Business Commons^™

How Information Technology Investment Influences Firm Financial Vulnerability, Andrew S. Miller

Theses and Dissertations

Information technology (IT) investments have increased over the last half-century without clear justification in academic or practice-based literatures. One area that has not been adequately addressed in the past literature is the role of IT investments in mitigating firm financial vulnerability. This dissertation specifically attempts to understand the marginal effects of IT investments on financial vulnerability as defined by firm risk and R&D depreciation. Two research questions are pursued to help explain the role IT investments play in firm financial vulnerability: 1) What is the relationship between IT investments and R&D depreciation? and 2) What is the relationship between IT …

Two Essays On Corporate Finance, Md Noman Hossain

Theses and Dissertations

This dissertation consists of two essays on corporate finance. In my first essay, we investigate whether and, if so, how the information disclosure preferences differ systematically between Republican CEOs and Democrat CEOs in the context of management earnings forecasts. We find that Republican CEOs tend to prefer a less asymmetric information environment than Democrat CEOs, and thus make more frequent, timelier, and more accurate disclosures than Democrat CEOs. Results using the propensity score-matched sample and the difference-in-differences analysis show that our results are unlikely to be driven by potential endogeneity. Our results are robust to controlling for various CEO characteristics, …

Essays In Workplace Safety Issues In Finance, Md Ruhul Amin

Theses and Dissertations

I examine how firms address workplace safety issues considering their value implication. In my first essay, I investigate the relation between workplace safety and inside debt held by the CEO in form of pension benefits and deferred compensation. To mitigate the endogeneity of CEO inside debt design, I exploit variation generated by the implementation of the Internal Revenue Code Section 409A Final Regulations. Consistent with the long-term orientation hypothesis, I find strong evidence of lower establishment-level work-related injuries and illnesses in firms whose CEOs have higher relative inside debt. I also document that CEOs inside debt holdings are associated with …

Two Essays On Finance Of Climate Change, Abdullah Al Masum

Theses and Dissertations

This dissertation consists of two essays on the finance of climate change. In the first essay, we find robust empirical evidence that firms in locations with higher exposure to climate change pay significantly higher spreads on their bank loans. To alleviate the concerns related to using firms’ headquarters in determining climate risk exposure, we exploit the economic link between a firm and its customers and find that the exposure of a firm’s customers to climate risk also adversely affects that firm’s cost of borrowing. In the cross-section, we find that the long-term loans of poorly rated firms drive the effect. …

Trading The Days Vs. Days Of Trading: An Empirical Literature Survey On Calendar Anomalies Across Markets, Mariam Ashraf Kiryakos

Theses and Dissertations

This thesis provides a comprehensive theoretical and empirical review of over five decades of research on two of the most examined calendar anomalies: the day-of-the-week and weekend effect. The expansive literature is classified into five different phases to demonstrate and review the evolution of research on these two seasonal anomalies. It also reconciles empirically the seemingly contradicting evidence documented by prior studies by adopting the lens of Adaptive Market Hypothesis (AMH) and conducting a cross-market analysis on the two calendar anomalies using the headline stock market indices of the ten largest economies by GDP as of 2019. The main methodology …

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 …

An Examination Of The Determinants Of Optimal Corporate Credit Hegde: Perspectives From Firms Listed In Djia30 And Nasdaq100, Dina Rofael

Theses and Dissertations

Raising number of corporate defaults could threaten the financial stability, thus modelling credit risk is a key ingredient of financial stability analysis. This paper tries to answer a specific question regarding the drivers of this risk: idiosyncratic risk (industry-specific or firm-specific) and/or systematic risk (macro-economic specific). As a first step, the paper estimates the optimal hedge ratio based on the interest coverage ratio, that acts as a measure for the probability of default. Against this background, the paper applies one of the fundamental-based models of credit risk, known as hybrid model after estimating the proposed indicator variable. The suggested model …

An Intelligent Market Cycle Detection System, Michael Azer

Theses and Dissertations

The detection of stock market cycles has attracted the attention of finance scholars and market practitioners. Accurately identifying the direction of a market can significantly increase the returns of investors. Despite this importance, conventional methodologies in the literature have predominantly attempted to evaluate the effect of subsets of factors as precedents to stock market cycles and with little agreement on what constitutes critical factors. There seems to be a lack in the literature for a comprehensive study that examines a multitude of factors at the same time on the S&P500 as the laboratory. Factors are categorized into: political events, economic …

Stock Prediction Using Natural Language Processing Sentiment Analysis On News Headlines During Covid-19, Mina Ibrahim

Theses and Dissertations

Stock prediction based on NLP sentiment analysis is one of the most researched topics due to the revenues they generate for investors. Researchers have used various tools to achieve this, especially fundamental and technical analysis based on historical data helped to achieve this target. Due to the technological advancement and abundance of data, the introduction of machine learning tools accelerated that approach. However, as the public mood affects the stock market, the need for another analysis emerged. Natural language processing sentiment analysis on data from various sources was able to capture public events and moods. NLP is one of the …

Stock Markets Performance During A Pandemic: How Contagious Is Covid-19?, Yara Abushahba

Theses and Dissertations

Background and Motivation: The coronavirus (“COVID-19”) pandemic, the subsequent policies and lockdowns have unarguably led to an unprecedented fluid circumstance worldwide. The panic and fluctuations in the stock markets were unparalleled. It is inarguable that real-time availability of news and social media platforms like Twitter played a vital role in driving the investors’ sentiment during such global shock.

Purpose:The purpose of this thesis is to study how the investor sentiment in relation to COVID-19 pandemic influenced stock markets globally and how stock markets globally are integrated and contagious. We analyze COVID-19 sentiment through the Twitter posts and investigate its …

Analysis Of Time-Phased Estimates Accuracy, Budget Profile And Under-Spending In Defense Acquisition Programs, Thinh Q. Tran

Theses and Dissertations

As fiscal resources become more limited due to the expanding range of mission needs, accurate cost estimating and budgeting have become more important than ever before. Accurate cost estimates allow the Department of Defense (DoD) to budget with confidence and to effectively communicate its needs to Congress. This research looks to analyze estimates from Air Force’s programs using Milestone B and Initial Operational Capability as the analysis window. Initial analysis of the linear interpolation of the percent budget change indicates that there is underspending in the earlier stages of acquisition programs’ development cycle. Additionally, looking at the cumulative budget change …

The Impact Of The Capital Market, The Insurance Sector And The Mortgage Finance Sector On Economic Growth In Egypt, 2005-2019, Hana Anis

Theses and Dissertations

This thesis aims to explore the relationship between financial markets and economic growth in Egypt for the 15 years period, starting from 2005 to 2019. The study concentrates on the non-banking financial sector which includes the stock market, the debt market, the mortgage and the insurance sectors. The Vector Autoregressive (VAR) model is utilized to describe the relationship between GDP growth rate, as a proxy for economic growth, and a number of variables from the financial sector. Results of the analysis show that there is a significant relationship and statistical causality between the growth rate and the debt market, represented …

Ai Stock-Screening Methodology For Portfolio Construction, Omar Ahmed Khater

Theses and Dissertations

Selecting profitable stocks is crucial in constructing an all-equity portfolio. Investors need to rely on screening mechanisms to aid investment decision making. New stock selection methods are highly desired, and existing methods are constantly improved. In this research, we investigate the potential of relying on artificial intelligence to guide the stock selection process. The developed model employed genetic algorithms to optimize the selection of screening rules from among a set of widely accepted fundamental indicators. The model robustness and performance are tested using stock market real data over a 14-year period from 2006 till 2019. Based on portfolio quality factors …