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We propose a new framework for modeling stochastic local volatility, with potential applications to modeling derivatives on interest rates, commodities, credit, equity, FX etc., as well as hybrid derivatives. Our model extends the…

Pricing of Securities · Quantitative Finance 2013-03-29 Igor Halperin , Andrey Itkin

We introduce a multi-factor stochastic volatility model based on the CIR/Heston volatility process that incorporates seasonality and the Samuelson effect. First, we give conditions on the seasonal term under which the corresponding…

Pricing of Securities · Quantitative Finance 2015-06-22 Lorenz Schneider , Bertrand Tavin

We consider an asset whose risk-neutral dynamics are described by a general class of local-stochastic volatility models and derive a family of asymptotic expansions for European-style option prices and implied volatilities. Our implied…

Computational Finance · Quantitative Finance 2014-12-01 Matthew Lorig , Stefano Pagliarani , Andrea Pascucci

In this paper we are interested in term structure models for pricing zero coupon bonds under rapidly oscillating stochastic volatility. We analyze solutions to the generalized Cox-Ingersoll-Ross two factors model describing clustering of…

Computational Finance · Quantitative Finance 2008-12-10 B. Stehlikova , D. Sevcovic

It is well known that the Cox-Ingersoll-Ross (CIR) stochastic model to study the term structure of interest rates, as introduced in 1985, is inadequate for modelling the current market environment with negative short interest rates.…

Computational Finance · Quantitative Finance 2018-06-12 Giuseppe Orlando , Rosa Maria Mininni , Michele Bufalo

In this paper, we consider three stochastic-volatility models, each characterized by distinct dynamics of instantaneous volatility: (1) a CIR process for squared volatility (i.e., the classical Heston model); (2) a mean-reverting lognormal…

Pricing of Securities · Quantitative Finance 2025-10-14 V. Perederiy

We propose to model multivariate volatility processes based on the newly defined conditionally uncorrelated components (CUCs). This model represents a parsimonious representation for matrix-valued processes. It is flexible in the sense that…

Statistics Theory · Mathematics 2007-06-13 Jianqing Fan , Mingjin Wang , Qiwei Yao

The purpose of this paper is to study the generalized Fong--Vasicek two-factor interest rate model with stochastic volatility. In this model the dispersion of the stochastic short rate (square of volatility) is assumed to be stochastic as…

Statistical Finance · Quantitative Finance 2008-12-10 B. Stehlikova , D. Sevcovic

We introduce a multi-factor stochastic volatility model based on the CIR/Heston stochastic volatility process. In order to capture the Samuelson effect displayed by commodity futures contracts, we add expiry-dependent exponential damping…

Pricing of Securities · Quantitative Finance 2015-02-23 Lorenz Schneider , Bertrand Tavin

In 'A Closed-Form Solution for Options with Stochastic Volatility with Applications to Bond and Currency Options', Heston proposes a Stochastic Volatility (SV) model with constant interest rate and derives a semi-explicit valuation formula.…

Computational Finance · Quantitative Finance 2021-03-10 Javier de Frutos , Victor Gaton

The discrete-time multifactor Vasi\v{c}ek model is a tractable Gaussian spot rate model. Typically, two- or three-factor versions allow one to capture the dependence structure between yields with different times to maturity in an…

Mathematical Finance · Quantitative Finance 2016-09-05 Philipp Harms , David Stefanovits , Josef Teichmann , Mario V. Wüthrich

We study a two-dimensional McKean-Vlasov stochastic differential equation, whose volatility coefficient depends on the conditional distribution of the second component with respect to the first component. We prove the strong existence and…

Probability · Mathematics 2024-06-21 Scander Mustapha

We present small-time implied volatility asymptotics for Realised Variance (RV) and VIX options for a number of (rough) stochastic volatility models via large deviations principle. We provide numerical results along with efficient and…

Mathematical Finance · Quantitative Finance 2020-11-03 Chloe Lacombe , Aitor Muguruza , Henry Stone

This paper presents a novel approach to stochastic volatility (SV) modeling by utilizing nonparametric techniques that enhance our ability to capture the volatility of financial time series data, with a particular emphasis on the…

Computation · Statistics 2025-02-18 Yudong Feng , Ashis Gangopadhyay

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

This study deals with the pricing and hedging of single-tranche collateralized debt obligations (STCDOs). We specify an affine two-factor model in which a catastrophic risk component is incorporated. Apart from being analytically tractable,…

Mathematical Finance · Quantitative Finance 2020-11-23 Zehra Eksi , Damir Filipović

We propose a formulation to construct new classes of financial price processes based on the insight that the key variable driving prices $P$ is the earning-over-price ratio $\gamma \simeq 1/P$, which we refer to as the earning yield and is…

Mathematical Finance · Quantitative Finance 2023-06-21 Li Lin , Didier Sornette

In an incomplete continuous-time securities market with uncertainty generated by Brownian motions, we derive closed-form solutions for the equilibrium interest rate and market price of risk processes. The economy has a finite number of…

General Finance · Quantitative Finance 2012-01-06 Peter Ove Christensen , Kasper Larsen

Income and risk coexist, yet investors are often so focused on chasing high returns that they overlook the potential risks that can lead to high losses. Therefore, risk forecasting and risk control is the cornerstone of investment. To…

Applications · Statistics 2023-11-14 Xinyuan Song

Vector autoregressions (VARs) with multivariate stochastic volatility are widely used for structural analysis. Often the structural model identified through economically meaningful restrictions--e.g., sign restrictions--is supposed to be…

Econometrics · Economics 2022-07-11 Joshua Chan , Eric Eisenstat , Xuewen Yu
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