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You searched for +publisher:"Penn State University" +contributor:("John C Liechty, Outside Member"). Showing records 1 – 3 of 3 total matches.

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Penn State University

1. Taoufik, Bahaeddine. FUNCTIONAL DATA BASED INFERENCE FOR HIGH FREQUENCY FINANCIAL DATA.

Degree: 2016, Penn State University

This thesis is concerned with developing new functional data techniques for high frequency financial applications. Chapter 1 of the thesis introduces Functional Data Analysis (FDA) with examples of application to real data. In this chapter, we provide some theoretical foundations for FDA. We also present a general theory and basic properties of reproducing kernel Hilbert spaces (RKHS). Chapter 2 of the thesis explores the relationship between market returns and a number of financial factors by fitting functional regression models. We establish two estimation procedures based on the least squares and generalized least squares methods. We also present four hypothesis testing procedures on the functional regression coefficients based on the squared integral L2 approach and the PCA approach for both least squares and generalized least squares methods. New asymptotic results are established allowing for minor departures from stationarity, to ensure convergence and asymptotic normality of our estimates. Our functional regression model is applied to cross-section returns data. Our data application results indicate a positive correlation between the volatility factor ``FVIX" and the higher returns and a negative correlation between the volatility factor ``FVIX" and the low and middle returns. Chapter 3 of the thesis develops a nonlinear function-on-function model using RKHS for real-valued functions. We establish the minimax rate of convergence of the excess prediction risk. Our simulation studies faced computational challenges due to the complexity of the estimation procedure. We examine the prediction performance accuracy of our model through a simulation study. Our nonlinear function-function model is applied to Cumulative intraday return (CIDR) data in order to investigate the prediction performance of Standard \& Poor's 500 Index (S\&P 500) and the Dow Jones Industrial Average (DJIA) for General Electric Company (GE) and International Business Machines Corp.(IBM) for the three periods defining the crisis: ``Before," `` During," and `` After''. Advisors/Committee Members: Matthew Logan Reimherr, Dissertation Advisor/Co-Advisor, Matthew Logan Reimherr, Committee Chair/Co-Chair, Runze Li, Committee Member, Zhibiao Zhao, Committee Member, John C Liechty, Outside Member.

Subjects/Keywords: Functional Data; Nonlinear Functional Regression; Cross-section of returns; Cumulative intraday returns; Reproducing kernel Hilbert spaces

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Taoufik, B. (2016). FUNCTIONAL DATA BASED INFERENCE FOR HIGH FREQUENCY FINANCIAL DATA. (Thesis). Penn State University. Retrieved from https://submit-etda.libraries.psu.edu/catalog/13392but129

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Taoufik, Bahaeddine. “FUNCTIONAL DATA BASED INFERENCE FOR HIGH FREQUENCY FINANCIAL DATA.” 2016. Thesis, Penn State University. Accessed November 29, 2020. https://submit-etda.libraries.psu.edu/catalog/13392but129.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Taoufik, Bahaeddine. “FUNCTIONAL DATA BASED INFERENCE FOR HIGH FREQUENCY FINANCIAL DATA.” 2016. Web. 29 Nov 2020.

Vancouver:

Taoufik B. FUNCTIONAL DATA BASED INFERENCE FOR HIGH FREQUENCY FINANCIAL DATA. [Internet] [Thesis]. Penn State University; 2016. [cited 2020 Nov 29]. Available from: https://submit-etda.libraries.psu.edu/catalog/13392but129.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Taoufik B. FUNCTIONAL DATA BASED INFERENCE FOR HIGH FREQUENCY FINANCIAL DATA. [Thesis]. Penn State University; 2016. Available from: https://submit-etda.libraries.psu.edu/catalog/13392but129

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


Penn State University

2. Jiang, Yilun. Debt Management Problems and Topics in Stackelberg Equilibrium.

Degree: 2019, Penn State University

The dissertation contains two parts. In the first part of the dissertation, we study optimal strategies for a borrower who needs to repay his debt, in an infinite time horizon. An instantaneous bankruptcy risk is present and the borrower refinances the debt by selling bonds to a pool of risk-neutral lenders. We consider both open-loop and feedback strategies. For open-loop strategies, we interpreted them as Stackelberg equilibria, where the borrower announces his repayment strategy at all future times, and lenders adjust the interest rate accordingly. Our analysis shows the existence of optimal open-loop controls, deriving necessary conditions for optimality and characterizing possible asymptotic limits as t →  +∞. For feedback strategies, we study the solution of a Hamilton-Jacobi equations and construct it as the limit of viscous solutions. Under suitable assumptions, this (possibly discontinuous) limit can be interpreted as an equilibrium solution to a non-cooperative differential game with deterministic dynamics. In the second part of the dissertation, we study the structure of the best reply map for the follower and the optimal strategy for the leader in a non-cooperative Stackelberg game. The two players choose their strategies within domains X\subseteq\Rm and Y\subseteq\Rn. Two main cases are considered: either X=Y=[0,1], or X=\R, Y=\Rn with n ≥  1. Using techniques from differential geometry, we prove that for an open dense set of cost functions the Stackelberg equilibrium is unique and is stable w.r.t.~small perturbations of the two cost functions. Then we introduce a concept of ''self consistent'' Stackelberg equilibria for stochastic games in infinite time horizon, where the two players adopt feedback strategies and have exponentially discounted costs. We focus on games in continuous time, described by a controlled Markov process with finite state space. Under generic assumptions, we prove that a unique self-consistent Stackelberg equilibrium exists, provided that either (i) the leader is far-sighted, i.e.~his exponential discount factor is sufficiently small, or (ii) the follower is narrow-sighted, i.e.~his discount factor is large enough. Advisors/Committee Members: Alberto Bressan, Dissertation Advisor/Co-Advisor, Alberto Bressan, Committee Chair/Co-Chair, Alexei Novikov, Committee Member, Iouri M Soukhov, Committee Member, John C Liechty, Outside Member.

