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Application Of Randomness In Finance, Jose Sanchez, Daanial Ahmad, Satyanand Singh 2021 CUNY New York City College of Technology

Application Of Randomness In Finance, Jose Sanchez, Daanial Ahmad, Satyanand Singh

Publications and Research

Brownian Motion which is also considered to be a Wiener process and can be thought of as a random walk. In our project we had briefly discussed the fluctuations of financial indices and related it to Brownian Motion and the modeling of Stock prices.


Cointegration And Statistical Arbitrage Of Precious Metals, Judge Van Horn 2021 University of Arkansas, Fayetteville

Cointegration And Statistical Arbitrage Of Precious Metals, Judge Van Horn

Finance Undergraduate Honors Theses

When talking about financial instruments correlation is often thrown around as a measure of the relation between two securities. An often more useful or tradeable measure is cointegration. Cointegration is the measure of two securities tendency to revert to an average price over time. In other words, cointegration ignores directionality and only cares about the distance between two securities. For a mean reversion strategy such as statistical arbitrage cointegration proves to be a far more reliable statistical measure of mean reversion, and while it is more reliable than correlation it still has its own problems. One thing to consider is ...


Applying Emotional Analysis For Automated Content Moderation, John Shelnutt 2021 University of Arkansas, Fayetteville

Applying Emotional Analysis For Automated Content Moderation, John Shelnutt

Computer Science and Computer Engineering Undergraduate Honors Theses

The purpose of this project is to explore the effectiveness of emotional analysis as a means to automatically moderate content or flag content for manual moderation in order to reduce the workload of human moderators in moderating toxic content online. In this context, toxic content is defined as content that features excessive negativity, rudeness, or malice. This often features offensive language or slurs. The work involved in this project included creating a simple website that imitates a social media or forum with a feed of user submitted text posts, implementing an emotional analysis algorithm from a word emotions dataset, designing ...


Use Of Linear Discriminant Analysis In Song Classification: Modeling Based On Wilco Albums, Caroline Pollard 2021 University of Mississippi

Use Of Linear Discriminant Analysis In Song Classification: Modeling Based On Wilco Albums, Caroline Pollard

Honors Theses

The study of music recommender algorithms is a relatively new area of study. Although these algorithms serve a variety of functions, they primarily help advertise and suggest music to users on music streaming services. This thesis explores the use of linear discriminant analysis in music categorization for the purpose of serving as a cheaper and simpler content-based recommender algorithm. The use of linear discriminant analysis was tested by creating lineardiscriminant functions that classify Wilco’s songs into their respective albums, specifically A.M., Yankee Hotel Foxtrot, and Sky Blue Sky. 4 sample songs were chosen from each album, and song ...


Using Machine Learning To Track The Location Of The Shock Train In Hypersonic Engines, Alison Reynolds 2021 William & Mary

Using Machine Learning To Track The Location Of The Shock Train In Hypersonic Engines, Alison Reynolds

Undergraduate Honors Theses

Proposed hypersonic vehicles would be able to travel at five to ten times the speed of sound, but there are still many problems that need to be solved to construct a functioning vehicle. One such problem involves shocks created in the engine isolator when the vehicle reaches high speeds. These shocks must be contained to the isolator to maximize performance and avoid potential failure. This project attempts to track the location of the leading shock given images of airflow from ground tests of engines using random forests and convolutional neural networks. When the models are trained and tested on data ...


How Risk-Related Statistics, As Reported In News And Social Media, Are Linked To The Use Of The Public Transit System, Prashiddhi Pokhrel 2021 University of Southern Maine

How Risk-Related Statistics, As Reported In News And Social Media, Are Linked To The Use Of The Public Transit System, Prashiddhi Pokhrel

Thinking Matters Symposium

Due to the pandemic, people have started relying more on televisions, news, social media, and other news outlets for guidance. Moreover, with the increasing amount of news, data, and information there is also an increase in the amount of misleading statistics. People’s opinions and decisions significantly depend on the data, statistics, and information that they are exposed to, as well as their sources. For this project, we want to look at how information and its sources are affecting the decision made by the general public for the usage of the Portland Transit System. It is very important to know ...


