Asset Pricing: Derivatives
Paper Session
Friday, Jan. 5, 2024 8:00 AM - 10:00 AM (CST)
- Chair: Jefferson Duarte, Rice University
Market Risk Premium Expectation: Combining Option Theory with Traditional Predictors
Abstract
Recently there is a growing literature on predicting the market risk premium from the option market, shedding new insights on the traditional voluminous literature of market predictability that relies on economic state variables. This paper provides a novel link between these literatures. Theoretically, we derive a generalized lower bound on the expected market risk premium that combines both options and state variables. Empirically, we find that the new bound significantly enhances the out-of-sample market predictability compared to using either type of information alone, with gains more pronounced in the short horizons such as one to three months.The Risk and Return of Equity and Credit Index Options
Abstract
We develop a structural credit risk model, which allows us to price equity/credit indices and their options through the asset dynamics of index constituents. We estimate the model via MLE and find that equity and credit index option prices are well explained out-of-sample. Contrary to recent empirical findings, the two option markets are not inconsistently priced through the lens of our model. Returns on both options, while extreme, do not indicate any evidence of mispricing. Our analysis suggests that jointly addressing the pricing of various instruments requires a balance between three sources of systematic risk: asset, variance, and jump risks.Exploring the Variance Risk Premium across Assets
Abstract
This paper explores the variance risk premium in option returns across twenty different futures, including equities, bonds, currencies, and commodities (energy, metals, and grains). We implement a novel model-free methodology that constructs tradable option portfolios, which replicate realized variance. In the period 2006–2020, most assets had significant variance risk premiums, but the realized S&P 500 variance risk premium was not significantly different from zero. Withina particular asset, option prices across different strikes are related to the level of volatility and the correlation of volatility with futures returns. Returns to variance are not associated with systematic risk, but are related to fat tails, consistent with option dealers demanding a premium for holdingidiosyncratic volatility risk. Contrary to Bollerslev et al. (2009), we find that option-implied variance does not positively predict underlying futures returns for the majority of assets. However, implied variance does predict returns to variance-sensitive option portfolios.
Discussant(s)
Dmitriy Muravyev
,
Michigan State University
Kerry Back
,
Rice University
Anders Trolle
,
Copenhagen Business School
Kris Jacobs
,
University of Houston
JEL Classifications
- G1 - General Financial Markets