Results 221 to 230 of about 78,871 (265)

Empirical‐Process Limit Theory and Filter Approximation Bounds for Score‐Driven Time Series Models

open access: yesJournal of Time Series Analysis, EarlyView.
ABSTRACT This article examines the filtering and approximation‐theoretic properties of score‐driven time series models. Under specific Lipschitz‐type and tail conditions, new results are derived, leading to maximal and deviation inequalities for the filtering approximation error using empirical process theory.
Enzo D'Innocenzo
wiley   +1 more source

Testing Distributional Granger Causality With Entropic Optimal Transport

open access: yesJournal of Time Series Analysis, EarlyView.
ABSTRACT We develop a novel nonparametric test for Granger causality in distribution based on entropic optimal transport. Unlike classical mean‐based approaches, the proposed method directly compares the full conditional distributions of a response variable with and without the history of a candidate predictor.
Tao Wang
wiley   +1 more source

Perpetual Futures Pricing

open access: yesMathematical Finance, EarlyView.
ABSTRACT Perpetual futures are contracts without expiration date in which the anchoring of the futures price to the spot price is ensured by periodic funding payments from long to short. We derive explicit expressions for the no‐arbitrage price of various perpetual contracts, including linear, inverse, and quantos futures in both discrete and ...
Damien Ackerer   +2 more
wiley   +1 more source

Optimal Portfolio Choice With Cross‐Impact Propagators

open access: yesMathematical Finance, EarlyView.
ABSTRACT We consider a class of optimal portfolio choice problems in continuous time where the agent's transactions create both transient cross‐impact driven by a matrix‐valued Volterra propagator, as well as temporary price impact. We formulate this problem as the maximization of a revenue‐risk functional, where the agent also exploits available ...
Eduardo Abi Jaber   +2 more
wiley   +1 more source

Deep Q-Managed: a new framework for multi-objective deep reinforcement learning. [PDF]

open access: yesFront Artif Intell
Menezes R   +3 more
europepmc   +1 more source

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