The paper tackles reinforcement learning with exogenous variables and rewards.
problem Exogenous state variables and rewards slow reinforcement learning by introducing uncontrolled variation.
method Formalizes exogenous state variables and rewards, decomposes MDP into exogenous and endogenous components, and introduces algorithms to discover these components.
result Optimal policies for the endogenous MDP are also optimal for the original MDP, but the endogenous MDP is easier to solve due to reduced variance.
Existence of incomplete Radner equilibrium with endogenous noise tracker.
problem Existence of incomplete Radner equilibrium in a model with endogenous noise tracker.
method Proved existence through a coupled system of ODEs, reduced to two coupled ODEs.
result Endogenous noise tracker leads to higher aggregate welfare for large stock supply.
Transformers can handle endogeneity in linear regression using IV methods.
problem Endogeneity in in-context linear regression models.
method Transformer architecture with gradient-based bi-level optimization and in-context pretraining.
result Transformers provide more robust predictions and estimates than 2SLS in endogenous scenarios.
Easy conditions found for simplifying complex systems.
problem Linearizing complex two-input systems.
method Endogenous dynamic feedback with a dimension of at most two.
result Necessary and sufficient conditions for linearizability.
New findings allow infinite mean intensity Hawkes processes to be stable.
problem Stability condition for Hawkes processes with infinite mean intensity.
method Analysis of Quadratic Hawkes processes with infinite mean intensity.
result Quadratic Hawkes processes are always stationary with infinite mean intensity when total endogeneity ratio exceeds unity.
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…
This paper models financial contagion with endogenously determined market liquidity.
problem Financial contagion and its impact on market liquidity during price drops.
method Developed a joint clearing system for interbank payments, asset prices, and market liquidity, with endogenous market capacity.
result Endogenous market liquidity significantly affects system risk during financial contagion.
Study classifies stock price jumps as exogenous or endogenous using news data.
problem Differentiating between exogenous and endogenous price jumps.
method Synchronized news data with order book data to analyze stock price movements.
result Exogenous jumps are abrupt and follow a decaying power-law, while endogenous jumps are progressively accelerating.
In this article we consider the volatility inference in the presence of both market microstructure noise and endogenous time. Estimators of the integrated volatility in such a setting are proposed, and their asymptotic properties are studied. Our proposed estimator is compared with the existing popular volatility estim…
New method tackles endogeneity in online learning with improved regret bounds.
problem Endogeneity in real data due to omitted variables, strategic behaviors, etc.
method O2SLS (Online Two-Stage Least Squares) for Instrumental Variable (IV) regression.
result O2SLS achieves identification and oracle regret bounds for stochastic online learning.
Test for linearizing 2-input systems with 2D feedback.
problem Linearizability of two-input systems by feedback.
method Algorithmic test for 2D endogenous feedback.
result Systematic derivation of flat outputs.
Paper corrects bias in online learning algorithms with endogenous data.
problem Dynamic selection problems in online learning algorithms with endogenous data.
method Instrumental-variable-based algorithm to correct bias, proving central limit theorem.
result Obtains true parameter values and low regret levels.
Finance is about how the continuous stream of news gets incorporated into prices. But not all news have the same impact. Can one distinguish the effects of the Sept. 11, 2001 attack or of the coup against Gorbachev on Aug., 19, 1991 from financial crashes such as Oct. 1987 as well as smaller volatility bursts? Using a …
A new boosting method corrects endogeneity bias in instrumental variable regression.
problem Endogeneity bias in instrumental variable regression.
method Causal Gradient Boosting (boostIV) that builds on gradient boosting algorithm.
result boostIV is consistent and performs well in finite samples compared to other methods.
Paper proposes a new model to assess risks in energy storage systems considering both exogenous and endogenous uncertainties.
problem Current risk assessment ignores the stochastic nature of energy storage availability.
method Data-driven unified model with exogenous and endogenous uncertainty description for four types of generic energy storage.
result Comparative results show more severe risks for endogenous uncertainty, suggesting new strategies for system operators.
