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We prove here a general closed-form expansion formula for forward-start options and the forward implied volatility smile in a large class of models, including the Heston stochastic volatility and time-changed exponential L\'evy models. This…

Pricing of Securities · Quantitative Finance 2015-02-05 Antoine Jacquier , Patrick Roome

This article present a continuous cascade model of volatility formulated as a stochastic differential equation. Two independent Brownian motions are introduced as random sources triggering the volatility cascade. One multiplicatively…

Statistical Finance · Quantitative Finance 2020-10-26 Jun-ichi Maskawa , Koji Kuroda

This paper advances interest rate modeling in the post-LIBOR era by introducing rough stochastic volatility into the Forward Market Model (FMM). We establish a rigorous asymptotic expansion of swaption implied volatility, connecting the FMM…

Mathematical Finance · Quantitative Finance 2025-10-01 Reo Adachi , Masaaki Fukasawa , Naoki Iida , Mitsumasa Ikeda , Yo Nakatsu , Ryota Tsurumi , Tomohisa Yamakami

In industrial applications it is quite common to use stochastic volatility models driven by semi-martingale Markov volatility processes. However, in order to fit exactly market volatilities, these models are usually extended by adding a…

Pricing of Securities · Quantitative Finance 2022-06-22 Enrico Dall'Acqua , Riccardo Longoni , Andrea Pallavicini

We introduce affine Volterra processes, defined as solutions of certain stochastic convolution equations with affine coefficients. Classical affine diffusions constitute a special case, but affine Volterra processes are neither…

Probability · Mathematics 2019-10-23 Eduardo Abi Jaber , Martin Larsson , Sergio Pulido

This paper is concerned with the estimation of the volatility process in a stochastic volatility model of the following form: $dX_t=a_tdt+\sigma_tdW_t$, where $X$ denotes the log-price and $\sigma$ is a c\`adl\`ag semi-martingale. In the…

Statistical Finance · Quantitative Finance 2015-03-13 A. Alvarez , F. Panloup , M. Pontier , N. Savy

Heteroskedasticity is a common feature of financial time series and is commonly addressed in the model building process through the use of ARCH and GARCH processes. More recently multivariate variants of these processes have been in the…

Methodology · Statistics 2015-12-18 Alexander Aue , Lajos Horvath , Daniel Pellatt

This paper is concerned with finite dimensional models for the entire term structure for energy futures. As soon as a finite dimensional set of possible yield curves is chosen, one likes to estimate the dynamic behaviour of the yield curve…

Mathematical Finance · Quantitative Finance 2023-08-07 Paul Krühner , Shijie Xu

We apply the concepts of utility based pricing and hedging of derivatives in stochastic volatility markets and introduce a new class of "reciprocal affine" models for which the indifference price and optimal hedge portfolio for pure…

Probability · Mathematics 2008-12-02 M. R. Grasselli , T. R. Hurd

A recently proposed stochastic hidden variable model for quantum mechanics has been claimed to involve "retrocausality" due to the appearance of equations of motion with future-time boundary conditions. We formulate an equivalent system of…

Quantum Physics · Physics 2025-12-05 William S. DeWitt , Benjamin H. Feintzeig

In this paper we provide a comprehensive analysis of a structural model for the dynamics of prices of assets traded in a market originally proposed in [1]. The model takes the form of an interacting generalization of the geometric Brownian…

Statistical Finance · Quantitative Finance 2018-06-06 Kartik Anand , Jonathan Khedair , Reimer Kuehn

Fractional processes have gained popularity in financial modeling due to the dependence structure of their increments and the roughness of their sample paths. The non-Markovianity of these processes gives, however, rise to conceptual and…

Mathematical Finance · Quantitative Finance 2018-02-07 Philipp Harms , David Stefanovits

We propose a novel approximate factor model tailored for analyzing time-dependent curve data. Our model decomposes such data into two distinct components: a low-dimensional predictable factor component and an unpredictable error term. These…

Econometrics · Economics 2025-02-26 Sven Otto , Nazarii Salish

We introduce a new model of financial market with stochastic volatility driven by an arbitrary H\"older continuous Gaussian Volterra process. The distinguishing feature of the model is the form of the volatility equation which ensures the…

Mathematical Finance · Quantitative Finance 2024-07-16 Giulia Di Nunno , Yuliya Mishura , Anton Yurchenko-Tytarenko

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 this paper, we relax the power parameter of instantaneous variance and develop a new stochastic volatility plus jumps model that generalize the Heston model and 3/2 model as special cases. This model has two distinctive features. First,…

Mathematical Finance · Quantitative Finance 2017-03-20 Wei Lin , Shenghong Li , Shane Chern

There are several approaches to modeling and forecasting time series as applied to prices of commodities and financial assets. One of the approaches is to model the price as a non-stationary time series process with heteroscedastic…

Statistical Finance · Quantitative Finance 2024-07-01 Andrei Renatovich Batyrov

In this paper, we introduce a linear stochastic volatility model driven by $\alpha$-stable processes, which admits a unique positive solution. To preserve positivity, we modify the classical forward Euler-Maruyama scheme and analyze its…

Probability · Mathematics 2025-02-04 Xiaotong Li , Wei Liu , Xuerong Mao , Hongjiong Tian , Yue Wu

In this paper we derive stochastic representations for the finite dimensional distributions of a multidimensional diffusion on a fixed time interval, conditioned on the terminal state. The conditioning can be with respect to a fixed point…

Probability · Mathematics 2014-07-29 Christian Bayer , John Schoenmakers

The use of spectral proper orthogonal decomposition (SPOD) to construct low-order models for broadband turbulent flows is explored. The choice of SPOD modes as basis vectors is motivated by their optimality and space-time coherence…

Fluid Dynamics · Physics 2021-09-22 Tianyi Chu , Oliver T. Schmidt