arXiv research

We formalize and decompose reinforcement learning problems with exogenous state variables and rewards.

The paper tackles reinforcement learning with exogenous variables and rewards.

We study Exo-MDPs to reduce sample complexity in reinforcement learning.

SPECTRA improves probabilistic energy forecasting by separating trends and uncertainties.

HRHN predicts time series by integrating exogenous data and temporal dynamics.

HL algorithms improve resource allocation in cloud environments.

Deep state space model forecasts time series with uncertainty.

Improved electricity price forecasting with NBEATSx model.

Study liquidity provision with exogenous competition using a reference market maker.

We consider the problem of identifying the causal direction between two discrete random variables using observational data. Unlike previous work, we keep the most general functional model but make an assumption on the unobserved exogenous variable: Inspired by Occam's razor, we assume that the exogenous variable is sim…

Proposes a multi-variable LSTM for accurate time series forecasting and variable importance.

Paper develops a new RL method for MDPs with uncertainty, achieving better regret bounds.

We address microscopic, agent based, and macroscopic, stochastic, modeling of the financial markets combining it with the exogenous noise. The interplay between the endogenous dynamics of agents and the exogenous noise is the primary mechanism responsible for the observed long-range dependence and statistical propertie…

We introduce a new measure of activity of financial markets that provides a direct access to their level of endogeneity. This measure quantifies how much of price changes are due to endogenous feedback processes, as opposed to exogenous news. For this, we calibrate the self-excited conditional Poisson Hawkes model, whi…

We investigate the large-volatility dynamics in financial markets, based on the minute-to-minute and daily data of the Chinese Indices and German DAX. The dynamic relaxation both before and after large volatilities is characterized by a power law, and the exponents $p_\pm$ usually vary with the strength of the large vo…

Study classifies stock price jumps as exogenous or endogenous using news data.

New method learns exogenous variable distributions for better causal optimization.

This paper uses NARX neural networks for macroeconomic forecasting and goal setting.

Paper proves causal direction can be inferred from data with limited randomness.

Using the mechanics of creep in material sciences as a metaphor, we present a general framework to understand the evolution of financial, economic and social systems and to construct scenarios for the future. In a nutshell, highly non-linear out-of-equilibrium systems subjected to exogenous perturbations tend to exhibi…

Method identifies unknown intervention targets in structural causal models from diverse data.

The Nonlinear autoregressive exogenous (NARX) model, which predicts the current value of a time series based upon its previous values as well as the current and past values of multiple driving (exogenous) series, has been studied for decades. Despite the fact that various NARX models have been developed, few of them ca…

New approach uses 'forward-looking' counterfactuals for treatment choice.

The paper analyzes binary option markets with exogenous information and price sensitivity.

In this paper, we propose an interpretable LSTM recurrent neural network, i.e., multi-variable LSTM for time series with exogenous variables. Currently, widely used attention mechanism in recurrent neural networks mostly focuses on the temporal aspect of data and falls short of characterizing variable importance. To th…

A model is presented in this work for simulating endogenously the evolution of the marginal costs of production of energy carriers from non-renewable resources, their consumption, depletion pathways and timescales. Such marginal costs can be used to simulate the long term average price formation of energy commodities. …

Enhances random forest performance with exogenous randomness.

Systems with long-range persistence and memory are shown to exhibit different precursory as well as recovery patterns in response to shocks of exogeneous versus endogeneous origins. By endogeneous, we envision either fluctuations resulting from an underlying chaotic dynamics or from a stochastic forcing origin which ma…

Method estimates exogenous and endogenous factors from event times.

This work tackles fitting Hawkes processes to interval-censored data.

Minimax PAC bounds for learning in exogenous contextual MDPs

Many statistical methods have been proposed to estimate causal models in classical situations with fewer variables than observations (p<n, p: the number of variables and n: the number of observations). However, modern datasets including gene expression data need high-dimensional causal modeling in challenging situation…

Paper simplifies complex causal identifiability problems with exogenous isomorphism.

Paper introduces a novel traffic forecasting model using autoencoders and exogenous variables.

We reverse engineer dynamics of financial contagion to find the scenario of smallest exogenous shock that, should it occur, would lead to a given final systemic loss. This reverse stress test can be used to identify the potential triggers of systemic events, and it removes the arbitrariness in the selection of shock sc…

This study defines a multivariate Self--Exciting Threshold Autoregressive with eXogenous input (MSETARX) models and present an estimation procedure for the parameters. The conditions for stationarity of the nonlinear MSETARX models is provided. In particular, the efficiency of an adaptive parameter estimation algorithm…

The study uses Random Matrix Theory to identify structural changes in stock markets during shocks.

Proposes a new test for validating multivariate dynamic regression models.

Incomplete financial markets are considered, defined by a multi-dimensional non-homogeneous diffusion process, being the direct sum of an Itô process (the price process), and another non-homogeneous diffusion process (the exogenous process, representing exogenous stochastic sources). The drift and the diffusion matrix …

Develops a framework for valuing Asian options with market impact.

Proposes Exogenous Matching for efficient counterfactual estimation.

EXOC framework uses auxiliary variables for counterfactual fairness in machine learning.

Paper proposes a new model to assess risks in energy storage systems considering both exogenous and endogenous uncertainties.

Paper harmonizes medical data using flow-based causal inference.

Policy analysts wish to visualize a range of policies for large simulator-defined Markov Decision Processes (MDPs). One visualization approach is to invoke the simulator to generate on-policy trajectories and then visualize those trajectories. When the simulator is expensive, this is not practical, and some method is r…

The study examines pricing American options with both exogenous and endogenous transaction costs.

A method for identifying NPWARX models with arbitrary domains using probabilistic mixture models.

Researchers use Meyer-σ-fields to model information flow in irreversible investment problems.