry

Policy Briefs and Reports

The startup ecosystem in Southern Nevada has undergone significant transformation during the past decade, evolving from a fragmented and nascent environment into a dynamic and increasingly coordinated landscape. This study examines the growth of the Southern Nevada startup ecosystem, analyzing key components such as funding sources, incubators, accelerators, and public-private collaborations. Utilizing both quantitative and qualitative data, including investment trends, economic impact reports, and interviews with over 100 stakeholders, this policy brief provides a comprehensive assessment of the strengths and gaps within the ecosystem. Key findings indicate that while the region has made substantial progress, particularly in fostering early-stage investments …

U.S. Options Exchange-Traded Funds: Performance Dynamics And Managerial Expertise, Elroi Hadad, Davinder K. Malhotra, Robert Mcleod

School of Business Faculty Papers

This study examines the performance dynamics of U.S. options exchange-traded funds (ETFs), whose investment strategy involves options contracts. Analyzing monthly returns data from February 2014 to April 2023, we evaluate the risk-adjusted performance, volatility, and market sensitivity of U.S. options ETFs relative to U.S. and global equities. Using Carhart's four-factor model, we find that U.S. options ETFs yield lower monthly returns than those of U.S. equities but outperform global equities, suggesting potential diversification benefits. While U.S. options ETFs underperformed during the COVID-19 pandemic, they demonstrated resilience thereafter, offering higher rewards for downside risk. We also find that managerial expertise may …

Mortgage Default Classification Modeling For Variable Analysis, Brendan R. Goggins

Honors College Theses

The financial crisis of the early 2000’s is a prime example of the severe consequences that mortgage default and borrower insolvency can have on economies at large. Mortgage default specifically is a prime case with the popularization of mortgage backed securities and the commonality of this loan structure. Multiple hypotheses and models have been formed to understand the reasons, causes, and consequences of mortgage default. This paper uses both machine learning and statistical classification models to inform an understanding of the variables most significant and impactful to the default outcome of mortgages. Consideration is given to both loan-level microeconomic variables …

Experimental Methods In Predicting Market Drift And Other Portfolio Optimization Factors Using Graph Theory, Perry Harrison Zhang

Computer Science Senior Theses

No abstract provided.

Balancing Perspectives: Assessing The Integration Of Ai In Academic Support Within Higher Education, Sami Ali

2024 Spring Honors Capstone Projects - Archive

The rapid advancement of A The rapid proliferation of Artificial Intelligence (AI) across various sectors highlights its transformative potential, yet its integration into educational settings raises ethical concerns, particularly regarding its misuse by students. This study conducts a detailed sentiment analysis and systematic literature review to examine the diverse perspectives on AI within education, from both academic and non-academic viewpoints. Utilizing advanced data mining tools to analyze sentiments and trends, this research reveals a complex landscape where optimism about AI’s capabilities is tempered by concerns over ethical implications and potential misuse. The findings contribute to the dialogue on leveraging AI …

Financial Consulting Internship In Valencia: Alternative Investments And Ai, Mason Sidney Rike

Finance Undergraduate Honors Theses

During the summer before my senior year, I had the opportunity to work as a research analyst in the finance department of TuaTeam, a financial and strategic consulting firm in Valencia, Spain. TuaTeam is a relatively new firm that serves its clients in a wide range of areas, from strategic restructuring and business model development to finding funding for future projects and identifying/evaluating potential investment opportunities. TuaTeam also works closely with communities around Spain to foster innovation and development among youth and professionals seeking to gain experience in new trends in technology and cultural enrichment. The company currently holds classes …

"Reconstitute": Business Plan Of A Start-Up Art Invsetment Bussiness: Artvest, Jianing Wang

MA Projects

Art is still used as a financial hedge in times of economic uncertainty. According to Artnet’s Financial Art Index, “The art market outperformed the S&P 500 from January 2022 to July 2023, with art returns rising by 4.2% in nominal terms, while the S&P 500 lost 6.6% during the same period.” 1 Although we are currently in a period of uncertainty about the future global economic outlook, the impact of fluctuations in art prices is relatively low. ArtVest will establish against post-pandemic New York in 2024, seamlessly bridging the realms of art and investment. ArtVest recognizes the potential in the …

Project Planning And Control, Burim Isa Berisha Dr.Sc

International Journal of Business and Technology

Operations management is important because it relates to the creation of products and services on which we are all dependent. Operations management is also quite motivating; operations are the center of many changes that affect business - changes in customer preferences, changes in the supply chain caused by technologies based on the businesses where we work, where we want to work and so on.

