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Physical Sciences and Mathematics Commons

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Full-Text Articles in Physical Sciences and Mathematics

Empirical Properties Of Functional Regression Models And Application To High-Frequency Financial Data, Xi Zhang May 2013

Empirical Properties Of Functional Regression Models And Application To High-Frequency Financial Data, Xi Zhang

All Graduate Theses and Dissertations, Spring 1920 to Summer 2023

Functional data analysis (FDA) has grown into a substantial field of statistical research, with new methodology, numerous useful applications and interesting novel theoretical developments. My dissertation focuses on the empirical properties of functional regression models and their application to financial data. We start from testing the empirical properties of forecasts with the functional autoregressive models based on simulated and real data. We define intraday returns and consider their prediction from such returns on a market index. This is an extension to intraday data of the Capital Asset Pricing model. Finally we investigate multifactor functional models and assess their suitability for …


The Chain-Link Fence Model: A Framework For Creating Security Procedures, Robert F. Houghton May 2013

The Chain-Link Fence Model: A Framework For Creating Security Procedures, Robert F. Houghton

All Graduate Theses and Dissertations, Spring 1920 to Summer 2023

Information technology security professionals are facing an ever growing threat to the networks that they defend. The process for creating procedures to help stem this threat is very difficult for security professionals. The Chain-Link Fence Model helps security professionals by guiding them through the process of creating and implementing new security procedures.


An Evolutionary Approach To Optimization Of Compound Stock Trading Indicators Used To Confirm Buy Signals, Allan W. Teeples Dec 2010

An Evolutionary Approach To Optimization Of Compound Stock Trading Indicators Used To Confirm Buy Signals, Allan W. Teeples

All Graduate Theses and Dissertations, Spring 1920 to Summer 2023

This thesis examines the application of genetic algorithms to the optimization of a composite set of technical indicator filters to confirm or reject buy signals in stock trading, based on probabilistic values derived from historical data. The simplicity of the design, which gives each filter within the composite filter the ability to act independently of the other filters, is outlined, and the cumulative indirect effect each filter has on all the others is discussed. This system is contrasted with the complexity of systems from previous research that attempt to merge several indicator filters together by giving each one a weight …