In order to disentangle the internal dynamics from exogenous factors within the Autoregressive Conditional Duration (ACD) model, we present an effective measure of endogeneity. Inspired from the Hawkes model, this measure is defined as the average fraction of events that are triggered due to internal feedback mechanism…
We developed a novel statistical method to identify structural differences between networks characterized by structural equation models. We propose to reparameterize the model to separate the differential structures from common structures, and then design an algorithm with calibration and construction stages to identif…
This paper highlights the role of risk neutral investors in generating endogenous bubbles in derivatives markets. We find that a market for derivatives, which has all the features of a perfect market except completeness and has some risk neutral investors, can exhibit extreme price movements which represent a violation…
Study optimal reinsurance for insurers with a reinsurer's default risk.
problem Optimal reinsurance for insurers with a reinsurer's default risk.
method Analytical solution for two types of reinsurance contracts.
result Joint effect of reinsurer's default and background risk on reinsurance demand.
Business cycles tend to comove across countries. However, standard models that attribute comovement to propagation of exogenous shocks struggle to generate a level of comovement that is as high as in the data. In this paper, we consider models that produce business cycles endogenously, through some form of non-linear d…
Investor optimizes utility in a market with endogenous pricing.
problem Maximizing utility in an incomplete market with endogenous pricing.
method Characterized optimality via FBSDEs and BSPDEs using generalized subgradients.
result Existence and smoothness of solutions for optimal investment and FBSDEs.
We present a model that investigates the spontaneous emergence of randomness in equity market microstructure. The phase space analysis of our model exposes an endogenous source of fluctuation in price and volume. We formulate a control problem for maximizing price regularity and stability while minimizing entanglement …
Study detects endogenous bubbles in meme stocks using CI.
problem Detecting endogenous bubbles in meme stocks.
method Used Log-Periodic Power Law (LPPL) Confidence Indicator (CI).
result CI detected numerous bubbles in meme stocks but struggled with predicting exogenous rallies.
The CAPM's market returns are endogenously determined, affecting all assets' expected returns.
problem The standard CAPM's market return assumption is not endogenously consistent.
method Demonstrates the impact of endogenously determined market returns on asset returns and the range of feasible market returns.
result Expected returns are influenced by all assets' risks, and market returns are limited by asset distribution.
AC-State discovers minimal latent state for control.
problem Discover minimal latent state from sensory information.
method Multi-step inverse model with information bottleneck.
result Guaranteed discovery of control-endogenous latent states.
Study reveals 2020 stock crashes were mostly endogenous, not exogenous.
problem Identifying the cause of the 2020 global stock market crash.
method Applied log-periodic power law singularity (LPPLS) methodology to analyze stock market indexes.
result The 2020 stock market crashes were mostly endogenous, driven by systemic instability.
Exogenous state variables and rewards can slow down reinforcement learning by injecting uncontrolled variation into the reward signal. We formalize exogenous state variables and rewards and identify conditions under which an MDP with exogenous state can be decomposed into an exogenous Markov Reward Process involving on…
Paper develops a new estimator for panel data with endogenous treatments, improving causal inference.
problem Challenges in causal inference for static panel data with endogenous treatments and confounding variables.
method Develops Double Machine Learning (DML) estimator for static panel models with endogenous treatments (panel IV DML). Introduces weak-identification diagnostics.
result Panel IV DML estimator improves estimation accuracy and delivers more reliable inference under weak identification.
Survival strategies in a market with self-determined prices are closely tied to log-optimal investment.
problem Survival of wealth in a market with endogenous prices.
method Assume only one's actions affect prices, use log-optimal strategy, disregard actual prices.
result Survival strategies are asymptotically close to log-optimal strategies.
