Service interruption on Monday 11 July from 12:30 to 13:00: all the sites of the CCSD (HAL, Epiciences, SciencesConf, AureHAL) will be inaccessible (network hardware connection).
Skip to Main content Skip to Navigation
Preprints, Working Papers, ...

Tempered Stable Processes with Time Varying Exponential Tails

Abstract : In this paper, we introduce a new time series model having a stochastic exponential tail. This model is constructed based on the Normal Tempered Stable distribution with a time-varying parameter. The model captures the stochastic exponential tail, which generates the volatility smile effect and volatility term structure in option pricing. Moreover, the model describes the time-varying volatility of volatility. We empirically show the stochastic skewness and stochastic kurtosis by applying the model to analyze S\&P 500 index return data. We present the Monte-Carlo simulation technique for the parameter calibration of the model for the S\&P 500 option prices. We can see that the stochastic exponential tail makes the model better to analyze the market option prices by the calibration.
Complete list of metadata

https://hal-paris1.archives-ouvertes.fr/hal-03018495
Contributor : Raphael DOUADY Connect in order to contact the contributor
Submitted on : Sunday, November 22, 2020 - 6:39:18 PM
Last modification on : Friday, April 29, 2022 - 10:12:43 AM
Long-term archiving on: : Tuesday, February 23, 2021 - 9:39:49 PM

File

draft_Proof_hi (2).pdf
Files produced by the author(s)

Identifiers

  • HAL Id : hal-03018495, version 1

Collections

Citation

young Shin Aaron Kim, Kum-Hwan Roh, Raphaël Douady. Tempered Stable Processes with Time Varying Exponential Tails. 2020. ⟨hal-03018495⟩

Share

Metrics

Record views

47

Files downloads

56