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- Creators: Barrett, The Honors College
Description
In January 2016, Chinese regulators announced the use of circuit breakers to stabilize the stock market but suspended this mechanism after two weeks. Researchers want to further understand the unique characteristics of Chinese stock market and measure the feasibility of implementing a circuit breaker in China once again. The thesis provides an overview of China's attempted implementation and its related consequences, followed by possible problems and tentative recommendations. It outlines key characteristics among different nations that are implementing circuit breakers and price limit systems. Circuit breaker policies in the United States and Japan are explained in detail, while policies in other nations are presented as an overall trend.
ContributorsLiu, Luyao (Co-author) / Zhang, Zihan (Co-author) / Simonson, Mark (Thesis director) / Aragon, George (Committee member) / School of Accountancy (Contributor) / Department of Finance (Contributor) / Barrett, The Honors College (Contributor)
Created2017-05
Description
Every day, millions of messages are posted across various social media channels, creating a golden opportunity for diligent stock traders. This "big data" can be overwhelming, yet incredibly powerful when analyzed properly. The Effect of Social Media on Stock Prices uncovers the ways in which social media messages can trigger abnormal stock price movements, and provides insight into how traders can utilize this information. These findings are organized into a step-by-step action plan that allows traders to formulate trading plans using data from social media channels. This action plan is fueled by an in-depth look at the stock market and social media industries, an analysis of the most important social media channels and messages, and case studies that took place during the duration of this project. This data may used to enable traders to focus on the right messages from the right sources at the right times. By developing the proper criteria for finding, filtering, and analyzing appropriate social media messages, traders can gain an edge in the stock market and increase their profitability.
ContributorsAndrews, Joshua (Author) / Giles, Bret (Thesis director) / Denning, Michael (Committee member) / Barrett, The Honors College (Contributor) / Department of Marketing (Contributor)
Created2015-05
Description
Dr. Dean Kashiwagi created a new thinking paradigm, Information Measurement Theory (IMT), which utilizes the understanding of natural laws to help individuals minimize decision-making and risk, which leads to reduced stress. In this new paradigm, any given situation can only have one unique outcome. The more information an individual has for the given situation, the better they can predict the outcome. Using IMT can help correctly "predict the future" of any situation if given enough of the correct information. A prime example of using IMT would be: to correctly predict what a young woman will be like when she's older, simply look at the young woman's mother. In essence, if you can't fall in love with the mother, don't marry the young woman. The researchers are utilizing the concept of IMT and extrapolating it to the financial investing world. They researched different financial investing strategies and were able to come to the conclusion that a strategy utilizing IMT would yield the highest results for investors while minimizing stress. Investors using deductive logic to invest received, on average, 1300% more returns than investors who did not over a 25-year period. Where other investors made many decisions and were constantly stressed with the tribulations of the market, the investors utilizing IMT made one decision and made much more than other investors. The research confirms the stock market will continue to increase over time by looking at the history of the stock market from a birds-eye view. Throughout the existence of the stock market, there have been highs and lows, but at the end of the day, the market continues to break through new ceilings. Investing in the stock market can be a dark and scary place for the blind investor. Using the concept of IMT can eliminate that blindfold to reduce stress on investors while earning the highest financial return potential. Using the basis of IMT, the researchers predict the market will continue to increase in the future; in conclusion, the best investment strategy is to invest in blue chip stocks that have a history of past success, in order to capture secure growth with minimal risk and stress.
ContributorsBerns, Ryan (Co-author) / Ybanez, Julian (Co-author) / Kashiwagi, Dean (Thesis director) / Kashiwagi, Jacob (Committee member) / Barrett, The Honors College (Contributor) / Department of Finance (Contributor) / Department of Marketing (Contributor) / W. P. Carey School of Business (Contributor)
Created2015-05
Description
This paper seeks to emphasize how the presence of uncertainty, speculation and leverage work in concert within the stock market to exacerbate crashes in a cyclical market. It analyzes three major stock market events: the crash of Oct. 19, 1987, “Black Monday;” the dotcom bust, from 1999 to 2002; and the subprime mortgage crisis, from 2007 to 2010. Within each event period I define determinants or measurements of uncertainty, speculation. Analysis of how these three concepts functioned during boom and bust will highlight how their presence can amplify the magnitude of a crash. This paper postulates that the amount of leverage during a crash determines how long-term its effects will be. This theory is fortified by extensive research and interviews with experts in the stock market who had a front row view of the discussed crises.
ContributorsGraff, Veronica Camille (Author) / Leckey, Andrew (Thesis director) / Cohen, Sarah (Committee member) / Historical, Philosophical & Religious Studies (Contributor) / Walter Cronkite School of Journalism & Mass Comm (Contributor, Contributor) / Dean, W.P. Carey School of Business (Contributor) / Barrett, The Honors College (Contributor)
Created2019-05
Description
Commercial real estate is tied to the macro conditions of the overall economy. In particular, the paper seeks to relate commercial real estate to alternative investments such as the 10-year treasury and the S&P 500 in the stock market by examining trends over the thirty-year period of 1979-2009. There will be comprehensive analysis, interpretation, and discussion of the national cap rate, the 10-year treasury, and the S&P 500 E/P ratio during the period. By analyzing past economic events and how the 10-year, S&P 500 E/P ratio, and cap rates move, the hope is to identify patterns and leading indicators to provide better insight into future events and behavior of commercial real estate and the stock market. The main intent is to provide the reader with the tools to assess the current market. In doing so, it is then possible to relate the current market with the past and with some degree of accuracy, predict where the market is headed. With such knowledge, investors can more aptly time and allocate their funds in order to maximize their returns.
