Physical Sciences and Mathematics Commons^™

Nonparametric Estimation Of Time Series Volatility Model Estimation, Teng Tu

Arts & Sciences Electronic Theses and Dissertations

In this article we consider two estimation methods of a non-parametric volatility model with autoregressive error of order two. The first estimation method based on the two- lag difference. To get a better result, we consider the second approach based on the general quadratic forms. For illustration, we provided several data sets from different simulation models to support the procedures of both two methods, and prove that the second approach can make a better estimation.

Allocating Interventions Based On Counterfactual Predictions: A Case Study On Homelessness Services, Amanda R. Kube

McKelvey School of Engineering Theses & Dissertations

Modern statistical and machine learning methods are increasingly capable of modeling individual or personalized treatment effects by predicting counterfactual outcomes. These counterfactual predictions could be used to allocate different interventions across populations based on individual characteristics. In many domains, like social services, the availability of possible interventions can be severely resource limited. This thesis considers possible improvements to the allocation of such services in the context of homelessness service provision in a major metropolitan area. Using data from the homeless system, I show potential for substantial predicted benefits in terms of reducing the number of families who experience repeat episodes …

Estimation Of A Noisy Subordinated Brownian Motion Via Two-Scales Power Variations, José E. Figueroa-López, Kiseop Lee

Mathematics Faculty Publications

High frequency based estimation methods for a semiparametric pure-jump subordinated Brownian motion exposed to a small additive microstructure noise are developed building on the two-scales realized variations approach originally developed by Zhang et al. (2005) for the estimation of the integrated variance of a continuous Itô process. The proposed estimators are shown to be robust against the noise and, surprisingly, to attain better rates of convergence than their precursors, method of moment estimators, even in the absence of microstructure noise. Our main results give approximate optimal values for the number K of regular sparse subsamples to be used, which is …

Mortgage Transition Model Based On Loanperformance Data, Shuyao Yang

Arts & Sciences Electronic Theses and Dissertations

The unexpected increase in loan default on the mortgage market is widely considered to be one of the main cause behind the economic crisis. To provide some insight on loan delinquency and default, I analyze the mortgage performance data from Fannie Mae website and investigate how economic factors and individual loan and borrower information affect the events of default and prepaid. Various delinquency status including default and prepaid are treated as discrete states of a Markov chain. One-step transition probabilities are estimated via multinomial logistic models. We find that in general current loan-to-value ratio, credit score, unemployment rate, and interest …

Statistical Analysis Of Markovian Queueing Models Of Limit Order Books, Yiyao Luo

Arts & Sciences Electronic Theses and Dissertations

The objective of this thesis is to investigate the suitability of some Markovian queueing models in being able to effectively describe the dynamical properties of a limit order book more specifically. We review and compare the assumptions proposed by Huang et al.[Quantitative Finance,12,547-557(2012)] and Cont et al.[SIAM Journal for Financial Mathematics,4,1- 25(2013)], and estimate the intensity parameters in both ways, based on real data of a stock on the Nasdaq Stock Market. Trough comparing by cumulative distribution functions of first-passage time to state 0, we will hsow that the estimators of Cont’s model fit our data better and we put …

On Post-Selection Confidence Intervals In Linear Regression, Xinwei Zhang

Arts & Sciences Electronic Theses and Dissertations

The general goal of this thesis is to investigate and examine some issues about post-selection inference which arises from the setting where statistical inference is carried out after a datadriven model selection step. In this setting, the classical inference theory which requires a fixed priori model becomes invalid since the selected model is a result of random event. Hence, a common practice in applied research which ignores the model selection and builds up confidence interval will result in misleading or even false conclusion. In this thesis, specifically, we first discusses some examples to show how the classical inference theory loses …

Market Risk Management For Financial Institutions Based On Garch Family Models, Qiandi Chen

Arts & Sciences Electronic Theses and Dissertations

The financial stock market turned out to rise and fall suddenly and sharply in recent years, which means that volatility and uncertainty is very significant in market and measuring the market risk accurately is of great importance. I collect the historical close price of S&P 500 Financials Sector Index from January 19th 2011 to January 31st 2017, and use the daily logarithm yield as time series data to build 2 ARMA models and 5 GARCH family models using t-distribution. Then I calculate future 10 days’ relative VAR in 1-day horizon under 99\% confidence level based on the selected model. E-GARCH …

Statistical Models To Predict Popularity Of News Articles On Social Networks, Ziyi Liu

Arts & Sciences Electronic Theses and Dissertations

Social networks have changed the way that we obtain information. Content creators and, specifically news article authors, have in interest in predicting the popularity of content, in terms of the number of shares, likes, and comments across various social media platforms. In this thesis, I employ several statistical learning methods for prediction. Both regression-based and classification-based methods are compared according to their predictive ability, using a database from the UCI Machine Learning Repository.

