Working in a continuous time setting, we extend to the general case of dynamic risk measures continuous from above the characterization of time consistency in terms of ``cocycle condition'' of the minimal penalty function. We prove also the supermartingale property for general time consistent dynamic risk measures. Whe…
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48 results for “dynamic consistence”
Study dynamic risk measures and performance indices using distortion functions.
problem Investigate time consistency of dynamic risk measures and performance indices generated by distortion functions.
method Analyze dynamic coherent risk measures (DCRMs) and dynamic weighted value at risk measures, proving their equivalence. Establish properties of families of DCRMs generated by distortion functions and define corresponding dynamic coherent acceptability indices (DCAIs). Examine time consistency of DCRMs and DCAIs.
result DCRM generated by distortion functions are sub-martingale time consistent but not super-martingale time consistent and not weakly acceptance time consistent.
Framework for quantifying uncertainty in dynamic processes.
problem Quantifying uncertainty in dynamic stochastic processes.
method Define dynamic uncertainty sets and dynamic robust risk measures.
result Dynamic robust risk measures are time-consistent under specific uncertainty sets.
New framework for consistent submodular maximization with insertions and deletions.
problem Maintaining near-optimal solutions in a dynamic setting with insertions and deletions.
method Developed a general framework for fully dynamic submodular maximization, instantiated for cardinality and rank-k matroid constraints.
result First constant-factor approximations with sublinear consistency for both cardinality and rank-k matroid constraints.
In this work we give a comprehensive overview of the time consistency property of dynamic risk and performance measures, focusing on a the discrete time setup. The two key operational concepts used throughout are the notion of the LM-measure and the notion of the update rule that, we believe, are the key tools for stud…
A new framework reduces inconsistencies in chaotic surrogate modeling.
problem Consistency issues between probabilistic objectives and dynamical system dynamics.
method KAFFEE (Kalman-Aware Framework For Ergodic Emulation), a differentiable extended Kalman filter.
result KAFFEE mitigates the dynamic-probabilistic consistency gap, improving reconstruction and predictive scores.
Classifies shapes of yield curves in the Svensson family.
problem Classifying shapes of yield curves in the Svensson family.
method Complete classification of shapes using mathematical analysis.
result Certain complex shapes cannot appear after a deterministic time horizon.
New models capture dynamic derivatives pricing with efficient simulations.
problem Capturing dynamic features of derivatives' term structures.
method Machine learning techniques to store and efficiently simulate complex drift terms.
result First efficient dynamic term structure models.
We extend the common Poisson shock framework reviewed for example in Lindskog and McNeil (2003) to a formulation avoiding repeated defaults, thus obtaining a model that can account consistently for single name default dynamics, cluster default dynamics and default counting process. This approach allows one to introduce…
We study time consistent dynamic pricing mechanisms of European contingent claims under uncertainty by using G framework introduced by Peng ([24]). We consider a financial market consisting of a riskless asset and a risky stock with price process modelled by a geometric generalized G-Brownian motion, which features the…
The main goal of this paper is to investigate under which conditions cash-subadditive convex dynamic risk measures are time-consistent. Proceeding as in Detlefsen and Scandolo \cite{detlef-scandolo} and inspired by their result, we give a dual representation of dynamic cash-subadditive convex risk measures (that can al…
Study dynamic Pareto-optimal allocations in multi-period economies with time-consistent risk measures.
problem Optimal allocation in multi-period pure-exchange economies with stochastic endowments and time-consistent risk measures.
method Introduced dynamic Pareto-optimal allocation processes and derived recursive and comonotone improvement theorems.
result Dynamic Pareto-optimal allocation processes can be constructed recursively and are comonotone.
Develops RL for dynamic risk assessment in stochastic optimization.
problem Time-consistent risk assessment in stochastic optimization problems.
method Model-free reinforcement learning with dynamic convex risk measures, time-consistent dynamic programming, policy gradient updates, actor-critic neural network optimization.
result Demonstrates optimal policies for statistical arbitrage, financial hedging, and robot control.
We introduce, in continuous time, an axiomatic approach to assign to any financial position a dynamic ask (resp. bid) price process. Taking into account both transaction costs and liquidity risk this leads to the convexity (resp. concavity) of the ask (resp. bid) price. Time consistency is a crucial property for dynami…
Blend-ASC improves self-consistency efficiency by dynamically allocating samples, reducing costs.
problem Efficiently applying self-consistency to large datasets is computationally expensive.
method Blend-ASC dynamically allocates samples during inference, improving efficiency.
result Blend-ASC reduces sample usage by 6.8x on average compared to vanilla self-consistency.
