Essays in Financial Markets and Time Series Econometrics

Resource type
Thesis type
(Thesis) Ph.D.
Date created
This thesis consists of two independent essays on financial econometrics. The first study introduces a new family of portmanteau tests for serial correlation. Using the wavelet transform, we decompose the variance of the underlying process into the variance of its low frequency and of its high frequency components and we design a variance ratio test of no serial correlation in the presence of dependence. Such decomposition can be carried out iteratively, each wavelet filter leading to a rich family of tests whose joint limiting null distribution is a multivariate normal. We illustrate the size and power properties of the proposed tests through Monte Carlo simulations. The second study focuses on counterparty risk and its role as a determinant of corporate credit spreads. However, there are only a few techniques available to isolate it from other factors. In this paper we describe a model of financial networks that is suitable for the construction of proxies for counterparty risk. Using data on the U.S. supplier-customer network of public companies, we find that, for each supplier, counterparties' leverage and jump risk are significant determinants of corporate credit spreads. Our findings are robust after controlling for several idiosyncratic, industry, and market factors.
Copyright statement
Copyright is held by the author.
This thesis may be printed or downloaded for non-commercial research and scholarly purposes.
Scholarly level
Supervisor or Senior Supervisor
Thesis advisor: Gencay, Ramazan
Member of collection
Download file Size
etd9607_DSignori.pdf 2.73 MB

Views & downloads - as of June 2023

Views: 0
Downloads: 1