Subjects/Keywords: optimal control; debt management; bankruptcy risk; non-cooperative game; Stackelberg equilibrium; generic property

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Jiang, Y. (2019). Debt Management Problems and Topics in Stackelberg Equilibrium. (Thesis). Penn State University. Retrieved from https://submit-etda.libraries.psu.edu/catalog/16312yxj141

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Jiang, Yilun. “Debt Management Problems and Topics in Stackelberg Equilibrium.” 2019. Thesis, Penn State University. Accessed November 29, 2020. https://submit-etda.libraries.psu.edu/catalog/16312yxj141.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Jiang, Yilun. “Debt Management Problems and Topics in Stackelberg Equilibrium.” 2019. Web. 29 Nov 2020.

Vancouver:

Jiang Y. Debt Management Problems and Topics in Stackelberg Equilibrium. [Internet] [Thesis]. Penn State University; 2019. [cited 2020 Nov 29]. Available from: https://submit-etda.libraries.psu.edu/catalog/16312yxj141.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Jiang Y. Debt Management Problems and Topics in Stackelberg Equilibrium. [Thesis]. Penn State University; 2019. Available from: https://submit-etda.libraries.psu.edu/catalog/16312yxj141

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


Penn State University

3. Constantinou, Panayiotis. TESTING SEPARABILITY OF FUNCTIONAL DATA.

Degree: 2017, Penn State University

The assumption of separability is used heavily in spatiotemporal statistics. Separability means that the spatiotemporal covariance structure factors into the product of two functions, one depending only on space and the other only on time. Separability is a property which can dramatically improve computational efficiency by substantially reducing model complexity. It is especially useful for functional data as it implies that the functional principal components are the same for each spatial location. In Chapter 1, we give a brief introduction to functional data, separability and introduce the data sets that motivate this dissertation. In Chapter 2, we present a new methodology to test for separability of spatiotemporal functional data. We present three tests, one being a functional extension of the Monte Carlo likelihood method of Mitchell et al. (2005), while the other two are based on quadratic forms. Our tests are based on asymptotic distributions of maximum likelihood estimators, and do not require Monte Carlo or bootstrap replications. The specification of the joint asymptotic distribution of these estimators is the main theoretical contribution in this chapter. It can be used to derive many other tests. The main methodological finding is that one of the quadratic form methods, which we call a norm approach, emerges as a clear winner in terms of finite sample performance in nearly every setting we considered. The norm approach focuses directly on the Frobenius distance between the spatiotemporal covariance function and its separable approximation. We demonstrate the efficacy of our methods via simulations, and applications to Irish wind data and Nitrogen Dioxide levels on the east coast of the United States. In Chapter 3, we derive and study a significance test for determining if a panel of functional time series is separable. In this context, separability means that the covariance structure factors into the product of two functions, one depending only on time and the other depending only on the coordinates of the panel. In this case, under the assumption of separability, the functional principal components are the same for each member of the panel. However such an assumption must be verified before proceeding with further inference. Our approach is based on functional norm differences and provides a test with well controlled size and high power. In addition to an asymptotic justification, our methodology is validated by a simulation study. It is applied to functional panels of particulate pollution and stock market data. Advisors/Committee Members: Matthew Logan Reimherr, Dissertation Advisor/Co-Advisor, Matthew Logan Reimherr, Committee Chair/Co-Chair, Michael G Akritas, Committee Member, Bing Li, Committee Member, John C Liechty, Outside Member.

Subjects/Keywords: Separability; Functional data; Space-time processes; Functional panels

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Constantinou, P. (2017). TESTING SEPARABILITY OF FUNCTIONAL DATA. (Thesis). Penn State University. Retrieved from https://submit-etda.libraries.psu.edu/catalog/14253pzc140

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Constantinou, Panayiotis. “TESTING SEPARABILITY OF FUNCTIONAL DATA.” 2017. Thesis, Penn State University. Accessed November 29, 2020. https://submit-etda.libraries.psu.edu/catalog/14253pzc140.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Constantinou, Panayiotis. “TESTING SEPARABILITY OF FUNCTIONAL DATA.” 2017. Web. 29 Nov 2020.

Vancouver:

Constantinou P. TESTING SEPARABILITY OF FUNCTIONAL DATA. [Internet] [Thesis]. Penn State University; 2017. [cited 2020 Nov 29]. Available from: https://submit-etda.libraries.psu.edu/catalog/14253pzc140.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Constantinou P. TESTING SEPARABILITY OF FUNCTIONAL DATA. [Thesis]. Penn State University; 2017. Available from: https://submit-etda.libraries.psu.edu/catalog/14253pzc140

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

.