Operations Management includes the role of operations management, the various characteristics of processes, management activities, the responsibilities of managers, and the timely evolution of Operations Management.

Operations Management is a constant change, fostering creativity which allows …

Management Of Small Enterprises And Family Businesses In The Republic Of Kosovo, Burim Isa Berisha Dr.Sc, Burim Berisha B.B

International Journal of Business and Technology

Small businesses represent the driving force of an economy. They are the key that enables the production and marketing of thousands of products and services thus becoming the basis for a sound economic development. Consequently, small businesses are of vital importance to the economy.

Small business is a generator of innovation and a source of new jobs. The trend shows that small businesses are the backbone of all developments and movements in the economic system.

The small business scope is present in almost every pore of social and economic life.

According to the Statistical Register for Businesses, there are 9,358 …

Forecasting Stock Indices With The Covid-19 Infection Rate As An Exogenous Variable, Mohammad Saha A. Patwary

School of Computing and Informatics

Forecasting stock market indices is challenging because stock prices are usually nonlinear and non- stationary. COVID-19 has had a significant impact on stock market volatility, which makes forecasting more challenging. Since the number of confirmed cases significantly impacted the stock price index; hence, it has been considered a covariate in this analysis. The primary focus of this study is to address the challenge of forecasting volatile stock indices during Covid-19 by employing time series analysis. In particular, the goal is to find the best method to predict future stock price indices in relation to the number of COVID-19 infection rates. …

Analyzing The Relationship Between Return And Trading Volume In Relation To Cross-Sectional Absolute Deviation (Csad) In Order To Detect Herding Behavior In Indonesia Emerging Stock Market, Helma Malini, Annisa Dipa Sakliana

The Indonesian Capital Market Review

Investor herding behavior is a primary source of speculative bubbles since it implies that investors make identical trading decisions, which can lead to stock prices deviating from their underlying worth. The goal of this study is to detect herding behavior in the Indonesian stock market between 2016 and 2021. The relationship between return and trading volume, known as Cross Sectional Absolute Deviation, is used to assess herding behavior (CSAD). Time-series regression and quantile regression analysis will be employed as data analytic techniques in this study to investigate herding behavior under various market scenarios. Herding behavior is evident in the Indonesian …

Bnsf Strategic Analysis, Bella Tran

Honors Program: Senior Projects (Public)

Burlington Northern Santa Fe, LLC. (BNSF), is an American railroad that is concentrated in the western two-thirds of the U.S. This railroad has a history stretching back over a century that has led the company to now function as one of the leading Class I Railroad with over 30,000 employees and over 30,000 miles of laid track. Two methods of analysis were used to examine the competitive environment in which BNSF operates. The first is the PESTEL analysis which examines the macro-environment. The second is Porter’s Five Forces which analyzes the competitive environment of an industry. The analyses concluded that …

A Strategic Audit Of Seaworld, Rachel Jendro

Honors Program: Senior Projects (Public)

This project is a strategic audit for SeaWorld Entertainment. The purpose of this report is to analyze the firm through multiple different perspectives and analyze the competitive advantage the business is pursuing. The project considers internal and external environments, strategic leadership, organizational structure, and resources to determine if and what type of competitive advantage the firm holds. Furthermore, it considers current events and strategic decisions, and how those relate to the overall strategy. A strategic audit is crucial to understanding the innerworkings of a firm. The factors that were analyzed are interconnected and performing a strategic audit can allow for …

The Analysis Of The Roles Of Bitcoin, Ethereum, And Gold As Hedge And Safe-Haven Assets On The Indonesian Stock Market Before And During The Covid-19 Pandemic, Carla A. Wijaya, Maria Ulpah

The Indonesian Capital Market Review

The uncertainty due to the COVID-19 outbreak has encouraged investors to look for value hedging instruments to minimize risk, which can be in the form of hedging assets or safe-haven assets. In response to it, this study aims to find out whether Bitcoin, Ethereum, and gold can behave as hedging and safe-haven assets before and amid the pandemic in Indonesia. The strategy is by observing the effects of volatility and return of Bitcoin, Ethereum, and gold on the Indonesian stock market. This study employed both quantile regression and simple linear regression models on data of daily closing price taken before …

