IBSS scholars use options data to quantify jump risk, with findings published in JEDC

Markets may look calm one day and then suddenly surge or plunge the next—“jump” movements that catch many investors off guard. Is there a way to spot signals in the market before prices actually jump? A latest study by Dr Edwin Ruan, Senior Associate Professor in Finance at the International Business School Suzhou (IBSS), Xi’an Jiaotong-Liverpool University (XJTLU), and his co-authors offers an answer. Their paper, “Merton (1976) Implied Jump,” has been formally published in the international journal Journal of Economic Dynamics and Control (JEDC). Building on the classic Merton jump–diffusion model, the study proposes a new method to identify and quantify “implied jumps” from options markets, providing a fresh analytical framework and empirical evidence for understanding sudden market volatility and risk pricing.

In financial economics, implied volatility has long been regarded as a key measure of market risk expectations. It reflects investors’ collective views on future uncertainty and plays a central role in asset pricing and risk management. However, market prices do not always move smoothly—unexpected events, macroeconomic policy shifts, or geopolitical tensions can cause abrupt “jumps” in asset prices. These jump risks play an essential role in market dynamics but are often overlooked or poorly captured by traditional volatility indicators. Motivated by this gap, the study addresses a long-standing question in financial research: can we infer the market’s expectation of jump risks directly from option prices, just as we infer volatility expectations?

Dr Ruan and his team provide an innovative answer to this question. Grounded in Merton’s 1976 jump-diffusion model, they develop a new empirical method that extracts investors’ expectations about market jumps directly from option data. By systematically estimating model parameters and leveraging cross-sectional option price information, the study isolates market-implied jump characteristics. Within this framework, the researchers introduce two new indices, the Implied Jump Expectation Index (JIX) and the Implied Jump Volatility Index (JVIX),  which respectively capture the market’s expectation of jump magnitude and jump uncertainty. Unlike conventional volatility-based measures, these indices uncover investors’ sentiment and risk compensation mechanisms under extreme market conditions.

Analyzing over a decade of U.S. index option data, the study finds that the implied jump indices are strongly correlated with subsequent market performance. Periods of elevated jump expectations are often followed by higher realized returns or increased risk premia, suggesting that investors indeed price in potential extreme events when trading options. Moreover, the implied jump indices demonstrate superior predictive power for future volatility. Incorporating these indices into conventional volatility forecasting models significantly enhances their explanatory and predictive accuracy.

The contribution of this research lies not only in introducing a new measurement framework for implied jumps but also in bridging theoretical and empirical perspectives. By making the market’s hidden jump expectations visible and measurable, the study provides valuable tools for investigating extreme risks, tail events, and investor sentiment. It also offers new insights for regulators and practitioners seeking to monitor systemic risks and understand the transmission of financial shocks. In practice, this framework can be extended beyond equity markets to commodities, foreign exchange, and other asset classes, facilitating a more comprehensive assessment of potential risk accumulation and contagion channels.

Dr Xinfeng (Edwin) Ruan (阮鑫丰) is a Senior Associate Professor of Finance and Distinguished Professor of Jiangsu Province (江苏省特聘教授) at the International Business School Suzhou (IBSS) of Xian-Jiaotong Liverpool University (XJTLU). Edwin earned his PhD in Finance from the University of Otago in 2017 and an MSc in Operations Research Management (Research Area: Financial Mathematics and Financial Engineering) from the Southwestern University of Finance and Economics (SWUFE) in 2014. Prior to joining XJTLU, he worked at the University of Otago from 2019 to 2023 and was a Postdoctoral Research Fellow at the Auckland University of Technology from 2018 to 2019. Edwin’s research interests mainly focus on asset pricing and derivatives, both in theoretical and empirical domains. He has extensive research experience in these areas and has published more than 30 papers in highly regarded, peer-reviewed journals, such as the Journal of Financial Markets, Journal of Economic Dynamics and Control, and Journal of Futures Markets. Edwin's outstanding research has been recognized with the Otago Business School Best Emerging Researcher award in 2019. He has won several best paper awards at recent national and international conferences. He currently serves as Associate Editor of the Journal of Chinese Economic and Business Studies (Impact Factor: 3.7) and has successfully supervised eight PhD students in Finance.

The Journal of Economic Dynamics and Control (JEDC) is an internationally renowned academic journal focusing on economic dynamics, control theory, and empirical applications. It publishes cutting-edge research on topics such as macroeconomic modeling, dynamic equilibrium analysis, optimal control, and nonlinear dynamic systems, while also encouraging studies that integrate computational methods, numerical simulations, and data-driven approaches into economics and finance. JEDC provides a scholarly platform that bridges economic theory, dynamic analysis, and computational techniques to advance the understanding of complex economic systems and mechanisms. The journal is ranked ABDC-A*.