This paper proposes a linear option pricing model by imposing common market pricing on decentralized risk exposure estimates across option contracts underlying the same security. The model embeds historical moment estimators to anchor the breakeven contribution of each risk source. A...

In this article, the Universal Approximation Theorem of Artificial Neural Networks (ANNs) is applied to the SABR stochastic volatility model in order to construct highly efficient representations. Initially, the SABR approximation of Hagan et al. [2002] is considered, then a more accurate...

The stock options implied volatility skew reflects both the structural risk characteristics of the underlying company and the short-term information flow about the stock price movement. This paper builds a semi-structural cross-sectional option pricing model to separate the structural risk...

This work discusses the calibration of instantaneous Libor correlations in the Libor market model. We extend existing calibration strategies by incorporation of spread option implied correlation information. The correlation structure implied by CMS spread options observed in the present-day's...

In this paper we propose a maximum entropy estimator for the asymptotic distribution of the hedging error for options. Perfect replication of financial derivatives is not possible, due to market incompleteness and discrete-time hedging. We derive the asymptotic hedging error for options under a...

We examine the distribution of realized Bitcoin daily log-returns and find significantly-thin tails. From there we construct a simple connection back to traditional volatility modelling. And then we discuss how this connection can serve as a foundation to leverage existing derivative quant...

The Polynomial Chaos Expansion (PCE) technique recovers a finite second order random variable exploiting suitable linear combinations of orthogonal polynomials which are functions of a given stochastic quantity $\xi$, hence acting as a kind of random basis. The PCE methodology has been developed...

This paper presents a tractable model of non-linear dynamics of market returns using a Langevin approach.Due to non-linearity of an interaction potential, the model admits regimes of both small and large return fluctuations. Langevin dynamics are mapped onto an equivalent quantum mechanical (QM)...

This paper presents a new option pricing approach for all underlying assets that precisely fits the market data. We obtain the probability density function of the underlying asset without any external parameter. The density function for a given expiration date is uniquely determined by the...

This paper develops a lattice method for option evaluation in the presence of regime shifts in the correlation structure of assets, aiming at investigating whether the option prices reflect such shifts. Specifically we try to investigate whether option prices reflect switches in the correlation...