𝔖 Bobbio Scriptorium
✦   LIBER   ✦

Testing range estimators of historical volatility

✍ Scribed by Jinghong Shu; Jin E. Zhang

Book ID
102219565
Publisher
John Wiley and Sons
Year
2006
Tongue
English
Weight
122 KB
Volume
26
Category
Article
ISSN
0270-7314

No coin nor oath required. For personal study only.

✦ Synopsis

Abstract

This study investigates the relative performance of various historical volatility estimators that incorporate daily trading range: M. Parkinson (1980), M. Garman and M. Klass (1980), L. C. G. Rogers and S. E. Satchell (1991), and D. Yang and Q. Zhang (2000). It is found that the range estimators all perform very well when an asset price follows a continuous geometric Brownian motion. However, significant differences among various range estimators are detected if the asset return distribution involves an opening jump or a large drift. By adding microstructure noise to the Monte Carlo simulation, the finding of S. Alizadeh, M. W. Brandt, and F. X. Diebold (2002)—that range estimators are fairly robust toward microstructure effects—is confirmed. An empirical test with S&P 500 index return data shows that the variances estimated with range estimators are quite close to the daily integrated variance. The empirical results support the use of range estimators for actual market data. © 2006 Wiley Periodicals, Inc. Jrl Fut Mark 26:297–313, 2006

📜 SIMILAR VOLUMES

Estimation and forecasting of stock vola
Estimation and forecasting of stock volatility with range-based estimators
✍ Joshy Jacob; Vipul 📂 Article 📅 2008 🏛 John Wiley and Sons 🌐 English ⚖ 303 KB

## Abstract This paper examines the estimation and forecasting performance of range‐based volatility estimators for stocks, with two‐scales realized volatility as the benchmark. There is evidence that the daily range‐based estimators provide an efficient and low‐bias alternative to the return‐based

A comparative study of range-based stock
A comparative study of range-based stock return volatility estimators for the German market
✍ Neda Todorova; Sven Husmann 📂 Article 📅 2011 🏛 John Wiley and Sons 🌐 English ⚖ 166 KB 👁 1 views

We thank the editor, Robert Webb, and an anonymous referee for their helpful comments. We also thank Thorben Lubnau, Tyge-F. Kummer, and the participants of the 2nd International Finance Conference of the Indian Institute of Management, Calcutta for their suggestions.

Forecasting performance of extreme-value
Forecasting performance of extreme-value volatility estimators
✍ Vipul; Joshy Jacob 📂 Article 📅 2007 🏛 John Wiley and Sons 🌐 English ⚖ 149 KB

## Abstract This study evaluates the forecasting performance of extreme‐value volatility estimators for the equity‐based Nifty Index using two‐scale realized volatility. This benchmark mitigates the effect of microstructure noise in the realized volatility. Extreme‐value estimates with relatively s