Work

The Continuous‐Time Limit of Quasi Score‐Driven Volatility Models

Year: 2025

Type: article

Abstract: ABSTRACT This article explores the continuous‐time limit of a class of quasi score‐driven (QSD) models that characterize volatility. As the sampling frequency increases and the time interval tends to zero, the model weakly converges to a continuous‐time stochastic volatility model where the two Brownian motions are correlated, thereby capturing the leverage effect in the market. Subsequently, we identify that a necessary condition for nondegenerate correlation is that the distribution of driving innovations differs from that of computing score, and at least one being asymmetric. We then illustrate this with two typical examples. As an application, the QSD model is used as an approximation for correlated stochastic volatility diffusions and quasi maximum likelihood estimation is performed. Simulation results confirm the method's effectiveness, particularly in estimating the correlation coefficient.

Source: Journal of Time Series Analysis

DOI: 10.1111/jtsa.12848

Authors: Yinhao Wu, Ping He

Institution: Shanghai University of Finance and Economics

Language: English

Topic: Financial Risk and Volatility Modeling

Subfield: Finance

Field: Economics, Econometrics and Finance

Domain: Social Sciences

Open Access status: green

Funders: National Natural Science Foundation of China, Fundamental Research Funds for the Central Universities

Awards: G1874091595, G8623491822