Pricing contingent claims on credit and carbon single and multiple underlying assets
Author(s)
Labre, Marcelo
Type
Thesis
Abstract
This thesis proposes alternative ways to price contingent claims written on portfolios of
credit instruments as well as on carbon underlying assets. On the first topic of this research
we tackle the pricing of Collateralized Debt Obligations (CDOs) by introducing two
different approaches through the application of respectively Johnson SB distributions and
entropy optimization principles, in contrast to market standard pricing approaches based
on variations of the Gaussian copula model. The relevance of this topic is in line with the
events that unfolded during the “credit crunch” of mid-2007 to early 2009, when CDOs
made headlines as being responsible for more than $542 billion in losses through writedowns
by financial institutions. On the second topic we propose a pricing methodology
for Emission Reduction Purchase Agreement (ERPA) contracts. These are instruments
based on carbon as an asset class and created by the emergence of an international carbon
market that followed the adoption of the Kyoto Protocol (KP) to the United Nations Framework
Convention on Climate Change (UNFCCC) in December 1997. ERPAs are of vital
importance to the function of KP’s market mechanisms and the carbon markets at large
as they formalize transactions of emissions reduction offsets between sellers and buyers,
more specifically transactions involving Certified Emission Reductions (CERs). We propose
a pricing methodology based on stochastic modeling of CER volume delivery risk and
carbon prices as the two main drivers underlying ERPAs, and apply it to a case study on a
run-of-river hydro power CDM project activity in China.
credit instruments as well as on carbon underlying assets. On the first topic of this research
we tackle the pricing of Collateralized Debt Obligations (CDOs) by introducing two
different approaches through the application of respectively Johnson SB distributions and
entropy optimization principles, in contrast to market standard pricing approaches based
on variations of the Gaussian copula model. The relevance of this topic is in line with the
events that unfolded during the “credit crunch” of mid-2007 to early 2009, when CDOs
made headlines as being responsible for more than $542 billion in losses through writedowns
by financial institutions. On the second topic we propose a pricing methodology
for Emission Reduction Purchase Agreement (ERPA) contracts. These are instruments
based on carbon as an asset class and created by the emergence of an international carbon
market that followed the adoption of the Kyoto Protocol (KP) to the United Nations Framework
Convention on Climate Change (UNFCCC) in December 1997. ERPAs are of vital
importance to the function of KP’s market mechanisms and the carbon markets at large
as they formalize transactions of emissions reduction offsets between sellers and buyers,
more specifically transactions involving Certified Emission Reductions (CERs). We propose
a pricing methodology based on stochastic modeling of CER volume delivery risk and
carbon prices as the two main drivers underlying ERPAs, and apply it to a case study on a
run-of-river hydro power CDM project activity in China.
Date Issued
2010-07
Date Awarded
2010-09
Copyright Statement
Attribution NoDerivatives 4.0 International Licence (CC BY-ND)
Advisor
Atkinson, Colin
Creator
Labre, Marcelo
Publisher Department
Mathematics
Publisher Institution
Imperial College London
Qualification Level
Doctoral
Qualification Name
Doctor of Philosophy (PhD)