Calibration and Model Uncertainty of a Two-Factor Mean-Reverting Diffusion Model for Commodity Prices

With the development of various derivative instruments and index products, commodities have become a distinct asset class which can offer enhanced diversification benefits to the traditional asset allocation of stocks and bonds. In this thesis, we begin by discussing some of the key properties of co...

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Main Author: Chuah, Jue Jun
Language:en
Published: 2013
Subjects:
Online Access:http://hdl.handle.net/10012/7758
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spelling ndltd-LACETR-oai-collectionscanada.gc.ca-OWTU.10012-77582013-10-04T04:12:26ZChuah, Jue Jun2013-08-28T19:41:05Z2013-08-28T19:41:05Z2013-08-28T19:41:05Z2013http://hdl.handle.net/10012/7758With the development of various derivative instruments and index products, commodities have become a distinct asset class which can offer enhanced diversification benefits to the traditional asset allocation of stocks and bonds. In this thesis, we begin by discussing some of the key properties of commodity markets which distinguish them from bond and stock markets. Then, we consider the informational role of commodity futures markets. Since commodity prices exhibit mean-reverting behaviour, we will also review several mean-reversion models which are commonly used to capture and describe the dynamics of commodity prices. In Chapter 4, we focus on discussing a two-factor mean-reverting model proposed by Hikspoors and Jaimungal, as a means of providing additional degree of randomness to the long-run mean level. They have also suggested a method to extract the implied market prices of risk, after estimating both the risk-neutral and real-world parameters from the calibration procedure. Given the usefulness of this model, we are motivated to investigate the robustness of this calibration process by applying the methodology to simulated data. The capability to produce stable and accurate parameter estimates will be assessed by selecting various initial guesses for the optimization process. Our results show that the calibration method had a lot of difficulties in estimating the volatility and correlation parameters of the model. Moreover, we demonstrate that multiple solutions obtained from the calibration process would lead to model uncertainty in extracting the implied market prices of risk. Finally, by using historical crude oil data from the same time period, we can compare our calibration results with those obtained by Hikspoors and Jaimungal.enCalibrationModel RiskCommodityCalibration and Model Uncertainty of a Two-Factor Mean-Reverting Diffusion Model for Commodity PricesThesis or DissertationSchool of AccountancyMaster of Quantitative FinanceQuantitative Finance
collection NDLTD
language en
sources NDLTD
topic Calibration
Model Risk
Commodity
Quantitative Finance
spellingShingle Calibration
Model Risk
Commodity
Quantitative Finance
Chuah, Jue Jun
Calibration and Model Uncertainty of a Two-Factor Mean-Reverting Diffusion Model for Commodity Prices
description With the development of various derivative instruments and index products, commodities have become a distinct asset class which can offer enhanced diversification benefits to the traditional asset allocation of stocks and bonds. In this thesis, we begin by discussing some of the key properties of commodity markets which distinguish them from bond and stock markets. Then, we consider the informational role of commodity futures markets. Since commodity prices exhibit mean-reverting behaviour, we will also review several mean-reversion models which are commonly used to capture and describe the dynamics of commodity prices. In Chapter 4, we focus on discussing a two-factor mean-reverting model proposed by Hikspoors and Jaimungal, as a means of providing additional degree of randomness to the long-run mean level. They have also suggested a method to extract the implied market prices of risk, after estimating both the risk-neutral and real-world parameters from the calibration procedure. Given the usefulness of this model, we are motivated to investigate the robustness of this calibration process by applying the methodology to simulated data. The capability to produce stable and accurate parameter estimates will be assessed by selecting various initial guesses for the optimization process. Our results show that the calibration method had a lot of difficulties in estimating the volatility and correlation parameters of the model. Moreover, we demonstrate that multiple solutions obtained from the calibration process would lead to model uncertainty in extracting the implied market prices of risk. Finally, by using historical crude oil data from the same time period, we can compare our calibration results with those obtained by Hikspoors and Jaimungal.
author Chuah, Jue Jun
author_facet Chuah, Jue Jun
author_sort Chuah, Jue Jun
title Calibration and Model Uncertainty of a Two-Factor Mean-Reverting Diffusion Model for Commodity Prices
title_short Calibration and Model Uncertainty of a Two-Factor Mean-Reverting Diffusion Model for Commodity Prices
title_full Calibration and Model Uncertainty of a Two-Factor Mean-Reverting Diffusion Model for Commodity Prices
title_fullStr Calibration and Model Uncertainty of a Two-Factor Mean-Reverting Diffusion Model for Commodity Prices
title_full_unstemmed Calibration and Model Uncertainty of a Two-Factor Mean-Reverting Diffusion Model for Commodity Prices
title_sort calibration and model uncertainty of a two-factor mean-reverting diffusion model for commodity prices
publishDate 2013
url http://hdl.handle.net/10012/7758
work_keys_str_mv AT chuahjuejun calibrationandmodeluncertaintyofatwofactormeanrevertingdiffusionmodelforcommodityprices
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