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Performance Classification Of Ornstein-Uhlenbeck-Type Models Using Fractal Analysis Of Time Series Data., Peter Kwadwo Asante May 2023

Performance Classification Of Ornstein-Uhlenbeck-Type Models Using Fractal Analysis Of Time Series Data., Peter Kwadwo Asante

Open Access Theses & Dissertations

This dissertation aims to assess the performance of Ornstein-Uhlenbeck-type models by examining the fractal characteristics of time series data from various sources, including finance, volcanic and earthquake events, US COVID-19 reported cases and deaths, and two simulated time series with differing properties. The time series data is categorized as either a Gaussian or a Lévy process (Lévy walk or Lévy flight) by using three scaling methods: Rescaled range analysis, Detrended fluctuation analysis, and Diffusion entropy analysis. The outcomes of this analysis indicate that the financial indices are classified as Lévy walks, while the volcanic, earthquake, and COVID-19 data are classified …


A Machine Learning Approach To Stochastic Optimal Control, Pablo Ever Avalos May 2022

A Machine Learning Approach To Stochastic Optimal Control, Pablo Ever Avalos

Open Access Theses & Dissertations

Merton's portfolio optimization problem is a well-renowned problem in financial mathematics which seeks to optimize the investment decision for an investor. In the simplest situation, the market consists of a risk-less asset (i.e. a bond) that pays back a relatively low interest rate, and a risky asset (i.e. a stock) that follows a geometric Brownian motion. The optimal allocation strategy of the investor's wealth is found by optimizing the expected utility along the stochastic evolution of the market. This thesis focuses on several different applications of this optimization problem. We look at pre-constructed analytical solutions and showcase the results. We …


Stochastic Modeling Of Earthquakes And Option Pricing Using Bns-Gamma-Ou Model, Mandela Bright Quashie Jan 2020

Stochastic Modeling Of Earthquakes And Option Pricing Using Bns-Gamma-Ou Model, Mandela Bright Quashie

Open Access Theses & Dissertations

High frequency data are becoming increasingly popular these days. They are fundamental in basically every facet of people’s lives. They are the determining factors in hedging in the field of finance. In geology, they help in the accurate prediction of earthquakes’ magnitude which goes along way to help save lives and properties.

High frequency data are also used more and more frequently for speculations. For this reason, it is important not only for scientists to apply models allowing correct quantification of these data, but also to improve the eciency of these models.

The Black-Scholes model, which is widely used because …


Lévy Processes: Characterizing Volcanic And Financial Time Series, Peter Kwadwo Asante Jan 2020

Lévy Processes: Characterizing Volcanic And Financial Time Series, Peter Kwadwo Asante

Open Access Theses & Dissertations

In this work, we use the Diffusion Entropy Analysis (DEA) to analyze and detect the scaling properties of time series from both emerging and well established markets as well as volcanic eruptions recorded by a seismic station, both financial and volcanic time series data are known to have high frequencies (i.e they are collected at an extremely fine scale). The objective is to determine the characterization i.e whether they follow a Gaussian or Lévy distribution. If they do follow a Lévy distribution we are then interested in finding if they are characterized by a Lévy walk which has a finite …


Estimating The Optimal Cutoff Point For Logistic Regression, Zheng Zhang Jan 2018

Estimating The Optimal Cutoff Point For Logistic Regression, Zheng Zhang

Open Access Theses & Dissertations

Binary classification is one of the main themes of supervised learning. This research is concerned about determining the optimal cutoff point for the continuous-scaled outcomes (e.g., predicted probabilities) resulting from a classifier such as logistic regression. We make note of the fact that the cutoff point obtained from various methods is a statistic, which can be unstable with substantial variation. Nevertheless, due partly to complexity involved in estimating the cutpoint, there has been no formal study on the variance or standard error of the estimated cutoff point.

In this Thesis, a bootstrap aggregation method is put forward to estimate the …


Quantifying A Mining Investability Quotient To Mitigate Junior Mining Investment Risk, Jonathan Mickey Merguerian Jan 2016

Quantifying A Mining Investability Quotient To Mitigate Junior Mining Investment Risk, Jonathan Mickey Merguerian

Open Access Theses & Dissertations

Uncertainty and risk are inherent features of investing in mineral exploration ventures. Investors rely on qualitative and quantitative analysis to evaluate risk of capital. The distinction between risk and uncertainty pertaining to mineral exploration is that risk is an opportunity for loss and uncertainty can be described as the range of probabilities that some condition may occur (Rose, 1987). Stakeholders rely on a combination of investment conferences, risk analysis equations, press releases, financial reports, and investment research to determine if an investment potential. J. M. Cozzolini developed a formula for Risk Adjusted Value (RAV) of an exploration venture. The study …


