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
The market risk premium is central in finance and has been analyzed by numerous studies in the time-series predictability literature and by growing studies in the options literature. In this paper, we provide a novel link between the two literatures. Theoretically, we derive a lower bound on the equity risk premium in terms of option prices and state variables. Empirically, we show that combining information from both options and investor sentiment significantly improves the out-of-sample predictability of the market risk premium versus using either type of information alone and adding an economic upper bound raises predictability further.The Risk and Return of Equity and Credit Index Options
Abstract
We estimate a structural model of equity and credit options using data on index default swap and physical equity index volatility. The model predicts reasonable time-series of level, skew, and term-structure of equity- and credit-index implied volatilities out-of-sample. Furthermore, the model predictions for option expected returns closely match empirical estimates. Decomposing returns into asset, variance, and jump risks, we study the sources of risk-return compensation in both derivative markets. Credit-index option expected returns are higher in absolute terms and depend more on variance risk than their equity counterparts which are primarily impacted by systematic asset 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