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Given a bivariate random pair $(X,Y)$, a natural problem is to estimate, from a single sample $(X_i,Y_i)_{1\le i\le n}$, quantities such as $\mathbb{E}\left[ \mathbb{E}[ Y\mid X ]^2 \right]$. More broadly, sensitivity indices are designed…

Statistics Theory · Mathematics 2026-03-25 Reda Chhaibi , Fabrice Gamboa , Clément Pellegrini

Albeit of crucial interest for both financial practitioners and researchers, market-implied volatility data of European swaptions often exhibit large portions of missing quotes due to illiquidity of the various underlying swaption…

Machine Learning · Computer Science 2022-04-25 Ivo Richert , Robert Buch

A statistical decision problem is hidden in the core of option pricing. A simple form for the price C of a European call option is obtained via the minimum Bayes risk, R_B, of a 2-parameter estimation problem, thus justifying calling C…

Pricing of Securities · Quantitative Finance 2013-04-19 Yannis G. Yatracos

We formulate a discrete-time Bayesian stochastic volatility model for high-frequency stock-market data that directly accounts for microstructure noise, and outline a Markov chain Monte Carlo algorithm for parameter estimation. The methods…

Applications · Statistics 2016-02-02 Georgi Dinolov , Abel Rodriguez , Hongyun Wang

No-arbitrage asset pricing characterizes valuation through the existence of equivalent martingale measures relative to a filtration and a class of admissible trading strategies. In practice, pricing is performed across multiple asset…

Mathematical Finance · Quantitative Finance 2026-01-21 Alejandro Rodriguez Dominguez

We study the formation of derivative prices in equilibrium between risk-neutral agents with heterogeneous beliefs about the dynamics of the underlying. Under the condition that the derivative cannot be shorted, we prove the existence of a…

Mathematical Finance · Quantitative Finance 2018-01-04 Johannes Muhle-Karbe , Marcel Nutz

No--arbitrage property provides a simple method for pricing financial derivatives. However, arbitrage opportunities exist among different markets in various fields, even for a very short time. By knowing that an arbitrage property exists,…

Computational Finance · Quantitative Finance 2022-05-24 Yasushi Ota , Yu Jiang , Daiki Maki

The stochastic-alpha-beta-rho (SABR) model has been widely adopted in options trading. In particular, the normal ($\beta=0$) SABR model is a popular model choice for interest rates because it allows negative asset values. The option price…

Pricing of Securities · Quantitative Finance 2023-01-10 Jaehyuk Choi , Byoung Ki Seo

Recent literature seek to forecast implied volatility derived from equity, index, foreign exchange, and interest rate options using latent factor and parametric frameworks. Motivated by increased public attention borne out of the…

Statistical Finance · Quantitative Finance 2020-09-22 Fearghal Kearney , Han Lin Shang , Lisa Sheenan

In the past decade, Bitcoin as an emerging asset class has gained widespread public attention because of their extraordinary returns in phases of extreme price growth and their unpredictable massive crashes. We apply the log-periodic power…

Statistical Finance · Quantitative Finance 2020-04-22 Min Shu , Wei Zhu

This paper discusses a novel explanation for asymmetric volatility based on the anchoring behavioral pattern. Anchoring as a heuristic bias causes investors focusing on recent price changes and price levels, which two lead to a belief in…

Pricing of Securities · Quantitative Finance 2016-06-14 Mihaly Ormos , Dusan Timotity

Multiscale stochastic volatility models have been developed as an efficient way to capture the principle effects on derivative pricing and portfolio optimization of randomly varying volatility. The recent book Fouque, Papanicolaou, Sircar…

Computational Finance · Quantitative Finance 2015-09-17 Jean-Pierre Fouque , Matthew Lorig , Ronnie Sircar

Model uncertainty is a type of inevitable financial risk. Mistakes on the choice of pricing model may cause great financial losses. In this paper we investigate financial markets with mean-volatility uncertainty. Models for stock markets…

Pricing of Securities · Quantitative Finance 2014-07-31 Yuhong Xu

Based on criteria of mathematical simplicity and consistency with empirical market data, a stochastic volatility model is constructed, the volatility process being driven by fractional noise. Price return statistics and asymptotic behavior…

Probability · Mathematics 2008-12-02 Rui Vilela Mendes , M. J. Oliveira

We propose a versatile Monte-Carlo method for pricing and hedging options when the market is incomplete, for an arbitrary risk criterion (chosen here to be the expected shortfall), for a large class of stochastic processes, and in the…

Condensed Matter · Physics 2007-05-23 Benoît Pochart , Jean-Philippe Bouchaud

We propose a new method for finding statistical arbitrages that can contain more assets than just the traditional pair. We formulate the problem as seeking a portfolio with the highest volatility, subject to its price remaining in a band…

Econometrics · Economics 2024-02-14 Kasper Johansson , Thomas Schmelzer , Stephen Boyd

In this paper, we present a method of estimating the volatility of a signal that displays stochastic noise (such as a risky asset traded on an open market) utilizing Linear Predictive Coding. The main purpose is to associate volatility with…

Information Theory · Computer Science 2007-07-13 Louis Mello

We endorse the idea, suggested in recent literature, that BitCoin prices are influenced by sentiment and confidence about the underlying technology; as a consequence, an excitement about the BitCoin system may propagate to BitCoin prices…

Mathematical Finance · Quantitative Finance 2019-09-23 Alessandra Cretarola , Gianna Figà-Talamanca

Calibration to a surface of option prices requires specifying a suitably flexible martingale model for the discounted asset price under a risk-neutral measure. Assuming Brownian noise and mean-square integrability, we construct an…

Mathematical Finance · Quantitative Finance 2026-02-19 Pere Diaz-Lozano , Thomas K. Kloster

Testing procedures for predictive regressions with lagged autoregressive variables imply a suboptimal inference in presence of small violations of ideal assumptions. We propose a novel testing framework resistant to such violations, which…

Statistical Finance · Quantitative Finance 2016-12-16 Lorenzo Camponovo , Olivier Scaillet , Fabio Trojani