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We derive upper and lower bounds on the expectation of $f(\mathbf{S})$ under dependence uncertainty, i.e. when the marginal distributions of the random vector $\mathbf{S}=(S_1,\dots,S_d)$ are known but their dependence structure is…

Probability · Mathematics 2017-06-19 Thibaut Lux , Antonis Papapantoleon

We show how inter-asset dependence information derived from market prices of options can lead to improved model-free price bounds for multi-asset derivatives. Depending on the type of the traded option, we either extract correlation…

Mathematical Finance · Quantitative Finance 2023-09-26 Jonathan Ansari , Eva Lütkebohmert , Ariel Neufeld , Julian Sester

We consider the computation of model-free bounds for multi-asset options in a setting that combines dependence uncertainty with additional information on the dependence structure. More specifically, we consider the setting where the…

Pricing of Securities · Quantitative Finance 2024-04-04 Evangelia Dragazi , Shuaiqiang Liu , Antonis Papapantoleon

We propose the extension of Fr\'{e}chet-Hoeffding copula bounds for circular data. The copula is a powerful tool for describing the dependency of random variables. In two dimensions, the Fr\'{e}chet-Hoeffding upper (lower) bound indicates…

Statistics Theory · Mathematics 2023-11-17 Hiroaki Ogata

We consider derivatives written on multiple underlyings in a one-period financial market, and we are interested in the computation of model-free upper and lower bounds for their arbitrage-free prices. We work in a completely realistic…

Optimization and Control · Mathematics 2022-01-13 Ariel Neufeld , Antonis Papapantoleon , Qikun Xiang

In this study, we propose a new formula for spread option pricing with the dependence of two assets described by a copula function. The advantage of the proposed method is that it requires only the numerical evaluation of a one-dimensional…

Pricing of Securities · Quantitative Finance 2023-08-31 Edoardo Berton , Lorenzo Mercuri

We derive bounds on the distribution function, therefore also on the Value-at-Risk, of $\varphi(\mathbf X)$ where $\varphi$ is an aggregation function and $\mathbf X = (X_1,\dots,X_d)$ is a random vector with known marginal distributions…

Risk Management · Quantitative Finance 2018-11-20 Thibaut Lux , Antonis Papapantoleon

Using neural networks, we compute bounds on the prices of multi-asset derivatives given information on prices of related payoffs. As a main example, we focus on European basket options and include information on the prices of other similar…

Computational Finance · Quantitative Finance 2020-11-03 Luca De Gennaro Aquino , Carole Bernard

A new class of copulas based on order statistics was introduced by Baker (2008). Here, further properties of the bivariate and multivariate copulas are described, such as that of likelihood ratio dominance (LRD), and further bivariate…

Methodology · Statistics 2014-12-03 Rose Baker

We introduce new estimates and tests of independence in copula models with unknown margins using $\phi$-divergences and the duality technique. The asymptotic laws of the estimates and the test statistics are established both when the…

Statistics Theory · Mathematics 2019-03-06 Salim Bouzebda , Amor Keziou

Finding upper and lower bounds to integrals with respect to copulas is a quite prominent problem in applied probability. In their 2014 paper, Hofer and Iaco showed how particular two dimensional copulas are related to optimal solutions of…

Optimization and Control · Mathematics 2016-07-01 Michael Preischl

The quanto option is a cross-currency derivative in which the pay-off is given in foreign currency and then converted to domestic currency, through a constant exchange rate, used for the conversion and determined at contract inception.…

Mathematical Finance · Quantitative Finance 2021-03-02 Rafael Felipe Carmargo Prudencio , Christian D. Jäkel

We introduce novel information-theoretic measures termed the multivariate cumulative copula fractional inaccuracy measure and the multivariate survival copula fractional inaccuracy measure, constructed respectively from multivariate copulas…

Statistics Theory · Mathematics 2025-06-25 Aman Pandey , Chanchal Kundu

Gaussian copulas are widely used in the industry to correlate two random variables when there is no prior knowledge about the co-dependence between them. The perturbed Gaussian copula approach allows introducing the skew information of both…

Pricing of Securities · Quantitative Finance 2012-02-10 Alberto Elices , Jean-Pierre Fouque

Being the limits of copulas of componentwise maxima in independent random samples, extreme-value copulas can be considered to provide appropriate models for the dependence structure between rare events. Extreme-value copulas not only arise…

Statistics Theory · Mathematics 2009-12-07 Gordon Gudendorf , Johan Segers

In this paper an analytic expression is given for the bounds of the distribution function of the sum of dependent normally distributed random variables. Using the theory of copulas and the important Frechet bounds the dependence structure…

Probability · Mathematics 2011-07-26 Walter Schneider

The Multiplicative Error Model (Engle (2002)) for nonnegative valued processes is specified as the product of a (conditionally autoregressive) scale factor and an innovation process with nonnegative support. A multivariate extension allows…

Statistical Finance · Quantitative Finance 2016-04-06 Fabrizio Cipollini , Robert F. Engle , Giampiero M. Gallo

In this paper, we construct a bound copula, which can reach both Frechet's lower and upper bounds for perfect positive and negative dependence cases. Since it covers a wide range of dependency and simple for computational purposes, it can…

Probability · Mathematics 2021-02-01 Suman Thapa , Yiqiang Q. Zhao

This paper examines a semi-analytical approach for pricing American options in time-inhomogeneous models characterized by negative interest rates (for equity/FX) or negative convenience yields (for commodities/cryptocurrencies). Under such…

Pricing of Securities · Quantitative Finance 2025-07-22 Andrey Itkin , Yerkin Kitapbayev

Conditional copulas are flexible statistical tools that couple joint conditional and marginal conditional distributions. In a linear regression setting with more than one covariate and two dependent outcomes, we propose the use of additive…

Methodology · Statistics 2014-07-31 Avideh Sabeti , Mian Wei , Radu V. Craiu
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