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- Machine Learning (3)
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Articles 1 - 21 of 21
Full-Text Articles in Physical Sciences and Mathematics
Towards Algorithmic Justice: Human Centered Approaches To Artificial Intelligence Design To Support Fairness And Mitigate Bias In The Financial Services Sector, Jihyun Kim
CMC Senior Theses
Artificial Intelligence (AI) has positively transformed the Financial services sector but also introduced AI biases against protected groups, amplifying existing prejudices against marginalized communities. The financial decisions made by biased algorithms could cause life-changing ramifications in applications such as lending and credit scoring. Human Centered AI (HCAI) is an emerging concept where AI systems seek to augment, not replace human abilities while preserving human control to ensure transparency, equity and privacy. The evolving field of HCAI shares a common ground with and can be enhanced by the Human Centered Design principles in that they both put humans, the user, at …
Application Of Sentiment Analysis And Machine Learning Techniques To Predict Daily Cryptocurrency Price Returns, Edward Wu
CMC Senior Theses
This paper examines the effects of social media sentiment relating to Bitcoin on the daily price returns of Bitcoin and other popular cryptocurrencies by utilizing sentiment analysis and machine learning techniques to predict daily price returns. Many investors think that social media sentiment affects cryptocurrency prices. However, the results of this paper find that social media sentiment relating to Bitcoin does not add significant predictive value to forecasting daily price returns for each of the six cryptocurrencies used for analysis and that machine learning models that do not assume linearity between the current day price return and previous daily price …
Pakistan's Contribution To The Global Rise In Conventional Pollution, Emily Warner
Pakistan's Contribution To The Global Rise In Conventional Pollution, Emily Warner
CMC Senior Theses
This thesis examines the impact of conventional pollutants on the environment, communities, and individuals in Pakistan. It begins by investigating the causes of conventional pollutants and exploring Pakistan’s agricultural industry, domestic practices, non-renewable energy sources, and industrial practices (the brick industry, leather tanning industry, and textile industry). It then analyzes factors that continue to contribute to conventional pollution in Pakistan such as economic incentives, politics, and traditional practices within industries. Exploring the measures that have been taken by Pakistan and other organizations to decrease conventional pollutants, it then suggests potential opportunities for improvement.
Using Short Bursts To Optimize Redistricting In Georgia, Vedika Vishweshwar
Using Short Bursts To Optimize Redistricting In Georgia, Vedika Vishweshwar
CMC Senior Theses
Identifying extreme outliers in large state spaces is a difficult prob-
lem. I consider this problem in the context of finding political district-
ing plans that maximize the number of districts in which the majority
of the population is from a minority group, such as African Americans.
Since the set of all possible districting plans is enormous and unfeasi-
ble to examine in practice, this paper proposes a sampling method to
find these outlying plans. Specifically, this paper experiments with short
bursts in the context of minority voting rights in Georgia. Short bursts
are a type of Markov Chain in …
Integrating Carbon Pricing Approaches, Amay Shah
Integrating Carbon Pricing Approaches, Amay Shah
CMC Senior Theses
Concerns about global climate change and its effects have been steadily growing around the world in recent years. The Paris Agreement has laid out ambitious targets for countries to cut their emissions in order to limit global warming to 1.5 degrees and to achieve net zero emissions by 2050. Carbon pricing mechanisms are an inventive instrument that can help achieve these emissions reductions by placing a price on greenhouse gas emissions, creating incentives for organizations to reduce their emissions. These mechanisms can also help enable the transfers from wealthy nations to developing nations that will be essential for ensuring a …
Feature Investigation For Stock Returns Prediction Using Xgboost And Deep Learning Sentiment Classification, Seungho (Samuel) Lee
Feature Investigation For Stock Returns Prediction Using Xgboost And Deep Learning Sentiment Classification, Seungho (Samuel) Lee
CMC Senior Theses
This paper attempts to quantify predictive power of social media sentiment and financial data in stock prediction by utilizing a comprehensive set of stock-related fundamental and technical variables and social media sentiments. For conducting sentiment analysis, this study employs a pretrained finBERT model that provides three different sentiment classifications and respective softmax scores. Hence, the significance of these variables is evaluated with XGBoost regression and Shapley Additive exPlanations (SHAP) frameworks. Through investigating feature importance, this study finds that statistical properties of sentiment variables provide a stronger predictive power than a weighted sentiment score and that it is possible to quantify …
Factory To Table: A Philosophic Analysis Of The Justice Or Lack Thereof Of Agricultural Markets, Will Carter
Factory To Table: A Philosophic Analysis Of The Justice Or Lack Thereof Of Agricultural Markets, Will Carter
CMC Senior Theses
How food is produced has dramatic consequences on how we live, our world’s justice, and the future of our planet. In a world increasingly driven by neoliberalism, agricultural markets have been incentivized to industrialize, globalize, and consolidate. This has resulted in the global dominance of a new type of agriculture, industrial agriculture, driven by the market logic of lowering costs and raising profits. Industrial agriculture has undoubtedly generated the profound benefit of cheaper, more plentiful food in much of the world. These favorable innovations lead many scholars to argue that free markets produce the most just and efficient arrangements for …
An Evaluation Of Knot Placement Strategies For Spline Regression, William Klein
An Evaluation Of Knot Placement Strategies For Spline Regression, William Klein
