Stock market daily volatility and information measures of predictability

D’Amico, Guglielmo, Fulvio Gismondi, Filippo Petroni and Flavio Prattico

Physica A: Statistical Mechanics and its Applications, 2019, vol. 518, issue C, 22-29

Abstract: The main purpose of this work is to investigate the relation between some measures in information theory and the accuracy of volatility forecasting using a model of asset returns. First we highlight the dependence between volatility forecasting and entropy and then we determine the relation between predictability and volatility. The study is conducted using a database of 65 stocks of the Dow Jones Composite Average from 1973 to 2014 and by computing the daily volatility of the market index. To this end we use the standard GARCH approach to model and forecast the daily volatility. The main result of this paper is the establishment of a relationship between the accuracy of the volatility forecast and the entropy of the time series of price returns. Since the entropy changes in time, before computing a forecast of the volatility it is recommended to compute the entropy of the time series that furnishes an important indicator on the limit of successive volatility forecast.

Keywords: Information theory; Entropy; Predictability; GARCH; Forecasting (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0378437118314869
Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:518:y:2019:i:c:p:22-29

DOI: 10.1016/j.physa.2018.11.049

Access Statistics for this article

Physica A: Statistical Mechanics and its Applications is currently edited by K. A. Dawson, J. O. Indekeu, H.E. Stanley and C. Tsallis

More articles in Physica A: Statistical Mechanics and its Applications from Elsevier
Bibliographic data for series maintained by Catherine Liu ().