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Rare Events

Paper Session

Sunday, Jan. 5, 2020 1:00 PM - 3:00 PM (PDT)

Manchester Grand Hyatt, Cortez Hill B
Hosted By: Econometric Society
  • Chair: Winston Wei Dou, University of Pennsylvania

Credit and Option Risk Premia

Lars Kuehn
,
Carnegie Mellon University
David Schreindorfer
,
Arizona State University
Florian Schulz
,
University of Washington

Abstract

We estimate a structural model of credit risk to quantify the impact of time-varying bankruptcy costs and risk on credit spreads. To identify these channels, the estimation relies on information in firm-level CDS rates and option prices. While CDS rates are sensitive to both time-varying bankruptcy costs and risk, equity option prices are only sensitive to risk because equity holders lose everything in bankruptcy. Our model features a representative agent with recursive preferences and Markov-switching states for the drift and volatility of consumption and earnings growth. The dynamics for consumption and earnings feature persistent and rare economic disasters, which are crucial for the valuation of CDS and option contracts. Firms issue debt trading off tax benefits and bankruptcy costs, refinance when their interest coverage ratio is too high, and optimally default when their interest coverage ratio is too low. A structural decomposition reveals that time-variation in expected loss rates account for 14% and time-variation in risk for 74% of the level of credit spreads.

Flights to Safety and Volatility Pricing

Claudia Moise
,
Duke University

Abstract

Unexpected shifts in the realized stock market volatility, often associated with financial crises, carry a significantly negative risk premium across stocks and Treasuries, which suggests the existence of a unified pricing model. Investors require a premium for holding the risky assets (stocks), which correlate negatively with volatility surprises, while they are willing to pay a premium for holding the safe assets (Treasury bonds), which correlate positively. This is consistent with investors' "flights to safety", and the corresponding change in sign in the stock-bond correlation, during times of economic uncertainty. Furthermore, because of their positive loadings on volatility, bonds perform well in bad times, which explains their lower expected returns. Interestingly, the joint pricing of stocks and Treasuries leads to economically meaningful and statistically significant risk premia estimates, and to a good performance of asset pricing models. In contrast, both the implied volatility index, VIX, and the tail index, SKEW, are not robustly priced across the two financial markets.

Jumps and the Correlation Risk Premium: Evidence from Equity Options

Nicole Branger
,
University of Muenster
René Flacke
,
University of Muenster
Frederik Middelhoff
,
University of Muenster

Abstract

This paper breaks the correlation risk premium down into two components: a premium related to the correlation of continuous stock price movements and a premium for bearing the risk of co-jumps. We propose a novel way to identify both premiums based on a dispersion trading strategy that goes long an index option portfolio and short a basket of option portfolios on the constituents. The option portfolios are constructed to only load on either diffusive volatility or jump risk. We document that both risk premiums are economically and statistically significant for the S&P 100 index. In particular, selling insurance against states of high jump correlation generates a sizable annualized Sharpe ratio of 0.85.

Aggregate Asymmetry in Idiosyncratic Jump Risk

Huidi Lin
,
Northwestern University
Viktor Todorov
,
Northwestern University

Abstract

We study the structure and pricing of idiosyncratic jumps, i.e., jumps in asset prices that occur outside market-wide jump events. Using options on individual stocks and the market index that are close to expiration as well as local estimates of market betas from returns on the underlying assets, we estimate nonparametrically the asymmetry in the risk-neutral expected idiosyncratic variation, i.e., the difference in variation due to negative and positive returns, which asymptotically is solely attributed to jumps. We derive a feasible Central Limit Theorem that allows to quantify precision in the estimation, with the limiting distribution being mixed Gaussian. We find strong empirical evidence for aggregate asymmetry in idiosyncratic risk which shows that such risk clusters cross-sectionally. Our results reveal the existence and non-trivial pricing of aggregate downside tail risk in stocks during market-neutral systematic events as well as a negative skew in the cross-sectional return distribution during such episodes.
Discussant(s)
Boris Nikolov
,
University of Lausanne and Swiss Finance Institute
Alan Moreira
,
University of Rochester
David Weinbaum
,
Syracuse University
Mete Kilic
,
University of Southern California
JEL Classifications
  • G1 - General Financial Markets
  • E3 - Prices, Business Fluctuations, and Cycles