Corpus ID: 236447888

Robustness and sensitivity analyses for rough Volterra stochastic volatility models

@inproceedings{Matas2021RobustnessAS,
  title={Robustness and sensitivity analyses for rough Volterra stochastic volatility models},
  author={Jan Matas and Jan Posp'ivsil},
  year={2021}
}
In this paper we perform robustness and sensitivity analysis of several continuous-time rough Volterra stochastic volatility models with respect to the process of market calibration. Robustness is understood in the sense of sensitivity to changes in the option data structure. The the latter analysis consists of statistical tests to determine whether a given studied model is sensitive to the changes in the option data structure. Empirical study is performed on a data set of Apple Inc. equity… Expand

Figures and Tables from this paper

On simulation of rough Volterra stochastic volatility models
Rough Volterra volatility models are a progressive and promising field of research in derivative pricing. Although rough fractional stochastic volatility models already proved to be superior in realExpand

References

SHOWING 1-10 OF 23 REFERENCES
Robustness and sensitivity analyses for stochastic volatility models under uncertain data structure
TLDR
The robustness of calibrated models is measured using bootstrapping methods on market data and Monte Carlo filtering techniques and an impact of the long memory parameter is measured for the approximative fractional SV model (FSV). Expand
On calibration of stochastic and fractional stochastic volatility models
In this paper we study optimization techniques for calibration of stochastic volatility models to real market data. Several optimization techniques are compared and used in order to solve theExpand
Pricing Under Rough Volatility
From an analysis of the time series of volatility using recent high frequency data, Gatheral, Jaisson and Rosenbaum previously showed that log-volatility behaves essentially as a fractional BrownianExpand
A Closed-Form Solution for Options with Stochastic Volatility with Applications to Bond and Currency Options
I use a new technique to derive a closed-form solution for the price of a European call option on an asset with stochastic volatility. The model allows arbitrary correlation between volatility andExpand
On simulation of rough Volterra stochastic volatility models
Rough Volterra volatility models are a progressive and promising field of research in derivative pricing. Although rough fractional stochastic volatility models already proved to be superior in realExpand
Affine fractional stochastic volatility models
By fractional integration of a square root volatility process, we propose in this paper a long memory extension of the Heston (Rev Financ Stud 6:327–343, 1993) option pricing model. Long memory inExpand
DECOMPOSITION FORMULA FOR ROUGH VOLTERRA STOCHASTIC VOLATILITY MODELS
TLDR
This paper provides a proof of the prediction law for general Gaussian Volterra processes and proposes a hybrid calibration scheme which combines the approximation formula alongside MC simulations which can significantly speed up the calibration to financial markets. Expand
Long memory in continuous-time stochastic volatility models
This paper studies a classical extension of the Black and Scholes model of option pricing, often known as the Hull and White model. Our specificity is that the volatility process is assumed not onlyExpand
The Pricing of Options on Assets with Stochastic Volatilities
One option-pricing problem which has hitherto been unsolved is the pricing of European call on an asset which has a stochastic volatility. This paper examines this problem. The option price isExpand
Jumps and Stochastic Volatility: Exchange Rate Processes Implicit in Deutsche Mark Options
An efficient method is developed for pricing American options on stochastic volatility/jumpdiffusion processes under systematic jump and volatility risk. The parameters implicit in deutsche mark (DM)Expand
...
1
2
3
...