Renewal Based Volatility Estimation

41 Pages Posted: 22 Feb 2018 Last revised: 25 Sep 2019

See all articles by Yifan Li

Yifan Li

University of Manchester - Alliance Manchester Business School; Lancaster University - Department of Accounting and Finance

Ingmar Nolte

Lancaster University - Department of Accounting and Finance

Sandra Nolte (Lechner)

Lancaster University Management School

Date Written: April 4, 2019

Abstract

This paper develops the idea of renewal time sampling, a novel sampling scheme constructed from stopping times of semimartingales. Based on this new sampling scheme we propose a class of volatility estimators named renewal based volatility estimators. In this paper we show that: (1) The spot variance of a continuous martingale can be expressed in terms of the conditional intensity or conditional duration density of renewal sampling times; (2) In an infill asymptotics setting, renewal based volatility estimators are consistent and jump-robust estimators of the integrated variance of a general semimartingale; (3) Renewal time sampling and range-based sampling have a higher sampling efficiency than equidistant return-based sampling.

Keywords: High-Frequency Volatility Estimation, Realized Volatility, Renewal Theory

JEL Classification: C02, C13, C14, C51

Suggested Citation

Li, Yifan and Nolte, Ingmar and Nolte (Lechner), Sandra, Renewal Based Volatility Estimation (April 4, 2019). Available at SSRN: https://ssrn.com/abstract=3123062 or http://dx.doi.org/10.2139/ssrn.3123062

Yifan Li (Contact Author)

University of Manchester - Alliance Manchester Business School ( email )

Booth Street West
Manchester, M15 6PB
United Kingdom

Lancaster University - Department of Accounting and Finance ( email )

The Management School
Lancaster LA1 4YX
United Kingdom

Ingmar Nolte

Lancaster University - Department of Accounting and Finance ( email )

Lancaster, Lancashire LA1 4YX
United Kingdom

Sandra Nolte (Lechner)

Lancaster University Management School ( email )

Lancaster, Lancashire LA1 4YX
United Kingdom

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