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HistoricalVolatilit​y

version 1.1.6 (21.1 KB) by Tommaso Belluzzo
A framework for historical volatility estimation and analysis.

4 Downloads

Updated 06 Aug 2019

GitHub view license on GitHub

# INTRODUCTION #

This script calculates and analyses the following historical volatility estimators:

> the traditional Close-to-Close estimator (and a variant of it that uses demeaned returns);
> the Parkinson estimator (1980);
> the Garman-Klass estimator (1980) and a variant proposed by Yang & Zhang (2000);
> the Rogers-Satchell estimator (1991);
> the Hodges-Tompkins estimator (2002);
> the Yang-Zhang estimator (2000);
> the Meilijson estimator (2009).

# USAGE #

1) Edit the "run.m" script following your needs.
2) Execute the "run.m" script.

# DATASET #

The script fetches historical time series from "Yahoo! Finance"; it shound't be too difficult to replace it with an alternative data source. The example is based on the returns of "J.P. Morgan Chase & Co." (JPM) between January 2010 and December 2017.

Cite As

Tommaso Belluzzo (2019). HistoricalVolatility (https://www.github.com/TommasoBelluzzo/HistoricalVolatility), GitHub. Retrieved .

Comments and Ratings (4)

Dear S.G., following your suggestions I'll try to modify the script so that it can accept both file feeds and market data. I cannot provide a release date for the moment. Thanks!

S. G.

Great job but Yahoo gives problem. I suggest to modify the script for providing data files instead.

Updates

1.1.6

Minor fixes and improvements.

1.1.5

Minor fixes and improvements.

1.1.4

Updated details concerning compatibility & requirements.

1.1.3

Updated details concerning compatibility & requirements.

1.1.2

Minor fixes and improvements.

1.1.1

Project website.

1.1.0

Target release.

1.0.9

Improved tags.

1.0.8

Improved tags.

1.0.7

Improved tags.

1.0.6

Improved description.

1.0.5

Improved description.

1.0.4

Improved description.

1.0.3

Added screenshot.

1.0.2

Minor fixes and improvements.

1.0.1

Added details concerning compatibility & requirements.

MATLAB Release Compatibility
Created with R2014b
Compatible with R2014b to R2018b
Platform Compatibility
Windows macOS Linux