ContributorsMillstein, Ethan David (Author) / Davis, Joseph (Thesis director) / Bronska, Michael (Committee member) / Barrett, The Honors College (Contributor) / Department of Finance (Contributor) / W. P. Carey School of Business (Contributor)
Created2014-05
Description
This paper investigates whether measures of investor sentiment can be used to predict future total returns of the S&P 500 index. Rolling regressions and other statistical techniques are used to determine which indicators contain the most predictive information and which time horizons' returns are "easiest" to predict in a three year data set. The five "most predictive" indicators are used to predict 180 calendar day future returns of the market and simulated investment of hypothetical accounts is conducted in an independent six year data set based on the rolling regression future return predictions. Some indicators, most notably the VIX index, appear to contain predictive information which led to out-performance of the accounts that invested based on the rolling regression model's predictions.
ContributorsDundas, Matthew William (Author) / Boggess, May (Thesis director) / Budolfson, Arthur (Committee member) / Hedegaard, Esben (Committee member) / Barrett, The Honors College (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / Department of Finance (Contributor)
Created2013-12
Description
The goal of this paper is to document a relation between the price of a company's stock and release of public information. I examine how accounting scandals and earnings reports change the price of a company's stock. I run my data through EVENTUS and check for statistical significance. If there is a statistical significance, then it can be stated that accounting information matters. The test results from my study revealed that there was no statistical significance between accounting scandal and stock market prices but there did exist a positive correlation between surprise earning announcements and stock market prices.
ContributorsWollaston, Millicent Mary (Author) / Smith, Geoffrey (Thesis director) / Call, Andrew (Committee member) / School of Mathematical and Statistical Sciences (Contributor) / School of Accountancy (Contributor) / Barrett, The Honors College (Contributor)
Created2016-12
Description
Millennial involvement levels in the stock market are startlingly low. But what has caused this disconnect between America's younger generation and the financial sector? Stress from past financial crises, distrust of Wall Street, corporate greed, or a dislike of capitalism could surely all be viable culprits. Through our mutual experiences and research, however, we have found that most millennials aren't cynical anarchists avoiding the stock market in an attempt to fight against the system. Rather, they are individuals who have the desire to learn about investing but are clueless as to where/how to start. We both began investing in the stock market early in our college careers by opening online brokerage accounts and developing investment portfolios based on knowledge we learned within our Finance degrees and through independent research. Word of our involvement in the stock market began to spread in our social circles and people would consistently approach either of us and ask a variety of questions regarding investing. Questions such as: Can you sit down and help me open up an account and pick some stocks? What type of things do you invest in? How do I get started? How much money have you made? (always a favorite). Pre-med students, engineers, business, science, and technology majors alike all showed interest in the stock market. The more and more we talked to people, the more we realized that the problem was not a lack of desire or a lack of intellect. The problem was a lack of logically presented information, and barriers to entry that were far too high. We want to fix that. Investnet will be an online educational platform that will teach anyone the basics of investing, in plain, easy to understand terms. Whether the individual has absolutely zero knowledge of finances, or has some familiarity with investing, Investnet will provide them with the knowledge and confidence necessary to start investing in the stock market (or choose not to, but at least they'll know how).
ContributorsMcKenzie, Connor (Co-author) / Shatila, Jordan (Co-author) / Budolfson, Arthur (Thesis director) / Hoffman, David (Committee member) / School of Mathematical and Statistical Sciences (Contributor) / Department of Finance (Contributor) / W. P. Carey School of Business (Contributor) / Economics Program in CLAS (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
Description
The Covid-19 pandemic has made a significant impact on both the stock market and the<br/>global economy. The resulting volatility in stock prices has provided an opportunity to examine<br/>the Efficient Market Hypothesis. This study aims to gain insights into the efficiency of markets<br/>based on stock price performance in the Covid era. Specifically, it investigates the market’s<br/>ability to anticipate significant events during the Covid-19 timeline beginning November 1, 2019<br/><br/>and ending March 31, 2021. To examine the efficiency of markets, our team created a Stay-at-<br/>Home Portfolio, experiencing economic tailwinds from the Covid lockdowns, and a Pandemic<br/><br/>Loser Portfolio, experiencing economic headwinds from the Covid lockdowns. Cumulative<br/>returns of each portfolio are benchmarked to the cumulative returns of the S&P 500. The results<br/>showed that the Efficient Market Hypothesis is likely to be valid, although a definitive<br/>conclusion cannot be made based on the scope of the analysis. There are recommendations for<br/>further research surrounding key events that may be able to draw a more direct conclusion.
ContributorsBrock, Matt Ian (Co-author) / Beneduce, Trevor (Co-author) / Craig, Nicko (Co-author) / Hertzel, Michael (Thesis director) / Mindlin, Jeff (Committee member) / Department of Finance (Contributor) / Economics Program in CLAS (Contributor) / WPC Graduate Programs (Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
Description
This study aims to combine the wisdom of crowds with ML to make more accurate stock price predictions for a select set of stocks. Different from prior works, this study uses different input elicitation techniques to improve crowd performance. In addition, machine learning is used to support the crowd. The influence of ML on the crowd is tested by priming participants with suggestions from an ML model. Lastly, the market conditions and stock popularity is observed to better understand crowd behavior.
ContributorsBhogaraju, Harika (Author) / Escobedo, Adolfo R (Thesis director) / Meuth, Ryan (Committee member) / Barrett, The Honors College (Contributor) / Computer Science and Engineering Program (Contributor)
Created2022-12