Derivatives and Commodities
Paper Session
Sunday, Jan. 5, 2025 8:00 AM - 10:00 AM (PST)
- Xiaohui Gao, Temple University
Forecasting Option Returns with News
Abstract
This paper examines the information content of news media for the cross-section of expected equity option returns. Applying various machine learning methods, we derive text-based signals from news articles on publicly traded companies that strongly forecast their delta-hedged option returns. The option return predictability is robust to variations in methodology and remains significant after controlling for existing predictors. We propose a text-based method to understand the underlying sources of our textual predictors. We find that the predictive power of the textual predictors stems from a composite effect, with future implied volatility changes being the most decisive, alongside significant contributions of various other option return determinants. Our study highlights the importance of analyzing text data using machine learning approaches to forecast option returns.Decentralized and Centralized Options Trading: A Risk Premia Perspective
Abstract
On-Chain options refer to option contracts, traded directly on a decentralized exchange on a blockchain. We report a novel set of stylized facts about the functioning of this so-called automated market making for options trading. We document the extent to which the On-Chain options differ from their Off-Chain counterparts traded on centralized exchanges. In particular, we find that On-Chain options exhibit larger implied volatilities than Off-Chain options, attributing it to the complex On-Chain fee structure, trading volume, and net demand pressure. We propose a theory explaining the difference in implied volatilities and empirically verify key model implications.Relative Basis and the Expected Returns of Commodity Futures
Abstract
We propose a novel measure, dubbed “relative basis,” to better capture the commodity convenience yield. Our measure is the difference between the traditional near-term basis and a similarly defined distant basis. This simple differencing purges out persistent commodity characteristics in traditional basis, such as storage and financing costs. Relative basis is closely tied to changes in physical inventories and dominates traditional basis in forecasting commodity futures returns. In contrast, relative basis does not forecast the returns of financial futures, which are not subject to inventory constraints. Our results provide new insights into the well-known relation between basis and expected futures returns.Discussant(s)
Bjorn Eraker
,
University of Wisconsin-Madison
Christopher Jones
,
University of Southern California
Hui Chen
,
Massachusetts Institute of Technology
William Diamond
,
University of Pennsylvania
JEL Classifications
- G1 - General Financial Markets