CMC Senior Theses
Regression splines have an established value for producing quality fit at a relatively low-degree polynomial. This paper explores the implications of adopting new methods for knot selection in tandem with established methodology from the current literature. Structural features of generated datasets, as well as residuals collected from sequential iterative models are used to augment the equidistant knot selection process. From analyzing a simulated dataset and an application onto the Racial Animus dataset, I find that a B-spline basis paired with equally-spaced knots remains the best choice when data are evenly distributed, even when structural features of a dataset are known …
Information Prioritization: A Comparison Between Utility Maximizers And Probability Matchers, Yusuf Ismaeel
Information Prioritization: A Comparison Between Utility Maximizers And Probability Matchers, Yusuf Ismaeel
CMC Senior Theses
This thesis examines the differences between probability matchers and utility maximizers in their preferences for information sources in a lab environment. In this paper, we consider the best source of information to be the most connected one. We conducted several linear probability model type regressions along with logit regressions. Furthermore, we also attempted to control and fix any potential misclassifications in classifying the cognitive strategy by using instrumental variables. The results show that utility maximizers will almost always choose the most informed node. Probability matchers, on the other hand, do not exhibit such a behavior as the probability matching strategy …
Optimal Execution In Cryptocurrency Markets, Ethan Kurz
Optimal Execution In Cryptocurrency Markets, Ethan Kurz
CMC Senior Theses
The purpose of this paper is to study the Almgren and Chriss model on the optimal execution of large block orders both on the NYSE and in cryptocurrency exchanges. Their model minimizes execution costs, which include linear temporary and permanent price impacts. We focus on how the stock market microstructure differs from a cryptocurrency exchange microstructure and what that means for how the model functions. Once the model and microstructures are explained, we examine how the Almgren-Chriss model functions with stocks from the NYSE, looking at specifically selling a large number of shares. We then investigate how a large "wholesale" …
K-Means Stock Clustering Analysis Based On Historical Price Movements And Financial Ratios, Shu Bin
K-Means Stock Clustering Analysis Based On Historical Price Movements And Financial Ratios, Shu Bin
CMC Senior Theses
The 2015 article Creating Diversified Portfolios Using Cluster Analysis proposes an algorithm that uses the Sharpe ratio and results from K-means clustering conducted on companies' historical financial ratios to generate stock market portfolios. This project seeks to evaluate the performance of the portfolio-building algorithm during the beginning period of the COVID-19 recession. S&P 500 companies' historical stock price movement and their historical return on assets and asset turnover ratios are used as dissimilarity metrics for K-means clustering. After clustering, stock with the highest Sharpe ratio from each cluster is picked to become a part of the portfolio. The economic and …
@Yourlocation: A Spatial Analysis Of Geotagged Tweets In The Us, Ocean Mckinney
@Yourlocation: A Spatial Analysis Of Geotagged Tweets In The Us, Ocean Mckinney
CMC Senior Theses
This project examines the spatial network properties observable from geo-located tweet data. Conventional exploration examines characteristics of a variety of network attributes, but few employ spatial edge correlations in their analysis. Recent studies have demonstrated the improvements that these correlations contribute to drawing conclusions about network structure. This thesis expands upon social network research utilizing spatial edge correlations and presents processing and formatting techniques for JSON (JavaScript Object Notation) data.
Can A Comprehensive Transition Plan To Barefoot Running Be The Solution To The Injury Epidemic In American Endurance Runners?, Michael A. Scarlett
Can A Comprehensive Transition Plan To Barefoot Running Be The Solution To The Injury Epidemic In American Endurance Runners?, Michael A. Scarlett
CMC Senior Theses
Fossils belonging to the genus Homo, dating as far back as two million years ago, exhibit uniquely efficient features suggesting that early humans had evolved to become exceptional endurance runners. Although they did not have the cushion or stability-control features provided in our modern day running shoes, our early human ancestors experienced far less of the running-related injuries we experience today. The injury rate has been estimated as high as 90% annually for Americans training for a marathon and as high as 79% annually for all American endurance runners. There is an injury epidemic in conventionally shod populations that …
Topic Analysis Of Tweets On The European Refugee Crisis Using Non-Negative Matrix Factorization, Chong Shen
Topic Analysis Of Tweets On The European Refugee Crisis Using Non-Negative Matrix Factorization, Chong Shen
CMC Senior Theses
The ongoing European Refugee Crisis has been one of the most popular trending topics on Twitter for the past 8 months. This paper applies topic modeling on bulks of tweets to discover the hidden patterns within these social media discussions. In particular, we perform topic analysis through solving Non-negative Matrix Factorization (NMF) as an Inexact Alternating Least Squares problem. We accelerate the computation using techniques including tweet sampling and augmented NMF, compare NMF results with different ranks and visualize the outputs through topic representation and frequency plots. We observe that supportive sentiments maintained a strong presence while negative sentiments such …
An Exposition And Calibration Of The Ho-Lee Model Of Interest Rates, Benjamin I. Lawson
An Exposition And Calibration Of The Ho-Lee Model Of Interest Rates, Benjamin I. Lawson
CMC Senior Theses
The purpose of this paper is to create an easily understandable version of the Ho-Lee interest rate model. The first part analyzes the model in detail, and the second part calibrates it to demonstrate how it can be applied to real market data.
