Essays in asset pricing and tail risk / Seo, Sang Byung.

Format:

Book

Thesis/Dissertation

Author/Creator:

Seo, Sang Byung, author.

Contributor:

Wachter, Jessica A., degree supervisor.

Roussanov, Nikolai, degree committee member.

Amir, Amir, degree committee member.

University of Pennsylvania. Finance, degree granting institution.

Language:

English

Subjects (All):

Finance.

Finance--Penn dissertations.

Penn dissertations--Finance.

Local Subjects:

Finance.

Finance--Penn dissertations.

Penn dissertations--Finance.

Genre:

Academic theses.

Physical Description:

1 online resource (199 pages)

Contained In:

Dissertation Abstracts International 76-11A(E).

Place of Publication:

[Philadelphia, Pennsylvania]: University of Pennsylvania ; Ann Arbor : ProQuest Dissertations & Theses, 2015.

Language Note:

English

System Details:

Mode of access: World Wide Web.

text file

Summary:

The first chapter "Option Prices in a Model with Stochastic Disaster Risk," co-authored with Jessica Wachter, studies the consistency between the rare disaster mechanism and options data. In contrast to past work based on an iid setup, we find that a model with stochastic disaster risk can explain average implied volatilities well, despite being calibrated to consumption and aggregate market data alone. Furthermore, we extend the stochastic disaster risk model to a two-factor model and show that it can match variation in the level and slope of implied volatilities, as well as the average implied volatility curves.

The second chapter "Do Rare Events Explain CDX Tranche Spreads?," also co-authored with Jessica Wachter, investigates the rare disaster mechanism based on the data on the CDX index and its tranches. Senior tranches are essentially deep out-of-the-money options because they do not incur any losses until a large number of investment-grade firms default. Using the two-factor stochastic disaster model, we jointly explain the spreads on each CDX tranche, as well as prices on put options and the aggregate market. This paper demonstrates the importance of beliefs about rare disasters and shows a basic consistency in these beliefs across different asset markets.

In the third chapter, "Correlated Defaults and Economic Catastrophes: Linking the CDS Market and Asset Returns," I consider economic catastrophes as massive correlated defaults and construct a catastrophic tail risk measure from joint default probabilities based on my model as well as information contained in the CDS data. Using the rich information contained in this measure, I find that investors put more weight on future extreme events even after the stock market showed signs of recovery from the recent financial crisis. Furthermore, I show that high catastrophic tail risk robustly predicts high future excess returns for various assets, including stocks, government bonds, and corporate bonds. This risk is negatively priced, generating substantial dispersion in the cross section of stock returns. These results consistently indicate that seemingly impossible economic catastrophes are considered as an important risk source when trading assets.

Notes:

Source: Dissertation Abstracts International, Volume: 76-11(E), Section: A.

Advisors: Jessica A. Wachter; Committee members: Amir Amir; Nikolai Roussanov.

Department: Finance.

Ph.D. University of Pennsylvania 2015.

Local Notes:

School code: 0175

ISBN:

9781321851809

Access Restriction:

Restricted for use by site license.