This website uses cookies.

By clicking the "Accept" button or continuing to browse our site, you agree to first-party and session-only cookies being stored on your device to enhance site navigation and analyze site performance and traffic. For more information on our use of cookies, please see our Privacy Policy.

« Back to Results

Derivatives

Paper Session

Sunday, Jan. 6, 2019 10:15 AM - 12:15 PM

Hilton Atlanta, 209-210-211
Hosted By: American Finance Association
  • Chair: Neil Pearson, University of Illinois

Decomposing Long Bond Returns: A Decentralized Modeling Approach

Peter Carr
,
New York University

Abstract

We develop a new, decentralized theory that determines the fair value of the yield to maturity on a bond or bond portfolio based purely on the near-term dynamics of its own yield, without the need to make assumptions on the instantaneous interest rate dynamics, nor the need to know whether and how the yield dynamics will change in the future. The new theory decomposes the yield into three components: near-term expectation, risk premium, and convexity effects. We propose to estimate the convexity effect with its recent time series and determine the expectation from either statistical models or economists’ forecasts, leaving the remaining component of the yield as a risk premium estimate. Empirical analysis on US and UK swap rates shows that this risk premium component can predict future bond excess returns.

The Pricing Kernel is U-shaped

Tobias Sichert
,
Goethe University Frankfurt

Abstract

Numerous studies find S-shaped pricing kernels, which is conflicting with standard theory. In contrast to that, based on a novel GARCH model with structural breaks, I show that the pricing kernel is consistently U-shaped. The new pricing kernel estimates imply a downward sloping term structure of risk premia and Sharpe ratios in both good and bad times for the pricing kernel itself. A pricing kernel mimicking trading strategy confirms the predictions and yields sizable Sharpe ratios. Furthermore, the U-shaped pricing kernel helps to explain cross-sectional stock return anomalies. The results are robust to numerous variations in the methodology and hold for several major international stock market indices. Finally, the empirical results can be explained well by a model with a variance-dependent pricing kernel, but only if structural breaks are included in the model.

Is there Smart Money? How Information in the Futures Market is Priced into the Cross-Section of Stock Returns with Delay

Steven Wei Ho
,
Columbia University
Alexandre Lauwers
,
Graduate Institute-Geneva

Abstract

We document a new empirical phenomenon in which the positions of managed money (MM) traders, who are sophisticated speculators in the commodity futures market, as disclosed by the CFTC Disaggregated Commitments of Traders (DCOT) reports, can predict the cross-section of commodity producers' stock returns in the subsequent week. The results are more pronounced in firms with higher information asymmetry, proxied by analyst dispersion and historical volatility. We thus provide more empirical evidence to the literature on investor specialization, market segmentation, informational friction and gradual information diffusion. Our results are also stronger in non-NBER recession periods.

Option Implied Spreads

Christopher Culp
,
Johns Hopkins Institute for Applied Economics
Yoshio Nozawa
,
Federal Reserve Board
Pietro Veronesi
,
University of Chicago

Abstract

We introduce the option-implied spread (IS), a metric alternative to implied volatility (IV) to gauge the relative value of European options. IS is the credit spread implicit in a European option's implied bond, i.e. a portfolio long a safe bond and short a put option. Unlike IV, IS is model-free, it is straightforward to compute, it is consistent across strike prices and maturities, and it has a natural interpretation as the yield -- in excess of risk free rate -- that is implicit in an specific option investment. Empirically, IS and its version normalized by default probability (NIS), are strongly time varying, increase in recessions and with uncertainty, and help predict future option excess returns.
Discussant(s)
Scott Joslin
,
University of Southern California
Mathieu Fournier
,
HEC Montréal
Brian Henderson
,
George Washington University
Dmitriy Muravyev
,
Boston College
JEL Classifications
  • G1 - General Financial Markets