Statistical Analysis Of The Price Jumps Of Financial Assets Based On Lob Data, Ying Zhuang

Arts & Sciences Electronic Theses and Dissertations

The price process in electronic markets is one prototypical example of a stochastic process, and it has historically be fitted and analyzed using different stochastic models such as Levy processes, diffusions, and SDEs (stochastic differential equations). In this thesis, we analyze Microsoft stock data in 2014-11-03 with the goal of studying the presence of jumps based on Limit Order Book (LOB) data. To this end, we divide the whole day’s data into many consecutive intervals and proceed to apply a jump detection method to identify the intervals that could potentially have jumps. After obtaining the intervals with potential jumps, we …

A Traders Guide To The Predictive Universe- A Model For Predicting Oil Price Targets And Trading On Them, Jimmie Harold Lenz

Doctor of Business Administration Dissertations

At heart every trader loves volatility; this is where return on investment comes from, this is what drives the proverbial “positive alpha.” As a trader, understanding the probabilities related to the volatility of prices is key, however if you could also predict future prices with reliability the world would be your oyster. To this end, I have achieved three goals with this dissertation, to develop a model to predict future short term prices (direction and magnitude), to effectively test this by generating consistent profits utilizing a trading model developed for this purpose, and to write a paper that anyone with …

Survival Analysis In A Clinical Setting, Yunzhao Liu

Arts & Sciences Electronic Theses and Dissertations

With the fast paced advancement of modern medicine, cancer treatments have improved greatly over the past few decades; however, the overall survival rate has not improved for head neck squamous cell carcinoma (HNSCC). Traditionally, the general affected population of HNSCC was male over 50-60 years of age, whom have had history of alcohol and tobacco use. Conversely, in the recent decades, HNSCC has exhibited significant rise in younger patients, largely due to the increase in human papillomavirus (HPV) infection among young adults.

Generally, HPV as the most prevalent sexually transmitted disease, consisted of strains that do not cause harm to …

Elements Of The Mathematical Formulation Of Quantum Mechanics, Keunjae Go

Senior Honors Papers / Undergraduate Theses

In this paper, we will explore some of the basic elements of the mathematical formulation of quantum mechanics. In the first section, I will list the motivations for introducing a probability model that is quite different from that of the classical probability theory, but still shares quite a few significant commonalities. Later in the paper, I will discuss the quantum probability theory in detail, while paying a brief attention to some of the axioms (by Birkhoff and von Neumann) that illustrate both the commonalities and differences between classical mechanics and quantum mechanics. This paper will end with a presentation of …

Genetic Imputation: Accuracy To Application, Shelina Raynell Ramnarine

Arts & Sciences Electronic Theses and Dissertations

Genotype imputation, the process of inferring genotypes for untyped variants, is used to identify and refine genetic association findings. This body of work focuses on assessing imputation accuracy and uses imputed data to identify genetic contributors to mentholated cigarette preference.

Inaccuracies in imputed data can distort the observed association between variants and a disease. Many statistics are used to assess accuracy; some compare imputed to genotyped data and others are calculated without reference to true genotypes. Prior work has shown that the Imputation Quality Score (IQS), which is based on Cohens kappa statistic and compares imputed genotype probabilities to true …

Market Effect: The Impact Of For-Profit Charter Schools On Racial And Socioeconomic Segregation, William Brett Robertson

Arts & Sciences Electronic Theses and Dissertations

For-profit charter schools are a controversial new development in public education. They combine a structural imperative to maximize profit for private shareholders with the social good of providing public education. This dissertation describes two analyses of for-profit charter schools designed to explore their impact on racial and socioeconomic segregation. The analyses utilize geographic information systems, multilevel modeling, and logistic regression to determine whether and how for-profit charter schools are likely to locate in demographically different neighborhoods, and/or educate demographically different student populations from other types of public schools. The results indicate that for-profit charter schools are less likely than other …

Spot Volatility Estimation Of Ito Semimartingales Using Delta Sequences, Weixuan Gao

Arts & Sciences Electronic Theses and Dissertations

This thesis studies a unifying class of nonparametric spot volatility estimators proposed by Mancini et. al.(2013). This method is based on delta sequences and is conceived to include many of the existing estimators in the field as special cases. The thesis first surveys the asymptotic theory of the proposed estimators under an infill asymptotic scheme and fixed time horizon, when the state variable follows a Brownian semimartingale. Then, some extensions to include jumps and financial microstructure noise in the observed price process are also presented. The main goal of the thesis is to assess the suitability of the proposed methods …

Lead Poisoning In United States Children, Zeren Zhou

Arts & Sciences Electronic Theses and Dissertations

We investigate factors related to blood lead levels of children ages 1 to 5 in the United States for the years 2007-2014. We use data from the National Health and Nutrition Examination Survey (NHANES). The goal is to explore predictors of lead in childrens' blood and to develop a multivariate model using as many predictors as possible. The analysis is conducted using SAS survey regression procedures that account for weighting, stratification, and clustering of the data.

