Optimal Pair-Trading Decision Rules for a Class of Non-Linear Boundary Crossings by Ornstein-Uhlenbeck Processes

Thumbnail image of item number 1 in: 'Optimal Pair-Trading Decision Rules for a Class of Non-Linear Boundary Crossings by Ornstein-Uhlenbeck Processes'.
Thumbnail image of item number 2 in: 'Optimal Pair-Trading Decision Rules for a Class of Non-Linear Boundary Crossings by Ornstein-Uhlenbeck Processes'.
Thumbnail image of item number 3 in: 'Optimal Pair-Trading Decision Rules for a Class of Non-Linear Boundary Crossings by Ornstein-Uhlenbeck Processes'.
Thumbnail image of item number 4 in: 'Optimal Pair-Trading Decision Rules for a Class of Non-Linear Boundary Crossings by Ornstein-Uhlenbeck Processes'.
Showing 1-4 of 166 pages in this dissertation.

PDF Version Also Available for Download.

Description

The most useful feature used in finance of the Ornstein-Uhlenbeck (OU) stochastic process is its mean-reverting property: the OU process tends to drift towards its long- term mean (its equilibrium state) over time. This important feature makes the OU process arguably the most popular statistical model for developing best pair-trading strategies. However, optimal strategies depend crucially on the first passage time (FPT) of the OU process to a suitably chosen boundary and its probability density is not analytically available in general. Even for crossing a simple constant boundary, the FPT of the OU process would lead to crossing a square … continued below

Physical Description

xviii, 147 pages : illustrations (some color)

Creation Information

Tamakloe, Emmanuel Edem Kwaku December 2021.

Context

This dissertation is part of the collection entitled: UNT Theses and Dissertations and was provided by the UNT Libraries to the UNT Digital Library, a digital repository hosted by the UNT Libraries. It has been viewed 36 times. More information about this dissertation can be viewed below.

Who

People and organizations associated with either the creation of this dissertation or its content.

Author

Chair

Committee Members

Publisher

Rights Holder

For guidance see Citations, Rights, Re-Use.

  • Tamakloe, Emmanuel Edem Kwaku

Provided By

UNT Libraries

The UNT Libraries serve the university and community by providing access to physical and online collections, fostering information literacy, supporting academic research, and much, much more.

About | Browse this Partner

Contact Us

Corrections Questions

What

Descriptive information to help identify this dissertation. Follow the links below to find similar items on the Digital Library.

Degree Information

Description

The most useful feature used in finance of the Ornstein-Uhlenbeck (OU) stochastic process is its mean-reverting property: the OU process tends to drift towards its long- term mean (its equilibrium state) over time. This important feature makes the OU process arguably the most popular statistical model for developing best pair-trading strategies. However, optimal strategies depend crucially on the first passage time (FPT) of the OU process to a suitably chosen boundary and its probability density is not analytically available in general. Even for crossing a simple constant boundary, the FPT of the OU process would lead to crossing a square root boundary by a Brownian motion process whose FPT density involves the complicated parabolic cylinder function. To overcome the limitations of the existing methods, we propose a novel class of non-linear boundaries for obtaining optimal decision thresholds. We prove the existence and uniqueness of the maximizer of our decision rules. We also derive simple formulas for some FPT moments without analytical expressions of its density functions. We conduct some Monte Carlo simulations and analyze several pairs of stocks including Coca-Cola and Pepsi, Target and Walmart, Chevron and Exxon Mobil. The results demonstrate that our method outperforms the existing procedures.

Physical Description

xviii, 147 pages : illustrations (some color)

Language

Item Type

Identifier

Unique identifying numbers for this dissertation in the Digital Library or other systems.

Collections

This dissertation is part of the following collection of related materials.

UNT Theses and Dissertations

Theses and dissertations represent a wealth of scholarly and artistic content created by masters and doctoral students in the degree-seeking process. Some ETDs in this collection are restricted to use by the UNT community.

About | Browse this Collection

What responsibilities do I have when using this dissertation?

Digital Files

When

Dates and time periods associated with this dissertation.

Creation Date

  • December 2021

Added to The UNT Digital Library

  • Jan. 8, 2022, 3:30 p.m.

Description Last Updated

  • May 10, 2024, 11:22 a.m.

Usage Statistics

When was this dissertation last used?

Yesterday: 0
Past 30 days: 1
Total Uses: 36
More Statistics

Interact With This Dissertation

Here are some suggestions for what to do next.

Start Reading

Thumbnail image of item number 1 in: 'Optimal Pair-Trading Decision Rules for a Class of Non-Linear Boundary Crossings by Ornstein-Uhlenbeck Processes'.
Thumbnail image of item number 2 in: 'Optimal Pair-Trading Decision Rules for a Class of Non-Linear Boundary Crossings by Ornstein-Uhlenbeck Processes'.
Thumbnail image of item number 3 in: 'Optimal Pair-Trading Decision Rules for a Class of Non-Linear Boundary Crossings by Ornstein-Uhlenbeck Processes'.
Thumbnail image of item number 4 in: 'Optimal Pair-Trading Decision Rules for a Class of Non-Linear Boundary Crossings by Ornstein-Uhlenbeck Processes'.

PDF Version Also Available for Download.

Citations, Rights, Re-Use

International Image Interoperability Framework

IIF Logo

We support the IIIF Presentation API

Links for Robots

Helpful links in machine-readable formats.

Archival Resource Key (ARK)

International Image Interoperability Framework (IIIF)

Metadata Formats

Images

URLs

Stats

Tamakloe, Emmanuel Edem Kwaku. Optimal Pair-Trading Decision Rules for a Class of Non-Linear Boundary Crossings by Ornstein-Uhlenbeck Processes, dissertation, December 2021; Denton, Texas. (https://digital.library.unt.edu/ark:/67531/metadc1873709/: accessed May 27, 2024), University of North Texas Libraries, UNT Digital Library, https://digital.library.unt.edu; .

Back to Top of Screen