Conjunction Of Factors Impacting The 2019-2020 Flu Season In The Us, Yichen Wang 2021 University of Minnesota - Morris

Conjunction Of Factors Impacting The 2019-2020 Flu Season In The Us, Yichen Wang

Undergraduate Research Symposium 2021

The 2019-2020 flu season is regarded as one of the most serious ones in decades. Previous researchers usually studied the effects of different factors on seasonal flu separately instead of their conjugate impact, so we wanted to find how multiple factors combine to affect the spread of influenza in the 2019-2020 flu season in America. We chose types of virus (A and B), environmental factors (temperature, precipitation, relative humidity), population density, and influenza vaccination status for different age groups which are statewide data containing monthly information from Sep. 2019 to May 2020. By principal component analysis, we could see the ...


Geometric Representation Learning, Luke Vilnis 2021 University of Massachusetts Amherst

Geometric Representation Learning, Luke Vilnis

Doctoral Dissertations

Vector embedding models are a cornerstone of modern machine learning methods for knowledge representation and reasoning. These methods aim to turn semantic questions into geometric questions by learning representations of concepts and other domain objects in a lower-dimensional vector space. In that spirit, this work advocates for density- and region-based representation learning. Embedding domain elements as geometric objects beyond a single point enables us to naturally represent breadth and polysemy, make asymmetric comparisons, answer complex queries, and provides a strong inductive bias when labeled data is scarce. We present a model for word representation using Gaussian densities, enabling asymmetric entailment ...


Netsci High: Bringing Agency To Diverse Teens Through The Science Of Connected Systems, Stephen M. Uzzo, Catherine B. Cramer, Hiroki Sayama, Russell Faux 2021 New York Hall of Science

Netsci High: Bringing Agency To Diverse Teens Through The Science Of Connected Systems, Stephen M. Uzzo, Catherine B. Cramer, Hiroki Sayama, Russell Faux

Northeast Journal of Complex Systems (NEJCS)

This paper follows NetSci High, a decade-long initiative to inspire teams of teenage researchers to develop, execute and disseminate original research in network science. The project introduced high school students to the computer-based analysis of networks, and instilled in the participants the habits of mind to deepen inquiry in connected systems and statistics, and to sustain interest in continuing to study and pursue careers in fields involving network analysis. Goals of NetSci High ranged from proximal learning outcomes (e.g., increasing high school student competencies in computing and improving student attitudes toward computing) to highly distal (e.g., preparing students ...


Analysis And Publication Profile Of Indonesian Scientific Work In 2020 Based On The Scopus Database, Akbar Iskandar, Nico Djundharto Djajasinga, Andi Dirga Noegraha, Erwin Gatot, Ansari Saleh Ahmar 2021 Universitas Negeri Yogyakarta, Yogyakarta, Indonesia

Analysis And Publication Profile Of Indonesian Scientific Work In 2020 Based On The Scopus Database, Akbar Iskandar, Nico Djundharto Djajasinga, Andi Dirga Noegraha, Erwin Gatot, Ansari Saleh Ahmar

Library Philosophy and Practice (e-journal)

This research was conducted to identify and describe the profile of publications in Indonesia in 2020. This research used the bibliometric methods. The data in this research were collected by searching through the Scopus database with the keywords: AFFILCOUNTRY “Indonesia” and PUBYEAR “2020” with the exception of AFFILCOUNTRY other than “Indonesia”. Data were then analyzed based on author affiliation, subject, document type, source type, source title, and language. The results of the research indicated that the development of Indonesian scientific publications was dominated by article types (50.69%) and conference papers (45.83%) with the subject area of publication dominated ...