Classification Trees And Rule-Based Modeling Using The C5.0 Algorithm For Self-Image Across Sex And Race In St. Louis, Rohan Shirali

Arts & Sciences Electronic Theses and Dissertations

The study population comprised children, adolescents, and adults who were residents of the city of St. Louis at the time of data collection in 2015. The data collected includes sex, age, race, measured height and weight, self-reported height and weight, zip code, educational background, exercise and diet habits, and descriptions and strategies of participants' weight (i.e. overweight and trying to lose weight, respectively). I use the C5.0 algorithm to create classification trees and rule-based models to analyze this population. Specifically, I model a binary self-image variable as a function of sex, age, race, zip code, and a ratio of reported …

Examining Cost Functionality And Optimization: A Case Study On Testing The Reasonableness Of New Aircraft Using Historical Aircraft Data, Katherine Jozefiak

Arts & Sciences Electronic Theses and Dissertations

When pursuing business by competing for government contracts, proving the submitted price is reasonable is often required. This proof is called a test of reasonableness. This study analyzes data from historical aircraft programs in relation of a new aircraft program in order to demonstrate the estimated cost of the new program is reasonable. The purpose of this study is to investigate three questions. Is the new program cost reasonable using current industry and government parameters? Is it better to look at programs from a total cost perspective or break the total cost into subcategory levels? Finally, this study applies a …

Distributed Target Tracking And Synchronization In Wireless Sensor Networks, Jichuan Li

McKelvey School of Engineering Theses & Dissertations

Wireless sensor networks provide useful information for various applications but pose challenges in scalable information processing and network maintenance. This dissertation focuses on statistical methods for distributed information fusion and sensor synchronization for target tracking in wireless sensor networks.

We perform target tracking using particle filtering. For scalability, we extend centralized particle filtering to distributed particle filtering via distributed fusion of local estimates provided by individual sensors. We derive a distributed fusion rule from Bayes' theorem and implement it via average consensus. We approximate each local estimate as a Gaussian mixture and develop a sampling-based approach to the nonlinear fusion …

Applying Bayesian Machine Learning Methods To Theoretical Surface Science, Shane Carr

McKelvey School of Engineering Theses & Dissertations

Machine learning is a rapidly evolving field in computer science with increasingly many applications to other domains. In this thesis, I present a Bayesian machine learning approach to solving a problem in theoretical surface science: calculating the preferred active site on a catalyst surface for a given adsorbate molecule. I formulate the problem as a low-dimensional objective function. I show how the objective function can be approximated into a certain confidence interval using just one iteration of the self-consistent field (SCF) loop in density functional theory (DFT). I then use Bayesian optimization to perform a global search for the solution. …

Survival Analysis Of Cardiovascular Diseases, Yuanxin Hu

All Theses and Dissertations (ETDs)

No abstract provided.

Poverty And Disability: A Vicious Circle? Evidence From Afghanistan And Zambia, Jean-Francois Trani, Mitchell M. Loeb

Brown School Faculty Publications

Disability and poverty have a complex and interdependent relationship. It is commonly understood that persons with disabilities are more likely to be poor and that poverty may contribute to sustaining disability. This interdependency is revealed not only through an examination of poverty in terms of income but also on a broader scale through other poverty related dimensions. Just how robust is this link? This paper compares data collected from household surveys in Afghanistan and Zambia, and explores the potential link between multidimensional poverty and disability. We find evidence of lower access to health care, education and labour market for people …

Poverty, Vulnerability, And Provision Of Healthcare In Afghanistan, Jean-Francois Trani, Parul Bakhshi, Ayan A. Noor, Dominque Lopez, Ashraf Mashkoor

Brown School Faculty Publications

This paper presents findings on conditions of healthcare delivery in Afghanistan. There is an ongoing debate about barriers to healthcare in low-income as well as fragile states. In 2002, the Government of Afghanistan established a Basic Package of Health Services (BPHS), contracting primary healthcare delivery to non-state providers. The priority was to give access to the most vulnerable groups: women, children, disabled persons, and the poorest households. In 2005, we conducted a nationwide survey, and using a logistic regression model, investigated provider choice. We also measured associations between perceived availability and usefulness of healthcare providers. Our results indicate that the …