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Full-Text Articles in Physical Sciences and Mathematics
Attempting To Predict The Unpredictable: March Madness, Coleton Kanzmeier
Attempting To Predict The Unpredictable: March Madness, Coleton Kanzmeier
Theses/Capstones/Creative Projects
Each year, millions upon millions of individuals fill out at least one if not hundreds of March Madness brackets. People test their luck every year, whether for fun, with friends or family, or to even win some money. Some people rely on their basketball knowledge whereas others know it is called March Madness for a reason and take a shot in the dark. Others have even tried using statistics to give them an edge. I intend to follow a similar approach, using statistics to my advantage. The end goal is to predict this year’s, 2022, March Madness bracket. To achieve …
Penalized Estimation Of Autocorrelation, Xiyan Tan
Penalized Estimation Of Autocorrelation, Xiyan Tan
All Dissertations
This dissertation explored the idea of penalized method in estimating the autocorrelation (ACF) and partial autocorrelation (PACF) in order to solve the problem that the sample (partial) autocorrelation underestimates the magnitude of (partial) autocorrelation in stationary time series. Although finite sample bias corrections can be found under specific assumed models, no general formulae are available. We introduce a novel penalized M-estimator for (partial) autocorrelation, with the penalty pushing the estimator toward a target selected from the data. This both encapsulates and differs from previous attempts at penalized estimation for autocorrelation, which shrink the estimator toward the target value of zero. …
Intraday Algorithmic Trading Using Momentum And Long Short-Term Memory Network Strategies, Andrew R. Whitinger Ii
Intraday Algorithmic Trading Using Momentum And Long Short-Term Memory Network Strategies, Andrew R. Whitinger Ii
Undergraduate Honors Theses
Intraday stock trading is an infamously difficult and risky strategy. Momentum and reversal strategies and long short-term memory (LSTM) neural networks have been shown to be effective for selecting stocks to buy and sell over time periods of multiple days. To explore whether these strategies can be effective for intraday trading, their implementations were simulated using intraday price data for stocks in the S&P 500 index, collected at 1-second intervals between February 11, 2021 and March 9, 2021 inclusive. The study tested 160 variations of momentum and reversal strategies for profitability in long, short, and market-neutral portfolios, totaling 480 portfolios. …
Flexible Modelling Of Time-Dependent Covariate Effects With Correlated Competing Risks: Application To Hereditary Breast And Ovarian Cancer Families, Seungwoo Lee
Electronic Thesis and Dissertation Repository
This thesis aims to develop a flexible approach for modelling time-dependent covariate effects on event risk using B-splines in the presence of correlated competing risks. The performance of the proposed model was evaluated via simulation in terms of the bias and precision of the estimation of the parameters and penetrance functions. In addition, we extended the concordance index to account for time-dependent effects and competing events simultaneously and demonstrated its inference procedures. We applied our proposed methods to data rising from the BRCA1 mutation families from the breast cancer family registry to evaluate the time-dependent effects of mammographic screening and …