Do Stock Prices and Volatility Jump? Reconciling Evidence from Spot and Option Prices


  • Bjørn Eraker

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    • Eraker is from Duke University. I am indebted to Rick Green (the editor) and an anonymous referee for their helpful comments. I also thank Fredrico Bandi, Lars Hansen, Nick Polson, Pietro Veronesi, Mike Johannes, David Bates, Ken Singleton, and Luca Benzoni as well as seminar participants at the University of Chicago, Duke University, McGill University, University de Montreal, University of Toronto, London Business School, Norwegian School of Economics, Northwestern University, University of Iowa, and University of Minnesota for helpful comments and discussions. Remaining errors are mine alone.


This paper examines the empirical performance of jump diffusion models of stock price dynamics from joint options and stock markets data. The paper introduces a model with discontinuous correlated jumps in stock prices and stock price volatility, and with state-dependent arrival intensity. We discuss how to perform likelihood-based inference based upon joint options/returns data and present estimates of risk premiums for jump and volatility risks. The paper finds that while complex jump specifications add little explanatory power in fitting options data, these models fare better in fitting options and returns data simultaneously.