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Essays in asset pricing and tail risk.

Seo, Sang Byung.

Essays in asset pricing and tail risk.

Record Type:	Electronic resources : Monograph/item
Title/Author:	Essays in asset pricing and tail risk.
Author:	Seo, Sang Byung.
Description:	199 p.
Notes:	Source: Dissertation Abstracts International, Volume: 76-11(E), Section: A.
Notes:	Adviser: Jessica A. Wachter.
Contained By:	Dissertation Abstracts International76-11A(E).
Subject:	Finance.
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3709549
ISBN:	9781321851809

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

Essays in asset pricing and tail risk. - 199 p.

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

Thesis (Ph.D.)--University of Pennsylvania, 2015.

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.

ISBN: 9781321851809Subjects--Topical Terms:

183252
Finance.

Essays in asset pricing and tail risk.
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245 1 0 $a Essays in asset pricing and tail risk.
300 $a 199 p.
500 $a Source: Dissertation Abstracts International, Volume: 76-11(E), Section: A.
500 $a Adviser: Jessica A. Wachter.
502 $a Thesis (Ph.D.)--University of Pennsylvania, 2015.
520 $a 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.
520 $a 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.
520 $a 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.
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