arXiv research

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

New method learns exogenous variable distributions for better causal optimization.

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

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

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

The paper tackles reinforcement learning with exogenous variables and rewards.

HL algorithms improve resource allocation in cloud environments.

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

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…

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

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…

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…

Enhances random forest performance with exogenous randomness.

Method estimates exogenous and endogenous factors from event times.

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

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

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…

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

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

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

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

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…

Improved electricity price forecasting with NBEATSx model.

Partially performative prediction studies how predictive models influence future data.

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

A phenomenological investigation of the endogenous and exogenous dynamics in the fluctuations of capital fluxes is investigated on the Chinese stock market using mean-variance analysis, fluctuation analysis and their generalizations to higher orders. Non-universal dynamics have been found not only in $α$ exponents diff…

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

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

SPECTRA improves probabilistic energy forecasting by separating trends and uncertainties.

Paper simplifies complex causal identifiability problems with exogenous isomorphism.

The paper evaluates income credibility using a hierarchical correlation reconstruction technique.

Algorithm learns fair ranking from biased data.

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…

We investigate the trading behavior of a large set of single investors trading the highly liquid Nokia stock over the period 2003-2008 with the aim of determining the relative role of endogenous and exogenous factors that may affect their behavior. As endogenous factors we consider returns and volatility, whereas the e…

Directed networks are pervasive both in nature and engineered systems, often underlying the complex behavior observed in biological systems, microblogs and social interactions over the web, as well as global financial markets. Since their structures are often unobservable, in order to facilitate network analytics, one …

New method for robust policy evaluation in offline reinforcement learning with sequentially exogenous unobserved confounders.

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…

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 …

Effective risk control must make a tradeoff between the microprudential risk of exogenous shocks to individual institutions and the macroprudential risks caused by their systemic interactions. We investigate a simple dynamical model for understanding this tradeoff, consisting of a bank with a leverage target and an unl…

Proposes Exogenous Matching for efficient counterfactual estimation.

Forecasting stock market decline and recovery post-COVID-19.

Paper harmonizes medical data using flow-based causal inference.

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…

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…

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

Study reveals 2020 stock crashes were mostly endogenous, not exogenous.

Deep state space model forecasts time series with uncertainty.