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.
Paper proposes a new method to evaluate joint risk under uncertainty.
Study approximates multivariate risk measures for Gaussian risks.
Simplifies study of multivariate shortfall risk measures.
New multivariate risk measures improve on univariate OCE methods.
Paper proposes a new model for multivariate risk measures using Wasserstein barycenters.
The equivalence between multiportfolio time consistency of a dynamic multivariate risk measure and a supermartingale property is proven. Furthermore, the dual variables under which this set-valued supermartingale is a martingale are characterized as the worst-case dual variables in the dual representation of the risk m…
We consider families of strongly consistent multivariate conditional risk measures. We show that under strong consistency these families admit a decomposition into a conditional aggregation function and a univariate conditional risk measure as introduced Hoffmann et al. (2016). Further, in analogy to the univariate cas…
The paper explores time consistency for scalar multivariate risk measures in markets with transaction costs.
In this paper, we introduce two alternative extensions of the classical univariate Value-at-Risk (VaR) in a multivariate setting. The two proposed multivariate VaR are vector-valued measures with the same dimension as the underlying risk portfolio. The lower-orthant VaR is constructed from level sets of multivariate di…
Paper introduces a new risk measure for multivariate residual estimation.
A new risk measure framework captures multivariate risk in banking.
The paper introduces MRVaR and MRCov for elliptical and log-elliptical distributions.
This paper uses multivariate probability models to assess financial system risks.
In economics, insurance and finance, value at risk (VaR) is a widely used measure of the risk of loss on a specific portfolio of financial assets. For a given portfolio, time horizon, and probability , the VaR is defined as a threshold loss value, such that the probability that the loss on the portfolio ove…
New framework for calculating multivariate risk measures using Wishart process.
Researchers extend CCVaR to multivariate data using Archimedean copulas.
We describe a general framework for measuring risks, where the risk measure takes values in an abstract cone. It is shown that this approach naturally includes the classical risk measures and set-valued risk measures and yields a natural definition of vector-valued risk measures. Several main constructions of risk meas…
Risk measures for multivariate financial positions are studied in a utility-based framework. Under a certain incomplete preference relation, shortfall and divergence risk measures are defined as the optimal values of specific set minimization problems. The dual relationship between these two classes of multivariate ris…
Paper introduces contribution measures for systemic risk in crypto markets.
We consider the Fractionally Integrated Exponential Generalized Autoregressive Conditional Heteroskedasticity process, denoted by FIEGARCH(p,d,q), introduced by Bollerslev and Mikkelsen (1996). We present a simulated study regarding the estimation of the risk measure on FIEGARCH processes. We consider the distr…
This paper contains an overview of results for dynamic multivariate risk measures. We provide the main results of four different approaches. We will prove under which assumptions results within these approaches coincide, and how properties like primal and dual representation and time consistency in the different approa…
In [16], a new family of vector-valued risk measures called multivariate expectiles is introduced. In this paper, we focus on the asymptotic behavior of these measures in a multivariate regular variations context. For models with equivalent tails, we propose an estimator of these multivariate asymptotic expectiles, in …
The financial crisis showed the importance of measuring, allocating and regulating systemic risk. Recently, the systemic risk measures that can be decomposed into an aggregation function and a scalar measure of risk, received a lot of attention. In this framework, capital allocations are added after aggregation and can…
Sharp bounds found for various risk measures using generalized FGM copulas.
Extended univariate Range Value-at-Risk to multivariate settings.
The paper introduces a new class of multivariate mixtures for actuarial applications.
The ongoing concern about systemic risk since the outburst of the global financial crisis has highlighted the need for risk measures at the level of sets of interconnected financial components, such as portfolios, institutions or members of clearing houses. The two main issues in systemic risk measurement are the compu…
The paper calculates moments and conditional risks for skewed elliptical distributions.
Since risky positions in multivariate portfolios can be offset by various choices of capital requirements that depend on the exchange rules and related transaction costs, it is natural to assume that the risk measures of random vectors are set-valued. Furthermore, it is reasonable to include the exchange rules in the a…
A generalization of expectiles for d-dimensional multivariate distribution functions is introduced. The resulting geometric expectiles are unique solutions to a convex risk minimization problem and are given by d-dimensional vectors. They are well behaved under common data transformations and the corresponding sample v…
Set-valued risk measures on with for conical market models are defined, primal and dual representation results are given. The collection of initial endowments which allow to super-hedge a multivariate claim are shown to form the values of a set-valued sublinear (coherent) risk measure. Sc…
The paper optimizes portfolios using a new GARCH model with regime switching and tempered stable innovations.
A method for calculating multi-portfolio time consistent multivariate risk measures in discrete time is presented. Market models for assets with transaction costs or illiquidity and possible trading constraints are considered on a finite probability space. The set of capital requirements at each time and state is c…
The paper estimates CoVaR with various models for financial risk analysis.
Develops a multivariate aggregation property for unbiased risk premium estimation.
A new multivariate distribution possessing arbitrarily parametrized and positively dependent univariate Pareto margins is introduced. Unlike the probability law of Asimit et al. (2010) [Asimit, V., Furman, E. and Vernic, R. (2010) On a multivariate Pareto distribution. Insurance: Mathematics and Economics 46(2), 308-31…
Study proposes a new portfolio selection method using non-Gaussian models and Esscher transform.
Unified asymptotic treatment for VaR- and expectile-based systemic risk measures.
Generalizes underlap coefficient for multivariate group separation.
This paper uses VAE to generate extreme events from multivariate data.
Investigates diversification quotient based on VaR and ES for portfolio models.
Paper introduces risk measures for non-convex portfolios.
In the paper, we use and investigate copulas models to represent multivariate dependence in financial time series. We propose the algorithm of risk measure computation using copula models. Using the optimal mean- portfolio we compute portfolio's Profit and Loss series and corresponded risk measures curves. Value-…
Capturing the dependence structure of multivariate extreme events is a major concern in many fields involving the management of risks stemming from multiple sources, e.g. portfolio monitoring, insurance, environmental risk management and anomaly detection. One convenient (non-parametric) characterization of extremal de…
In this paper we consider a multivariate model-based approach to measure the dynamic evolution of tail risk interdependence among US banks, financial services and insurance sectors. To deeply investigate the risk contribution of insurers we consider separately life and non-life companies. To achieve this goal we apply …
A two-step nonparametric method estimates financial systemic risk.
Proposes a new portfolio optimization method considering reward, dispersion, and asymmetry.
The paper examines stochastic ordering of Gini indexes for multivariate elliptical risks.