Nondominant Hand Computer Mouse Training And The Bilateral Transfer Effect To The Dominant Hand, Drew Schweiger, Richard T. Stone, Ulrike Genschel 2021 Iowa State University

Nondominant Hand Computer Mouse Training And The Bilateral Transfer Effect To The Dominant Hand, Drew Schweiger, Richard T. Stone, Ulrike Genschel

Industrial and Manufacturing Systems Engineering Publications

This study explored the effects of training computer mouse use in the nondominant hand on clicking performance of the dominant and nondominant hands. Computer mouse use is a daily operation in the workplace and requires minute hand and wrist movements developed and refined through practice and training for many years. Our study had eleven right-handed computer mouse users train their nondominant hand for 15 min a day, five days per week, for six weeks. This study found improved performance with the computer mouse in the dominant hand following nondominant hand training because of the bilateral transfer effect of training. Additionally ...


The Mean-Reverting 4/2 Stochastic Volatility Model: Properties And Financial Applications, Zhenxian Gong 2021 The University of Western Ontario

The Mean-Reverting 4/2 Stochastic Volatility Model: Properties And Financial Applications, Zhenxian Gong

Electronic Thesis and Dissertation Repository

Financial markets and instruments are continuously evolving, displaying new and more refined stylized facts. This requires regular reviews and empirical evaluations of advanced models. There is evidence in literature that supports stochastic volatility models over constant volatility models in capturing stylized facts such as "smile" and "skew" presented in implied volatility surfaces. In this thesis, we target commodity and volatility index markets, and develop a novel stochastic volatility model that incorporates mean-reverting property and 4/2 stochastic volatility process. Commodities and volatility indexes have been proved to be mean-reverting, which means their prices tend to revert to their long term ...


Sars-Cov-2 Pandemic Analytical Overview With Machine Learning Predictability, Anthony Tanaydin, Jingchen Liang, Daniel W. Engels 2021 Southern Methodist University

Sars-Cov-2 Pandemic Analytical Overview With Machine Learning Predictability, Anthony Tanaydin, Jingchen Liang, Daniel W. Engels

SMU Data Science Review

Understanding diagnostic tests and examining important features of novel coronavirus (COVID-19) infection are essential steps for controlling the current pandemic of 2020. In this paper, we study the relationship between clinical diagnosis and analytical features of patient blood panels from the US, Mexico, and Brazil. Our analysis confirms that among adults, the risk of severe illness from COVID-19 increases with pre-existing conditions such as diabetes and immunosuppression. Although more than eight months into pandemic, more data have become available to indicate that more young adults were getting infected. In addition, we expand on the definition of COVID-19 test and discuss ...


Bias Of Rank Correlation Under A Mixture Model, Russell Land 2021 Georgia Southern University

Bias Of Rank Correlation Under A Mixture Model, Russell Land

Electronic Theses and Dissertations

This thesis project will analyze the bias in mixture models when contaminated data is present. Specifically, we will analyze the relationship between the bias and the mixing proportion, p, for the rank correlation methods Spearman’s Rho and Kendall’s Tau. We will first look at the history of the two non-parametric rank correlation methods and the sample and population definitions will be introduced. Copulas will be introduced to show a few ways we can define these correlation methods. After that, mixture models will be defined and the main theorem will be stated and proved. As an example, we will ...


Neither “Post-War” Nor Post-Pregnancy Paranoia: How America’S War On Drugs Continues To Perpetuate Disparate Incarceration Outcomes For Pregnant, Substance-Involved Offenders, Becca S. Zimmerman 2021 Pitzer College

Neither “Post-War” Nor Post-Pregnancy Paranoia: How America’S War On Drugs Continues To Perpetuate Disparate Incarceration Outcomes For Pregnant, Substance-Involved Offenders, Becca S. Zimmerman

Pitzer Senior Theses

This thesis investigates the unique interactions between pregnancy, substance involvement, and race as they relate to the War on Drugs and the hyper-incarceration of women. Using ordinary least square regression analyses and data from the Bureau of Justice Statistics’ 2016 Survey of Prison Inmates, I examine if (and how) pregnancy status, drug use, race, and their interactions influence two length of incarceration outcomes: sentence length and amount of time spent in jail between arrest and imprisonment. The results collectively indicate that pregnancy decreases length of incarceration outcomes for those offenders who are not substance-involved but not evenhandedly -- benefitting white pregnant ...


