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Articles 1 - 7 of 7
Full-Text Articles in Physical Sciences and Mathematics
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 …
An Exponential Formula For Random Variables Generated By Multiple Brownian Motions, Maximilian Lawrence Baroi
An Exponential Formula For Random Variables Generated By Multiple Brownian Motions, Maximilian Lawrence Baroi
CGU Theses & Dissertations
The frozen operator has been used to develop Dyson-series like representations for random variables generated by classical Brownian motion, Lévy processes and fractional Brownian with Hurst index greater than 1/2.The relationship between the conditional expectation of a random variable (or fractional conditional expectation in the case of fractional Brownian motion)and that variable's Dyson-series like representation is the exponential formula. These results had not yet been extended to either fractional Brownian motion with Hurst index less than 1/2, or d-dimensional Brownian motion. The former is still out of reach, but we hope our review of stochastic integration for fractional Brownian motion …
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 …
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 …
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" …
Be Wary Of Black-Box Trading Algorithms, Gary N. Smith
Be Wary Of Black-Box Trading Algorithms, Gary N. Smith
Pomona Economics
Black-box algorithms now account for nearly a third of all U. S. stock trades. It is a mistake to think that these algorithms possess superhuman intelligence. In reality, computers do not have the common sense and wisdom that humans have accumulated by living. Trading algorithms are particularly dangerous because they are so efficient at discovering statistical patterns—but so utterly useless in judging whether the discovered patterns are meaningful.
Getting Girls In Stem & The Dangers Of Forgetting That Science Is Art - Someone Made It Up, Heidi Therese Dangelmaier, Camilla Hermann
Getting Girls In Stem & The Dangers Of Forgetting That Science Is Art - Someone Made It Up, Heidi Therese Dangelmaier, Camilla Hermann
The STEAM Journal
Encouraging girls to participate in STEM is a hot topic that has captured the concern of the world’s academic, business and scientific communities. The intention is noble, however the strategies being deployed are reinforcing the very bias society seeks to eliminate. If we wish to advance our evolutionary journey as a species, a shift from “feeling sorry for disadvantaged girls” to “fearing STEM without girls’ reformation” is imperative. This piece discusses the rise to an initiative to redesign culture: Girlapproved.