The paper proposes a method to improve reinforcement learning by ensuring consistency between observed and imagined dynamics.
problem Compounding errors in traditional model-based reinforcement learning approaches.
method An auxiliary cost function to ensure consistency between observed and imagined dynamics.
result The proposed approach helps train powerful policies and better dynamics models.
We propose a new class of mappings, called Dynamic Limit Growth Indices, that are designed to measure the long-run performance of a financial portfolio in discrete time setup. We study various important properties for this new class of measures, and in particular, we provide necessary and sufficient condition for a Dyn…
Analyzes feature learning in neural networks using a self-consistent dynamical field theory.
problem Feature learning in infinite-width neural networks.
method Constructs deterministic dynamical order parameters as inner-product kernels for hidden unit activations and gradients.
result Reveals the hidden layer activation distribution, neural tangent kernel evolution, and output predictions.
The paper studies dynamic star-shaped risk measures and their representation.
problem Representing dynamic star-shaped risk measures and their properties.
method Representation theorems for dynamic monetary and star-shaped risk measures.
result Dynamic star-shaped risk measures can be represented as the lower envelope of a family of dynamic convex risk measures.
New method solves continuous time mean-variance model for consistent investment strategy.
problem Time-consistent optimal strategy for continuous time mean-variance model.
method Developed a new Bellman principle method.
result Obtained a time-consistent dynamic optimal strategy.
Investigates consistency of FX rate dynamics under inversion.
problem Consistency of jump-diffusion dynamics for FX rates under inversion.
method Calibrated Heston and SABR models, analyzed jumps in domestic and foreign measures.
result Determines conditions for consistency in FX rate dynamics under inversion.
Valuation Reveals Uncertaintyq-fin.MF
Paper recovers uncertainty from dynamic valuation rules.
problem Recovering latent uncertainty from observable valuation rules.
method Developed procedures to identify and characterize uncertainty structures from valuation rules.
result Valuation rules contain sufficient information to identify and recover uncertainty structures.
In this paper we propose the notion of dynamic deviation measure, as a dynamic time-consistent extension of the (static) notion of deviation measure. To achieve time-consistency we require that a dynamic deviation measures satisfies a generalised conditional variance formula. We show that, under a domination condition,…
The paper explores time consistency for scalar multivariate risk measures in markets with transaction costs.
problem Time consistency of scalar multivariate risk measures in markets with transaction costs.
method Presented dual representations and derived an equivalent recursive formulation for multivariate scalar risk measures.
result Developed a direct notion of a 'moving scalarization' for scalar time consistency.
Proposes a model for identifying edges in low-rank dynamical networks.
problem Inability of conventional methods to handle low-rank dynamical networks.
method Low rank dynamical network model with causal Wiener filtering.
result Consistent method for estimating all network edges.
Dynamic submodular maximization with consistency constraints.
problem Maximizing submodular functions in a streaming environment with limited changes.
method Algorithms with trade-offs between consistency and approximation quality.
result Effective algorithms for real-world applications.
The paper examines dynamic reserving for multiple currencies under coherent risk measures.
problem Dynamic reserving for risk in multiple currencies under a general coherent risk measure.
method Shows time-consistency of reserving portfolios in multiple currencies when a generalized m-stability condition holds, equivalent to dynamic trading across baskets of currencies with proportional transaction costs.
result A version of the Fundamental Theorem of Asset Pricing holds in this context, proving time-consistency of reserving portfolios.
Derives option pricing formulas consistent with rational asset pricing theory.
problem Existing behavioral finance option pricing formulas allow arbitrage opportunities.
method Introduces transaction costs to offset arbitrage opportunities.
result Derives formulas consistent with rational dynamic asset pricing theory.
In an incomplete financial market, the axiomatic of Time Consistent Pricing Procedure (TCPP), recently introduced, is used to assign to any financial asset a dynamic limit order book, taking into account both the dynamics of basic assets and the limit order books for options. Kreps-Yan fundamental theorem is extended t…
Finite-Sample Properties of Model Specification Tests for Multivariate Dynamic Regression Modelsecon.EM
Proposes a new test for validating multivariate dynamic regression models.
problem Inadequate exogeneity conditions for conventional model specification tests in dynamic systems.
method Develops a generalized Durbin estimator for multiple-equation systems with dynamic dependencies, and constructs Wald tests.
result Bootstrap-based Wald tests improve finite-sample size control and validate the null hypothesis in multifactor models.
Study on cryptocurrency market dynamics and correlations over time.
problem Understanding the dynamics and correlations of cryptocurrency market over time.
method Evolutionary correlation analysis, turning point algorithm, inverse relationship between market size and collective dynamics, time-varying consistency of relationships, examination of volatility structure.
result Increased uniformity in volatility during market crashes, termed 'volatility dispersion'.
