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We present a neural network (NN) approach to fit and predict implied volatility surfaces (IVSs). Atypically to standard NN applications, financial industry practitioners use such models equally to replicate market prices and to value other…

Pricing of Securities · Quantitative Finance 2020-10-27 Damien Ackerer , Natasa Tagasovska , Thibault Vatter

The usage of a spot volatility estimate based on a volatility decomposition in a time-changed price-model according to the trading times is investigated. In this model clock-time volatility splits up into the product of tick-time volatility…

Probability · Mathematics 2016-05-10 Rainer Dahlhaus , Sophon Tunyavetchakit

This paper develops an asymptotic distribution theory for an endogenous instrumentation approach in quantile predictive regressions when both generated covariates and persistent predictors are used. The generated covariates are obtained…

Econometrics · Economics 2024-04-23 Christis Katsouris

Varimax factor rotations, while popular among practitioners in psychology and statistics since being introduced by H. Kaiser, have historically been viewed with skepticism and suspicion by some theoreticians and mathematical statisticians.…

Statistics Theory · Mathematics 2024-03-11 Joshua Cape

We introduce a multivariate diffusion model that is able to price derivative securities featuring multiple underlying assets. Each asset volatility smile is modeled according to a density-mixture dynamical model while the same property…

Pricing of Securities · Quantitative Finance 2014-09-24 Damiano Brigo , Francesco Rapisarda , Abir Sridi

Exact relationships between the short time-to-maturity ATM implied volatility slope, the (dual) volatility swap, and the (dual) zero vanna implied volatility are given.

Pricing of Securities · Quantitative Finance 2022-02-16 Frido Rolloos

One the one hand, rough volatility has been shown to provide a consistent framework to capture the properties of stock price dynamics both under the historical measure and for pricing purposes. On the other hand, market price of volatility…

Mathematical Finance · Quantitative Finance 2025-12-05 Ofelia Bonesini , Antoine Jacquier , Aitor Muguruza

We propose a non-parametric extension with leverage functions to the Andersen commodity curve model. We calibrate this model to market data for WTI and NG including option skew at the standard maturities. While the model can be calibrated…

Mathematical Finance · Quantitative Finance 2022-12-16 Orcan Ogetbil , Bernhard Hientzsch

In a market with stochastic volatility and jumps, we consider a VIX-linked fee structure for variable annuity contracts with guaranteed minimum withdrawal benefits (GMWB). Our goal is to assess the effectiveness of the VIX-linked fee…

Risk Management · Quantitative Finance 2018-04-13 Michael A. Kouritzin , Anne MacKay

This paper develops a flexible and computationally efficient multivariate volatility model, which allows for dynamic conditional correlations and volatility spillover effects among financial assets. The new model has desirable properties…

Methodology · Statistics 2025-07-25 Wenyu Li , Yuchang Lin , Qianqian Zhu , Guodong Li

In this paper, we introduce a new time series model having a stochastic exponential tail. This model is constructed based on the Normal Tempered Stable distribution with a time-varying parameter. The model captures the stochastic…

Computational Finance · Quantitative Finance 2023-03-23 Young Shin Kim , Kum-Hwan Roh , Raphael Douady

The Stochastic Volatility (SV) model and its variants are widely used in the financial sector while recurrent neural network (RNN) models are successfully used in many large-scale industrial applications of Deep Learning. Our article…

Econometrics · Economics 2022-01-25 Trong-Nghia Nguyen , Minh-Ngoc Tran , David Gunawan , R. Kohn

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 this paper, we are concerned with nonparametric inference on the volatility of volatility process in stochastic volatility models. We construct several estimators for its integrated version in a high-frequency setting, all based on…

Statistics Theory · Mathematics 2015-09-30 Mathias Vetter

Stochastic volatility modelling of financial processes has become increasingly popular. The proposed models usually contain a stationary volatility process. We will motivate and review several nonparametric methods for estimation of the…

Methodology · Statistics 2014-07-15 Bert van Es , Peter Spreij , Harry van Zanten

In the Black-Scholes context we consider the probability distribution function (PDF) of financial returns implied by volatility smile and we study the relation between the decay of its tails and the fitting parameters of the smile. We show…

Pricing of Securities · Quantitative Finance 2010-10-12 L. Spadafora , G. P. Berman , F. Borgonovi

The discrepancy between realized volatility and the market's view of volatility has been known to predict individual equity options at the monthly horizon. It is not clear how this predictability depends on a forecast's ability to predict…

Statistical Finance · Quantitative Finance 2025-06-10 Austin Pollok

A major drawback of the Standard Heston model is that its implied volatility surface does not produce a steep enough smile when looking at short maturities. For that reason, we introduce the Stationary Heston model where we replace the…

Mathematical Finance · Quantitative Finance 2020-07-13 Vincent Lemaire , Thibaut Montes , Gilles Pagès

The implied volatility is a crucial element of any financial toolbox, since it is used for quoting and the hedging of options as well as for model calibration. In contrast to the Black-Scholes formula its inverse, the implied volatility, is…

Computational Finance · Quantitative Finance 2017-10-06 Kathrin Glau , Paul Herold , Dilip B. Madan , Christian Pötz

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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