Modeling The Impact Of Adding Cryptocurrency In A Portfolio, Ashley Pineault

Honors Theses and Capstones

This study examines the backgrounds of Bitcoin and Ethereum. How they came about, where they differ from one another in functions, and what investors believe will be a better cryptocurrency stock as an investment to include in an optimized portfolio. It will also study the impact of adding two leading cryptocurrencies, Bitcoin and Ethereum, into a hypothetical, optimal investment portfolio. Data collection includes the adjusted closing price of 30 diversified stocks from 2016 to 2021. Those adjusted closing prices are the beginning of determining the optimal portfolio for three separate portfolios. One has the Ethereum cryptocurrencies, the other has Bitcoin …

Co-Jumps, Co-Jump Tests, And Volatility Forecasting: Monte Carlo And Empirical Evidence, Weijia Peng, Chun Yao

WCBT Faculty Publications

This study classifies jumps into idiosyncratic jumps and co-jumps to quantitatively identify systematic risk and idiosyncratic risk by utilizing high-frequency data. We found that systematic risk occurs more frequently and has larger magnitudes than the idiosyncratic risk in an individual asset, which indicates that volatilities from one sector are largely derived from the contagious effect of other sectors. We further investigated the importance of idiosyncratic jumps and co-jumps to predict the sector-level S&P500 exchange-traded fund (ETF) volatility. It was found that the predictive content of co-jumps is higher than that of idiosyncratic jumps, suggesting that systematic risk is more informative …

Stock Market Manipulation Detection Using Continuous Wavelet Transform & Machine Learning Classification, Sarah Youssef

Theses and Dissertations

Stock market manipulation detection is important for both investors and regulators. Being able to detect stock manipulation and preventing it gives investors the confidence in the market fairness and integrity. It also helps maintaining liquidity of the stocks and market efficiency. Implementing data mining algorithms in manipulation detection is a relatively recent technique but in the past few years there has been an increasing interest in it's applications in this domain. The benefit of monitoring manipulative trade behavior is that it can be implemented on live feed of stock data, which saves a lot of time in detecting stock price …

Stock Trend Prediction Using Candlestick Charting And Ensemble Machine Learning Techniques With A Novelty Feature Engineering Scheme, Yaohu Lin, Shancun Liu, Haijun Yang, Harris Wu

Information Technology & Decision Sciences Faculty Publications

Stock market forecasting is a knotty challenging task due to the highly noisy, nonparametric, complex and chaotic nature of the stock price time series. With a simple eight-trigram feature engineering scheme of the inter-day candlestick patterns, we construct a novel ensemble machine learning framework for daily stock pattern prediction, combining traditional candlestick charting with the latest artificial intelligence methods. Several machine learning techniques, including deep learning methods, are applied to stock data to predict the direction of the closing price. This framework can give a suitable machine learning prediction method for each pattern based on the trained results. The investment …

The Relative Industry Specific Effects Of Covid-19 On Market Volatility And Liquidity, Callin Christensen

All Graduate Plan B and other Reports, Spring 1920 to Spring 2023

Understanding how historical events affect market volatility and liquidity can provide crucial information to financial analysts, investment professionals, and managers in the event that similar circumstances resurface. In this study, I look at how a global pandemic (COVID-19) can introduce frictions into the market and cause disrupt the generation or flow of available information, this could cause prices to deviate significantly from their equilibrium values. I also hypothesize that these inefficiencies may have a greater effect on some industries than others. My analysis seems to confirm this hypothesis. I observe that the global COVID-19 pandemic leads to statistically significant increases …

A Little Birdy Told Me: Analysis Of The Impact Of Public Tweet Sentiment On Stock Prices, Alexander Novitsky

CMC Senior Theses

The combination of the advent of the internet in 1983 with the Securities and Exchange Commission’s ruling allowing firms the use of social media for public disclosures merged to create a wealth of user data that traders could quickly capitalize on to improve their own predictive stock return models. This thesis analyzes some of the impact that this new data may have on stock return models by comparing a model that uses the Index Price and Yesterday’s Stock Return to one that includes those two factors as well as average tweet Polarity and Subjectivity. This analysis is done with ten …

Behavioral Agent-Based Framework For Interacting Financial Markets, Heba M. Ezzat Dr.

