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This paper shows a novel machine learning model for realized volatility (RV) prediction using a normalizing flow, an invertible neural network. Since RV is known to be skewed and have a fat tail, previous methods transform RV into values…

Computational Engineering, Finance, and Science · Computer Science 2023-10-24 Xin Du , Kai Moriyama , Kumiko Tanaka-Ishii

We develop closed-form expansions for the implied volatility of VIX options within the class of forward variance models. Our approach builds on weak-approximation techniques for VIX option prices and yields explicit implied volatility…

Computational Finance · Quantitative Finance 2026-05-26 Ying Liao , Ankush Agarwal , Florian Bourgey

Single index financial market models cannot account for the empirically observed complex interactions between shares in a market. We describe a multi-share financial market model and compare characteristics of the volatility, that is the…

Condensed Matter · Physics 2009-10-31 Adam Ponzi

The Heston stochastic volatility model is arguably, the most popular stochastic volatility model used to price and risk manage exotic derivatives. In spite of this, it is not necessarily easy to calibrate to the market and obtain stable…

Pricing of Securities · Quantitative Finance 2025-12-23 Jherek Healy

We investigate the historical volatility of the 100 most capitalized stocks traded in US equity markets. An empirical probability density function (pdf) of volatility is obtained and compared with the theoretical predictions of a lognormal…

Statistical Mechanics · Physics 2009-11-07 Salvatore Micciche` , Giovanni Bonanno , Fabrizio Lillo , Rosario N. Mantegna

It is a market practice to express market-implied volatilities in some parametric form. The most popular parametrizations are based on or inspired by an underlying stochastic model, like the Heston model (SVI method) or the SABR model (SABR…

Mathematical Finance · Quantitative Finance 2026-01-06 Nicola F. Zaugg , Leonardo Perotti , Lech A. Grzelak

Econophysics and econometrics agree that there is a correlation between volume and volatility in a time series. Using empirical data and their distributions, we further investigate this correlation and discover new ways that volatility and…

Statistical Finance · Quantitative Finance 2014-03-21 Zeyu Zheng , Zhi Qiao , Joel N. Tenenbaum , H. Eugene Stanley , Baowen Li

The growth of the exhange-traded fund (ETF) industry has given rise to the trading of options written on ETFs and their leveraged counterparts {(LETFs)}. We study the relationship between the ETF and LETF implied volatility surfaces when…

Computational Finance · Quantitative Finance 2015-04-16 Tim Leung , Matthew Lorig , Andrea Pascucci

Volatility is a key measure of risk in financial analysis. The high volatility of one financial asset today could affect the volatility of another asset tomorrow. These lagged effects among volatilities - which we call volatility spillovers…

Statistical Finance · Quantitative Finance 2017-08-08 Luca Barbaglia , Christophe Croux , Ines Wilms

We examine whether model-based spot volatility estimators extracted from traded options data enhance the predictive power of the Heterogeneous Autoregressive (HAR) model for realized volatility. Specifically, we infer spot volatility under…

Risk Management · Quantitative Finance 2026-04-13 Zheqi Fan , Meng Melody Wang , Yifan Ye

We study two complementary methodologies for calibrating implied volatility surfaces: analytical approximations and data-driven models based on rough path theory. On the analytical side, we revisit a second-order asymptotic expansion for…

Mathematical Finance · Quantitative Finance 2026-05-11 Elisa Alòs , Òscar Burés , Rafael de Santiago , Josep Vives

We calculate the realized volatility in the spin model of financial markets and examine the returns standardized by the realized volatility. We find that moments of the standardized returns agree with the theoretical values of standard…

Computational Finance · Quantitative Finance 2016-11-28 Tetsuya Takaishi

It is well known that the probability distribution of high-frequency financial returns is characterized by a leptokurtic, heavy-tailed shape. This behavior undermines the typical assumption of Gaussian log-returns behind the standard…

Statistical Finance · Quantitative Finance 2023-06-14 Federica De Domenico , Giacomo Livan , Guido Montagna , Oreste Nicrosini

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

In the first quarter of 2006 Chicago Board Options Exchange (CBOE) introduced, as one of the listed products, options on its implied volatility index (VIX). This created the challenge of developing a pricing framework that can…

Pricing of Securities · Quantitative Finance 2009-05-14 Claudio Albanese , Harry Lo , Aleksandar Mijatović

This paper introduces novel volatility diffusion models to account for the stylized facts of high-frequency financial data such as volatility clustering, intra-day U-shape, and leverage effect. For example, the daily integrated volatility…

Methodology · Statistics 2022-06-01 Donggyu Kim , Minseok Shin

In this chapter, we consider volatility swap, variance swap and VIX future pricing under different stochastic volatility models and jump diffusion models which are commonly used in financial market. We use convexity correction approximation…

Mathematical Finance · Quantitative Finance 2017-12-08 Anatoliy Swishchuk , Zijia Wang

The volatility characterizes the amplitude of price return fluctuations. It is a central magnitude in finance closely related to the risk of holding a certain asset. Despite its popularity on trading floors, the volatility is unobservable…

Physics and Society · Physics 2008-12-02 Zoltan Eisler , Josep Perello , Jaume Masoliver

This paper proposes an empirical test of financial contagion in European equity markets during the tumultuous period of 2008-2011. Our analysis shows that traditional GARCH and Gaussian stochastic-volatility models are unable to explain two…

Statistical Finance · Quantitative Finance 2012-03-28 Nicholas G. Polson , James G. Scott

We examine statistical pictures of violent conflicts over the last 2000 years, finding techniques for dealing with incompleteness and unreliability of historical data. We introduce a novel approach to apply extreme value theory to…

Applications · Statistics 2016-09-05 Pasquale Cirillo , Nassim Nicholas Taleb