The paper concerns primal and dual representations as well as time consistency of set-valued dynamic risk measures. Set-valued risk measures appear naturally when markets with transaction costs are considered and capital requirements can be made in a basket of currencies or assets. Time consistency of scalar risk measu…
New method learns diffusion bridges for rare events.
problem Simulating rare events in diffusion processes.
method Iterative online learning based on self-consistency.
result Strong performance in various empirical settings.
We consider dynamic sublinear expectations (i.e., time-consistent coherent risk measures) whose scenario sets consist of singular measures corresponding to a general form of volatility uncertainty. We derive a càdlàg nonlinear martingale which is also the value process of a superhedging problem. The superhedging strate…
This paper improves deep learning model consistency through ensemble methods.
problem Consistency and correct-consistency issues in deep learning models.
method Formal definition of consistency and correct-consistency, proving ensemble improvement, proposing dynamic snapshot ensemble method.
result Ensemble methods can improve correct-consistency of deep learning models.
We prove the Fundamental Theorem of Asset Pricing for a discrete time financial market where trading is subject to proportional transaction cost and the asset price dynamic is modeled by a family of probability measures, possibly non-dominated. Using a backward-forward scheme, we show that when the market consists of a…
Dynamic model assesses CCP risk with time-consistent risk measures.
problem Assessing central counterparty risk in dynamic markets.
method Markovian structure model of joint credit migrations; time-consistent dynamic risk measures.
result Proposes a method for more accurate initial margin and default fund allocation.
Constant price impact functions, much used in financial literature, are shown to give rise to paradoxical outcomes since they do not allow for proper predictability removal: for instance the exploitation of a single large trade whose size and time of execution are known in advance to some insider leaves the arbitrage o…
Generative adversarial network for probabilistic forecasting of random systems.
problem Forecasting random dynamical systems without distributional assumptions.
method Recurrent neural network and generative adversarial network (GAN) with regularization based on maximum mean discrepancy (MMD).
result The proposed model successfully forecasts complex stochastic processes with multiple-step predictions.
We study the dynamic indifference pricing with ambiguity preferences. For this, we introduce the dynamic expected utility with ambiguity via the nonlinear expectation--G-expectation, introduced by Peng (2007). We also study the risk aversion and certainty equivalent for the agents with ambiguity. We obtain the dynamic …
We define Conditional quasi concave Performance Measures (CPMs), on random variables bounded from below, to accommodate for additional information. Our notion encompasses a wide variety of cases, from conditional expected utility and certainty equivalent to conditional acceptability indexes. We provide the characteriza…
LUQ learns QoI from dynamical systems for consistent observation inversion.
problem Quantifying uncertainties on model inputs corresponding to observable QoI in dynamical systems.
method LUQ framework for SIPs, including data filtering, dynamics learning, observation classification, and feature extraction.
result LUQ provides tractable solutions to SIPs for dynamical systems, enabling uncertainty quantification.
Dynamic risk measures follow law invariance principles over time.
problem Tackles dynamic risk measurement principles.
method Shows equivalence between adapted law invariance and recursive one-step conditional-law representation for time-consistent risk measures.
result Identifies adapted law invariance as the dynamic counterpart of ordinary law invariance.
In this paper we provide a flexible framework allowing for a unified study of time consistency of risk measures and performance measures (also known as acceptability indices). The proposed framework not only integrates existing forms of time consistency, but also provides a comprehensive toolbox for analysis and synthe…
Paper proposes a method to identify optimal threshold for stock market networks.
problem Challenges in identifying the optimal threshold for reliable stock network construction.
method Dynamic consistence between threshold network and stock market, optimal threshold maximized by consistence function.
result Optimal threshold value of 0.28 for stocks in S&P 500 Index.
The paper addresses time inconsistency in mean-risk optimization.
problem Time inconsistency in mean-risk optimization.
method Use of a time consistent dynamic convex risk measure to evaluate portfolio risk.
result The dynamic mean-risk problem satisfies a set-valued Bellman's principle.
COLoKe adapts Koopman embeddings online, reducing overfitting and improving long-term predictions.
problem Online adaptation of Koopman embeddings to avoid overfitting and maintain long-term predictive accuracy.
method Combines deep feature learning with multistep prediction consistency in a lifted space, using a conformal-style mechanism for selective updates.
result Empirically effective in reducing overfitting and maintaining long-term predictive accuracy.
Paper analyzes learning dynamics in quasi-periodic environments, showing consistent solutions.
problem Challenges in stochastic gradient learning for complex environments.
method Uses energy balance equations derived from Caldirola-Kanai Hamiltonian to model learning.
result In quasi-periodic environments, learning yields consistent solutions for similar patterns.