Analysis And Implementation Of The Maximum Likelihood Expectation Maximization Algorithm For Find, Angus Boyd Jameson 2020 University of New Hampshire

Analysis And Implementation Of The Maximum Likelihood Expectation Maximization Algorithm For Find, Angus Boyd Jameson

Student Research Projects

This thesis presents an organized explanation and breakdown of the Maximum Likelihood Expectation Maximization image reconstruction algorithm. This background research was used to develop a means of implementing the algorithm into the imaging code for UNH's Field Deployable Imaging Neutron Detector to improve its ability to resolve complex neutron sources. This thesis provides an overview for this implementation scheme, and include the results of a couple of reconstruction tests for the algorithm. A discussion is given on the current state of the algorithm and its integration with the neutron detector system, and suggestions are given for how the work ...


Bayesian Semi-Supervised Keyphrase Extraction And Jackknife Empirical Likelihood For Assessing Heterogeneity In Meta-Analysis, GUANSHEN WANG 2020 Southern Methodist University

Bayesian Semi-Supervised Keyphrase Extraction And Jackknife Empirical Likelihood For Assessing Heterogeneity In Meta-Analysis, Guanshen Wang

Statistical Science Theses and Dissertations

This dissertation investigates: (1) A Bayesian Semi-supervised Approach to Keyphrase Extraction with Only Positive and Unlabeled Data, (2) Jackknife Empirical Likelihood Confidence Intervals for Assessing Heterogeneity in Meta-analysis of Rare Binary Events.

In the big data era, people are blessed with a huge amount of information. However, the availability of information may also pose great challenges. One big challenge is how to extract useful yet succinct information in an automated fashion. As one of the first few efforts, keyphrase extraction methods summarize an article by identifying a list of keyphrases. Many existing keyphrase extraction methods focus on the unsupervised setting ...


Improved Statistical Methods For Time-Series And Lifetime Data, Xiaojie Zhu 2020 Southern Methodist University

Improved Statistical Methods For Time-Series And Lifetime Data, Xiaojie Zhu

Statistical Science Theses and Dissertations

In this dissertation, improved statistical methods for time-series and lifetime data are developed. First, an improved trend test for time series data is presented. Then, robust parametric estimation methods based on system lifetime data with known system signatures are developed.

In the first part of this dissertation, we consider a test for the monotonic trend in time series data proposed by Brillinger (1989). It has been shown that when there are highly correlated residuals or short record lengths, Brillinger’s test procedure tends to have significance level much higher than the nominal level. This could be related to the discrepancy ...


Confirmative Evaluation: New Cipp Evaluation Model, Tia L. Finney 2020 Wayne State University

Confirmative Evaluation: New Cipp Evaluation Model, Tia L. Finney

Journal of Modern Applied Statistical Methods

Struggling trainees often require a substantial investment of time, effort, and resources from medical educators. An emergent challenge involves developing effective ways to accurately identify struggling students and better understand the primary causal factors underlying their poor performance. Identifying the potential reasons for poor performance in medical school is a key first step in developing suitable remediation plans. The SOM Modified Program is a remediation program that aims to ensure academic success for medical students. The purpose of this study is to determine the impact of modifying the CIPP evaluation model by adding a confirmative evaluation step to the model ...


Quantifying The Simultaneous Effect Of Socio-Economic Predictors And Build Environment On Spatial Crime Trends, Alfieri Daniel Ek 2020 University of Arkansas, Fayetteville

Quantifying The Simultaneous Effect Of Socio-Economic Predictors And Build Environment On Spatial Crime Trends, Alfieri Daniel Ek

Theses and Dissertations

Proper allocation of law enforcement agencies falls under the umbrella of risk terrainmodeling (Caplan et al., 2011, 2015; Drawve, 2016) that primarily focuses on crime prediction and prevention by spatially aggregating response and predictor variables of interest. Although mental health incidents demand resource allocation from law enforcement agencies and the city, relatively less emphasis has been placed on building spatial models for mental health incidents events. Analyzing spatial mental health events in Little Rock, AR over 2015 to 2018, we found evidence of spatial heterogeneity via Moran’s I statistic. A spatial modeling framework is then built using generalized linear ...


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