Catastrophic risks and the pricing of catastrophe equity put options

Massimo Arnone, Michele Leonardo Bianchi (), Anna Grazia Quaranta () and Gian Luca Tassinari ()
Additional contact information
Michele Leonardo Bianchi: Bank of Italy
Anna Grazia Quaranta: University of Macerata
Gian Luca Tassinari: University of Bologna

Computational Management Science, 2021, vol. 18, issue 2, No 5, 213-237

Abstract: Abstract In this paper, after a review of the most common financial strategies and products that insurance companies use to hedge catastrophic risks, we study an option pricing model based on processes with jumps where the catastrophic event is captured by a compound Poisson process with negative jumps. Given the importance that catastrophe equity put options (CatEPuts) have in this context, we introduce a pricing approach that provides not only a theoretical contribution whose applicability remains confined to purely numerical examples and experiments, but which can be implemented starting from real data and applied to the evaluation of real CatEPuts. We propose a calibration framework based on historical log-returns, market capitalization and option implied volatilities. The calibrated parameters are then considered to price CatEPuts written on the stock of the main Italian insurance company over the high volatile period from January to April 2020. We show that the ratio between plain-vanilla put options and CatEPuts strictly depends on the shape of the implied volatility smile and it varies over time.

Keywords: Catastrophe equity put options; Variance gamma; Compound Poisson; Double-calibration (search for similar items in EconPapers)
JEL-codes: C2 C63 G1 G12 G22 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)

Downloads: (external link)
http://link.springer.com/10.1007/s10287-021-00391-y 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:18:y:2021:i:2:d:10.1007_s10287-021-00391-y

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

DOI: 10.1007/s10287-021-00391-y

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 ().