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We formulate and analyze an inverse problem using derivatives prices to obtain an implied filtering density on volatility's hidden state. Stochastic volatility is the unobserved state in a hidden Markov model (HMM) and can be tracked using…

Pricing of Securities · Quantitative Finance 2017-03-07 Carlos Fuertes , Andrew Papanicolaou

We derive a new high-order compact finite difference scheme for option pricing in stochastic volatility jump models, e.g. in Bates model. In such models the option price is determined as the solution of a partial integro-differential…

Computational Finance · Quantitative Finance 2019-02-25 Bertram Düring , Alexander Pitkin

Path integral techniques for the pricing of financial options are mostly based on models that can be recast in terms of a Fokker-Planck differential equation and that, consequently, neglect jumps and only describe drift and diffusion. We…

Pricing of Securities · Quantitative Finance 2010-11-08 L. Z. J. Liang , D. Lemmens , J. Tempere

In this paper we present a rigorously motivated pricing equation for derivatives, including general cash collateralization schemes, which is consistent with quoted market bond prices. Traditionally, there have been differences in how…

Pricing of Securities · Quantitative Finance 2014-09-22 Johan Gunnesson , Alberto Fernández Muñoz de Morales

We study the parameter estimation for parabolic, linear, second-order, stochastic partial differential equations (SPDEs) observing a mild solution on a discrete grid in time and space. A high-frequency regime is considered where the mesh of…

Statistics Theory · Mathematics 2019-09-11 Markus Bibinger , Mathias Trabs

We consider a stochastic volatility asset price model in which the volatility is the absolute value of a continuous Gaussian process with arbitrary prescribed mean and covariance. By exhibiting a Karhunen-Lo\`{e}ve expansion for the…

Mathematical Finance · Quantitative Finance 2017-02-08 Archil Gulisashvili , Frederi Viens , Xin Zhang

In a stochastic volatility framework, we find a general pricing equation for the class of payoffs depending on the terminal value of a market asset and its final quadratic variation. This allows a pricing tool for European-style claims…

Pricing of Securities · Quantitative Finance 2012-06-12 Lorenzo Torricelli

We study dynamic hedging of counterparty risk for a portfolio of credit derivatives. Our empirically driven credit model consists of interacting default intensities which ramp up and then decay after the occurrence of credit events. Using…

Risk Management · Quantitative Finance 2017-09-06 Lijun Bo , Agostino Capponi , Claudia Ceci

In this paper we develop a framework for estimating Probability of Default (PD) based on stochastic models governing an appropriate asset value processes. In particular, we build upon a L\'evy-driven Ornstein-Uhlenbeck process and consider…

Risk Management · Quantitative Finance 2023-09-25 Kyriakos Georgiou , Athanasios N. Yannacopoulos

A variable annuity contract with Guaranteed Minimum Withdrawal Benefit (GMWB) promises to return the entire initial investment through cash withdrawals during the contract plus the remaining account balance at maturity, regardless of the…

Pricing of Securities · Quantitative Finance 2017-01-17 Pavel V. Shevchenko , Xiaolin Luo

We consider the pricing problem related to payoffs that can have discontinuities of polynomial growth. The asset price dynamic is modeled within the Black and Scholes framework characterized by a stochastic volatility term driven by a…

Probability · Mathematics 2016-07-26 Viktor Bezborodov , Luca Di Persio , Yuliya Mishura

In this paper we investigate the pricing problem of a pure endowment contract when the insurer has a limited information on the mortality intensity of the policyholder. The payoff of this kind of policies depends on the residual life time…

Mathematical Finance · Quantitative Finance 2020-07-23 Claudia Ceci , Katia Colaneri , Alessandra Cretarola

This paper studies the stochastic modeling of market drawdown events and the fair valuation of insurance contracts based on drawdowns. We model the asset drawdown process as the current relative distance from the historical maximum of the…

Pricing of Securities · Quantitative Finance 2016-03-11 Hongzhong Zhang , Tim Leung , Olympia Hadjiliadis

Stochastic delay differential equations (SDDE's) have been used for financial modeling. In this article, we study a SDDE obtained by the equation of a CIR process, with an additional fixed delay term in drift; in particular, we prove that…

Probability · Mathematics 2018-06-05 Federico Flore , Giovanna Nappo

The classical derivation of the well-known Vasicek model for interest rates is reformulated in terms of the associated pricing kernel. An advantage of the pricing kernel method is that it allows one to generalize the construction to the…

Mathematical Finance · Quantitative Finance 2019-06-04 Dorje C. Brody , Lane P. Hughston , David M. Meier

Recent empirical studies suggest that the volatilities associated with financial time series exhibit short-range correlations. This entails that the volatility process is very rough and its autocorrelation exhibits sharp decay at the…

Pricing of Securities · Quantitative Finance 2018-04-17 Josselin Garnier , Knut Solna

In this paper, we introduce a model that adds a non-linearity to discounting: the discounting factor may depend on the notional (i.e., discounted values are no longer linear in the notional). In the first part of the paper, we provide a…

Mathematical Finance · Quantitative Finance 2021-10-26 Christian P. Fries

Parametric estimation of stochastic differential equations (SDEs) has been a subject of intense studies already for several decades. The Heston model for instance is driven by two coupled SDEs and is often used in financial mathematics for…

Mathematical Finance · Quantitative Finance 2022-11-29 Jarosław Gruszka , Janusz Szwabiński

We analyze the fluctuation of the loss from default around its large portfolio limit in a class of reduced-form models of correlated firm-by-firm default timing. We prove a weak convergence result for the fluctuation process and use it for…

Probability · Mathematics 2015-02-20 Konstantinos Spiliopoulos , Justin A. Sirignano , Kay Giesecke

Classic stochastic volatility models assume volatility is unobservable. We use the Volatility Index: S&P 500 VIX to observe it, to easier fit the model. We apply it to corporate bonds. We fit autoregression for corporate rates and for risk…

Statistical Finance · Quantitative Finance 2025-01-06 Jihyun Park , Andrey Sarantsev
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