A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.
This paper develops copula-based models for forecasting multivariate realized volatility.
The study evaluates financial risk using copulas and statistical tests.
Characterizes symmetric Bernoulli distributions with minimal convex sums.
We review the main "omnibus procedures" for goodness-of-fit testing for copulas: tests based on the empirical copula process, on probability integral transformations, on Kendall's dependence function, etc, and some corresponding reductions of dimension techniques. The problems of finding asymptotic distribution-free te…
Estimates copula density for complex data distributions.
All too often measuring statistical dependencies between financial time series is reduced to a linear correlation coefficient. However this may not capture all facets of reality. We study empirical dependencies of daily stock returns by their pairwise copulas. Here we investigate particularly to which extent the non-st…
Paper proposes copula-based models for analyzing multivariate zero-inflated continuous data.
GCMM improves clustering and fits un-synchronized data.
Paper introduces a new test for conditional independence using weighted partial copulas.
Researchers solved a problem about extreme mass distributions in quasi-copulas.
CoCAI uses copulas for accurate multivariate time-series forecasting and anomaly detection.
This paper develops statistical models for cryptocurrency returns using hidden Markov regression and copulas.
Time series models generalize ARMA and ARFIMA with non-Gaussian dependence.
We discuss the connection between information and copula theories by showing that a copula can be employed to decompose the information content of a multivariate distribution into marginal and dependence components, with the latter quantified by the mutual information. We define the information excess as a measure of d…
Bayesian approach models nonignorable missing data using copulas and marginal quantiles.
When choosing the right copula for our data a key point is to distinguish the family that describes it at the best. In this respect, a better choice of the copulas could be obtained through the information about the (non)symmetry of the data. Exchangeability as a probability concept (first next to independence) has bee…
Copula Discrepancy benchmarks sample dependence structure against known families.
We analyze the statistical dependency structure of the S&P 500 constituents in the 4-year period from 2007 to 2010 using intraday data from the New York Stock Exchange's TAQ database. With a copula-based approach, we find that the statistical dependencies are very strong in the tails of the marginal distributions. This…
Constructs bivariate quantiles using vine copulas for multivariate analysis.
We proposed a new statistical dependency measure called Copula Dependency Coefficient(CDC) for two sets of variables based on copula. It is robust to outliers, easy to implement, powerful and appropriate to high-dimensional variables. These properties are important in many applications. Experimental results show that C…
This paper introduces a nonparametric copula-based index for detecting the strength and monotonicity structure of linear and nonlinear statistical dependence between pairs of random variables or stochastic signals. Our index, termed Copula Index for Detecting Dependence and Monotonicity (CIM), satisfies several desirab…
We study the adaptive estimation of copula correlation matrix for the semi-parametric elliptical copula model. In this context, the correlations are connected to Kendall's tau through a sine function transformation. Hence, a natural estimate for is the plug-in estimator with Kendall's tau statistic. We …
Bayesian model selection of vine copulas: a loss-based perspective
Heterogeneity of economic agents is emphasized in a new trend of macroeconomics. Accordingly the new emerging discipline requires one to replace the production function, one of key ideas in the conventional economics, by an alternative which can take an explicit account of distribution of firms' production activities. …
This paper proposes a new method to improve VI approximations by capturing dependence between blocks using vector copulas.
A new test method improves goodness-of-fit tests for copulas.
The paper presents a new copula based method for measuring dependence between random variables. Our approach extends the Maximum Mean Discrepancy to the copula of the joint distribution. We prove that this approach has several advantageous properties. Similarly to Shannon mutual information, the proposed dependence mea…
Proposes a copula-driven framework for multimodal learning.
IGNIS uses neural networks to estimate copula parameters robustly.
Study examines impact of oil and gold prices on Tehran Stock Exchange.
Improved forecasting of financial risk using Diffusion-Copula framework.
Causal discovery is a fundamental problem in statistics and has wide applications in different fields. Transfer Entropy (TE) is a important notion defined for measuring causality, which is essentially conditional Mutual Information (MI). Copula Entropy (CE) is a theory on measurement of statistical independence and is …
We introduce a new method for estimating the parameter of the bivariate Clayton copulas within the framework of Algorithmic Inference. The method consists of a variant of the standard boot-strapping procedure for inferring random parameters, which we expressly devise to bypass the two pitfalls of this specific instance…
Paper compares econometric models with machine learning for energy forecasting.
The paper proposes a method to identify power system oscillation modes using blind source separation.
Method detects effects of synthesis parameters on plutonium oxide microstructure.
New tests for conditional copulas based on decision trees.
Proposes a novel path generation and evaluation method for video games.
SYNC generates synthetic data from aggregated sources using Gaussian copulas.
Copula models have become popular in different applications, including modeling shocks, in view of their ability to describe better the dependence concepts in stochastic systems. The class of maxmin copulas was recently introduced by Omladič and Ružić. It extends the well known classes of Marshall-Olkin and Marshall co…
New RBM model outperforms copula models in credit risk management.
Levy copulas are the most general concept to capture jump dependence in multivariate Levy processes. They translate the intuition and many features of the copula concept into a time series setting. A challenge faced by both, distributional and Levy copulas, is to find flexible but still applicable models for higher dim…
A new copula, the checkerboard copula, maximizes entropy and preserves dependence.
This paper proposes a new class of copulas which characterize the set of all twice continuously differentiable copulas. We show that our proposed new class of copulas is a new generalized copula family that include not only asymmetric copulas but also all smooth copula families available in the current literature. Spea…
We derive bounds on the distribution function, therefore also on the Value-at-Risk, of where is an aggregation function and is a random vector with known marginal distributions and partially known dependence structure. More specifically, we analyze three type…
A new boosting model handles dependent censoring in time-to-event data.
Variational Bayes (VB), also known as independent mean-field approximation, has become a popular method for Bayesian network inference in recent years. Its application is vast, e.g. in neural network, compressed sensing, clustering, etc. to name just a few. In this paper, the independence constraint in VB will be relax…
We provide a set of copulas that can be interpreted as having the negative extreme dependence. This set of copulas is interesting because it coincides with countermonotonic copula for a bivariate case, and more importantly, is shown to be minimal in concordance ordering in the sense that no copula exists which is stric…