Using interpolated implied volatility for analysing exogenous market changes

Matúš Maciak () and Sebastiano Vitali ()
Additional contact information
Matúš Maciak: Charles University
Sebastiano Vitali: University of Bergamo

Computational Management Science, 2024, vol. 21, issue 1, No 25, 21 pages

Abstract: Abstract This paper focuses on market changes due to exogenous effects. The standard implied volatility is shown to be insufficient for a proper detection and analysis of this type of risk. This is mainly because such changes are usually dominated by endogenous effects coming from a specific trading mechanism or natural market dynamics. A methodologically unique approach based on artificial options that always have a constant time to maturity is proposed and explicitly defined. The key principle is to use interpolated volatilities, which can effectively eliminate instabilities due to the natural market dynamics while the changes caused by the exogenous causes are preserved. Formal statistical tests for distinguishing significant effects are proposed under different theoretical and practical scenarios. Statistical theory, computational and algorithmic details, and comprehensive empirical comparisons together with a real data illustration are all presented.

Keywords: Implied volatility; Exogenous effects; Artificial options; Constant time to maturity; Panel data; Changepoint detection (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://link.springer.com/10.1007/s10287-024-00505-2 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

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:spr:comgts:v:21:y:2024:i:1:d:10.1007_s10287-024-00505-2

Ordering information: This journal article can be ordered from
http://www.springer. ... ch/journal/10287/PS2

DOI: 10.1007/s10287-024-00505-2

Access Statistics for this article

Computational Management Science is currently edited by Ruediger Schultz

More articles in Computational Management Science from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().