Applications Of Monte Carlo Methods In Statistical Inference Using Regression Analysis, Ji Young Huh
Applications Of Monte Carlo Methods In Statistical Inference Using Regression Analysis, Ji Young Huh
CMC Senior Theses
This paper studies the use of Monte Carlo simulation techniques in the field of econometrics, specifically statistical inference. First, I examine several estimators by deriving properties explicitly and generate their distributions through simulations. Here, simulations are used to illustrate and support the analytical results. Then, I look at test statistics where derivations are costly because of the sensitivity of their critical values to the data generating processes. Simulations here establish significance and necessity for drawing statistical inference. Overall, the paper examines when and how simulations are needed in studying econometric theories.
A Look Into The Industry Of Video Games Past, Present, And Yet To Come, Chad Hadzinsky
A Look Into The Industry Of Video Games Past, Present, And Yet To Come, Chad Hadzinsky
CMC Senior Theses
Since its inception, the video game industry has been both a new medium for art and innovation as well as a major driving force in the advancements of many technologies. The often overlooked video game industry has turned from a hobby to a multi-billion dollar industry in its short, forty year life. People of all ages and genders across the world are playing video games at a higher clip than ever before. With so many new gamers and emerging technologies, it is an exciting time for the industry. The landscape is constantly changing and successful business models of the past …
Nfl Betting Market: Using Adjusted Statistics To Test Market Efficiency And Build A Betting Model, James P. Donnelly
Nfl Betting Market: Using Adjusted Statistics To Test Market Efficiency And Build A Betting Model, James P. Donnelly
CMC Senior Theses
The use of statistical analysis has been prevalent in the sports gambling industry for years. More recently, we have seen the emergence of "adjusted statistics", a more sophisticated way to examine each play and each result (further explanation below). And while adjusted statistics have become commonplace for professional and recreational bettors alike, little research has been done to justify their use. In this paper the effectiveness of this data is tested on the most heavily wagered sport in the world – the National Football League (NFL). The results are studied with two central questions in mind: Does the market account …
State Level Earned Income Tax Credit’S Effects On Race And Age: An Effective Poverty Reduction Policy, Anthony J. Barone
State Level Earned Income Tax Credit’S Effects On Race And Age: An Effective Poverty Reduction Policy, Anthony J. Barone
CMC Senior Theses
In this paper, I analyze the effectiveness of state level Earned Income Tax Credit programs on improving of poverty levels. I conducted this analysis for the years 1991 through 2011 using a panel data model with fixed effects. The main independent variables of interest were the state and federal EITC rates, minimum wage, gross state product, population, and unemployment all by state. I determined increases to the state EITC rates provided only a slight decrease to both the overall white below-poverty population and the corresponding white childhood population under 18, while both the overall and the under-18 black population for …
Energy Storage: Technology For A More Efficient Grid, Noah Proser
Energy Storage: Technology For A More Efficient Grid, Noah Proser
CMC Senior Theses
Energy storage technologies have the potential to revolutionize the electric grid by allowing for the integration of renewable generation while increasing the utilization and efficiency of current grid assets. These technologies include pumped hydroelectric storage, compressed air energy storage (CAES), flywheels, batteries, thermal energy storage (TES), super capacitors, and superconducting magnetic energy storage (SMES). While energy storage has been implemented in some areas, its benefits are greatly undervalued by current regulatory frameworks leading to suboptimal outcomes for grid operators, utilities, and ratepayers. Large-scale adoption of storage technologies will require regulatory frameworks that recognize the benefits of grid-scale storage across generation, …
Overcoming The Obstacles To Sustainability In Ghana, Ashley M. Scott
Overcoming The Obstacles To Sustainability In Ghana, Ashley M. Scott
CMC Senior Theses
For several decades following its independence from Great Britain, Ghana’s policies continued to promote over-extraction of natural resources to the detriment of its economy and rural communities. Agricultural and forestry policy has gradually evolved to foster more sustainable and equitable practices, as in building partnerships with the private sector to fund infrastructure improvements. Policy has recently recognized the dire need to adopt agricultural practices and means of forest resource extraction that are compatible with ecological stewardship. However, many shortcomings are still apparent. Large logging operations completely disregard forestry regulations with impunity, whereas rural sustenance extractors are severely punished in the …