Public Social Network Sites And Social Recruiting, Abby Peters Jan 2014

Public Social Network Sites And Social Recruiting, Abby Peters

Open Access Theses & Dissertations

Social network sites (SNSs) are an increasingly popular form of social media used by individuals and organizations. As these platforms continue to transform the way people communicate with one another, they are simultaneously revolutionizing the way individuals interact with organizations. Part of this dramatic change is apparent in the processes by which organizations are recruiting employees and job seekers are pursuing employment. To investigate these phenomena, I employed the diffusion of innovations theory in a SNS context to examine the relationship between organizations' use of their corporate career website and their use of SNSs as recruiting sources. Subsequently, I used …


A Systematic Approach To Manage Missing Data In Pavement Management Systems, Mazin M. Al-Zou'bi Jan 2013

A Systematic Approach To Manage Missing Data In Pavement Management Systems, Mazin M. Al-Zou'bi

Open Access Theses & Dissertations

Pavements are an important part of the highway transportation infrastructure, accounting for the largest share of the overall investment. A tremendous amount of time and money is spent each year on the construction of new pavements, as well as on the maintenance and rehabilitation of existing pavements.

Transportation agencies use pavement management systems (PMS) for their maintenance and rehabilitation planning, programming, and budgeting. PMS are used to make decisions regarding when maintenance and rehabilitation should be applied. The systems also select what type of treatment should be applied for each pavement section in the network with clear estimations of the …


Analysis Of Intermittence And Log-Periodicity Of Foreign Exchange Rates Near A Crash, Arturo Casillas Jan 2012

Analysis Of Intermittence And Log-Periodicity Of Foreign Exchange Rates Near A Crash, Arturo Casillas

Open Access Theses & Dissertations

Many believe that financial indices near a crash exhibit a type of critical point characterized by log-periodic signatures. Models have been developed based on these ideas in an attempt to mathematically characterize financial data about to crash. Few of these models consider the property of intermittency. Intermittency is a concept borrowed from fluid dynamics that essentially implies that a system alternates between a stable, or predictable, state and unstable state. One model that attempts to characterize crashes incorporates intermittency in the form of log-stationary intervals. It models the asset price as a step function that follows an underlying power law. …


Arma-Garch Model Applied To Exchange-Traded Funds, Rebecca Davis Jan 2012

Arma-Garch Model Applied To Exchange-Traded Funds, Rebecca Davis

Open Access Theses & Dissertations

In this paper, time-varying volatility of some of the leading exchange-traded funds are studied. The ARMA mean equation with GARCH errors is used to model the series correlations and the conditional heteroscadesticity in the asset

returns. The conditional distributions of the standardized residuals are assumed to be skew-generalized error distribution. The high kurtosis and fat tail of the returns, were captured in all the data by fitting an ARMA-GARCH model with the conditional distribution of, skew-generalized error distribution.

Furthermore, the sample cross-correlations of these significant exchange-traded funds and the corresponding financial indices they mimic were computed. The empirical conclusion was …


Study Of Volatility Structures In Geophysics And Finance Using Garch Models, Francis Biney Jan 2012

Study Of Volatility Structures In Geophysics And Finance Using Garch Models, Francis Biney

Open Access Theses & Dissertations

This work investigates the underlying volatility processes in earthquake series, explosive series, high frequency (tick) data and financial indices. Furthermore it examines the applicability of a range of GARCH specifications for modeling volatility of these series in order to identify similarities and differences in the volatility structures. The GARCH

variants considered include the basic GARCH, IGARCH, ARFIMA (0,d,0)-GARCH and FIGARCH specifications. In all the applications the methodology provides insight into features of these series volatility.


New Algorithms For Optimal Portfolio Selection, Tanja Magoc Jan 2009

New Algorithms For Optimal Portfolio Selection, Tanja Magoc

Open Access Theses & Dissertations

Over the past four thousand years, numerous techniques have been developed and used to address problems in Finance. These techniques include simple arithmetic calculations and probabilistic methods as well as intelligent systems techniques such as neural networks, genetic algorithms, multi-agent systems, and support vector machines. The techniques have been developed to accurately and quickly collect, validate, analyze, and integrate data that change dynamically.

The particular problem that we address in this Dissertation is the construction of efficient algorithms for the problem of an optimal portfolio selection, that is, algorithms that would accurately and in real time determine the best distribution …