Business Administration

Purpose – This paper aims at developing a behavioral agent-based model for interacting financial markets. Additionally, the effect of imposing Tobin taxes on market dynamics is explored. Design/methodology/approach – The agent-based approach is followed to capture the highly complex, dynamic nature of financial markets. The model represents the interaction between two different financial markets located in two countries. The artificial markets are populated with heterogeneous, boundedly rational agents. There are two types of agents populating the markets; market makers and traders. Each time step, traders decide on which market to participate in and which trading strategy to follow. Traders can …

Improving Vix Futures Forecasts Using Machine Learning Methods, James Hosker, Slobodan Djurdjevic, Hieu Nguyen, Robert Slater

SMU Data Science Review

The problem of forecasting market volatility is a difficult task for most fund managers. Volatility forecasts are used for risk management, alpha (risk) trading, and the reduction of trading friction. Improving the forecasts of future market volatility assists fund managers in adding or reducing risk in their portfolios as well as in increasing hedges to protect their portfolios in anticipation of a market sell-off event. Our analysis compares three existing financial models that forecast future market volatility using the Chicago Board Options Exchange Volatility Index (VIX) to six machine/deep learning supervised regression methods. This analysis determines which models provide best …

Are Women Executives Hurting Firm Performance? An Examination Of Gender Diversity On Firm Risk, Performance, And Executive Compensation, Krystal Diane Sung

CMC Senior Theses

In order to assess the continuing imbalance of top executives between genders, I examine the effects of gender diversity within top management teams on firm risk, performance, and executive compensation. Capitalizing on previous analysis, I apply three unique differentiators. First, I utilize current data from 2012 to 2017 from Compustat, CRSP, and ExecuComp. Second, I provide a unique subset view on a firm and individual performance of female CEOs to examine executive compensation. Third, my scope of analysis expands to S&P Composite 1500 companies. I use separate models to estimate the effect of gender diversity on firm risk by examining …

Disposition Effect And Multi-Asset Market Dynamics, Heba M. Ezzat Dr.

Business Administration

Purpose – Asset pricing dynamics in a multi-asset framework when investors’ trading exhibits the disposition effect is studied. The purpose of this paper is to explore asset pricing dynamics and the switching behavior among multiple assets. Design/methodology/approach – The dynamics of complex financial markets can be best explored by following agent-based modeling approach. The artificial financial market is populated with traders following two heterogeneous trading strategies: the technical and the fundamental trading rules. By simulation, the switching behavior among multiple assets is investigated. Findings – The proposed framework can explain important stylized facts in financial time series, such as random …

Strategic Implications Of Blockchain, William R. Adams

Marriott Student Review

This thesis introduces blockchain, the underlying technology of cryptocurrencies such as Bitcoin, and discusses how best to conceptualize it relative to other technologies. Following an explanation of the fundamentals of blockchain, also known as the distributed ledger, I identify the characteristics of the technology. Building upon blockchain’s inherent strengths and limitations, I explore potential business applications of blockchain. Finally, I recommend that leaders continue to track the development and adoption of blockchain technology, even if they decide that implementing it does not align with their organization’s strategy at present.

The Emerging International Taxation Problems, James G. Yang, Victor N.A. Metallo

Department of Accounting and Finance Faculty Scholarship and Creative Works

The problems of tax evasion and tax avoidance are as old as taxes themselves. Between 2015 and 2016 alone, many U.S. multinational corporations were involved in tax disputes with the European Commission. From a historical perspective, these disputes are unprecedented as they have resulted in tremendous amount of tax penalties. The most notable case was Apple for €13 billion of unpaid tax. This article discusses what tax strategies these corporations used that caused such disputes. It specifically investigates seven corporations: Apple Inc., McDonald’s, Starbucks, Fiat, Amazon, Google, and Ikea, and elaborates on the following tax strategies: high royalties, intercompany transfer …

Loss Aversion, Adaptive Beliefs, And Asset Pricing Dynamics, Kamal Samy Selim Prof, Ahmed Eltabee Okasha Dr., Heba M. Ezzat Dr.

Business Administration

We study asset pricing dynamics in artificial financial markets model. The financial market is populated with agents following two heterogeneous trading beliefs, the technical and the fundamental prediction rules. Agents switch between trading rules with respect to their past performance. The agents are loss averse over asset price fluctuations. Loss aversion behaviour depends on the past performance of the trading strategies in terms of an evolutionary fitness measure. We propose a novel application of the prospect theory to agent-based modelling, and by simulation, the effect of evolutionary fitness measure on adaptive belief system is investigated. For comparison, we study pricing …