Work

Testing and forecasting price jumps with return moments

Year: 2025

Type: article

Abstract: We detect jumps with the cubic variation and derive its exact distribution under a generic pure‐diffusion model with deterministic time‐varying volatility. Our method performs well for not only high‐ but also low‐frequency returns. We use the jump testing method to construct monthly and daily jump indicators from the daily and intraday S&P 500 index returns, and find that they can be significantly and robustly predicted by VIX. Other option‐implied and historical moments are either subsumed by VIX or are conditionally useful. Our results support the superior informational role played by the risk‐neutral volatility in predicting future price jump events.

Source: International Review of Finance

DOI: 10.1111/irfi.70002

Authors: Fang Zhen, Xinfeng Ruan, Jin E. Zhang

Institutions: Central University of Finance and Economics, Xi’an Jiaotong-Liverpool University, University of Otago

Language: English

Topic: Stochastic processes and financial applications

Subfield: Finance

Field: Economics, Econometrics and Finance

Domain: Social Sciences

Open Access status: bronze

Funders: University of Otago, Central University of Finance and Economics, Government of Jiangsu Province

Award: G7939476300