Event occurrence is not only subject to the environmental changes, but is also facilitated by the events that have occurred in a system. Here, we develop a method for estimating such extrinsic and intrinsic factors from a single series of event-occurrence times. The analysis is performed using a model that combines the…
We perform an extended analysis of the distribution of drawdowns in the two leading exchange markets (US dollar against the Deutsmark and against the Yen), in the major world stock markets, in the U.S. and Japanese bond market and in the gold market, by introducing the concept of ``coarse-grained drawdowns,'' which all…
A new and an enriched JPEG algorithm is provided for identifying redundancies in a sequence of irregular noisy data points which also accommodates a reference-free criterion function. Our main contribution is by formulating analytically (instead of approximating) the inverse of the transpose of JPEGwavelet transform wi…
The deterrent effect of military alliances is well documented and widely accepted. However, such work has typically assumed that alliances are exogenous. This is problematic as alliances may simultaneously influence the probability of conflict and be influenced by the probability of conflict. Failing to account for suc…
DynForest predicts event probabilities from longitudinal data, handling endogenous predictors.
problem Predicting individual risk using longitudinal patient history.
method Random survival forests with time-fixed features from longitudinal predictors.
result DynForest provides accurate individual event probability predictions.
The study examines pricing American options with both exogenous and endogenous transaction costs.
problem Pricing American options with transaction costs and liquidity risks.
method Modeling liquidity risks as a mean-reverting process and transaction costs as proportional to trading amount. Two nonlinear PDEs are used to characterize option values. Numerical solution via ADI method and model calibration using maximum likelihood estimation.
result The model incorporating liquidity risks significantly outperforms the Leland model.
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…
The study shows how probability weighting can lead to betting in a risk-averse economy.
problem Understanding how probability weighting affects economic behavior and risk aversion.
method Examining a von Neumann-Morgenstern economy with an RDU agent to model probability weighting effects.
result Probability weighting can lead to endogenous betting in an economy with common beliefs.
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…
This paper theoretically explains and validates a deep neural network approach to IV estimation.
problem Endogeneity issues in empirical applications, especially in the presence of omitted variables, measurement error, or simultaneous causality.
method A two-stage estimator using deep neural networks in a linear instrumental variables model, with a latent structural assumption on the reduced form equation.
result The second-stage estimator achieves the semiparametric efficiency bound, with a smaller estimation error and requiring weaker conditions on the smoothness of optimal instruments.
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…
Extends QHawkes to MQHawkes for analyzing financial co-jumps.
problem Capturing endogenous co-jumps in financial markets.
method Develops MQHawkes process with quadratic kernels, investigates stationarity, and derives Yule-Walker equations.
result Volatility distribution exhibits power-law behavior with computable exponents.
We study optimal liquidation of a trading position (so-called block order or meta-order) in a market with a linear temporary price impact (Kyle, 1985). We endogenize the pressure to liquidate by introducing a downward drift in the unaffected asset price while simultaneously ruling out short sales. In this setting the l…
Model shows AI adoption amplifies financial market risk through prediction, herding, and cognitive dependency.
problem Systemic risk in financial markets due to AI adoption.
method Developed a unified model within an extended rational expectations framework, incorporating endogenous adoption, performative prediction, algorithmic herding, and cognitive dependency.
result Systemic risk multiplier grows superlinearly with AI penetration, implying tail-loss amplification of 18-54%.
Study portfolio selection with exogenous and endogenous transaction costs using deep learning.
problem Portfolio selection with both exogenous and endogenous transaction costs.
method Deep learning-driven policy iteration scheme for high-dimensional HJB equations.
result Proposes a scheme to address the curse of dimensionality and adapt to high-dimensional control spaces.
Thanks to the access to labeled orders on the Cac40 index future provided by Euronext, we are able to quantify market participants contributions to the volatility in the diffusive limit. To achieve this result we leverage the branching properties of Hawkes point processes. We find that fast intermediaries (e.g., market…
Model shows how banks' fears of future defaults can cause immediate financial stress.
problem How banks' future default worries cause immediate financial stress.
method Dynamic interbank model with endogenous distress contagion, mark-to-market valuation adjustment, forward-backward approach.
result Distress contagion acts as a stochastic volatility term leading to clustering and down-market spikes.
New RL algorithms correct bias in dynamic data analysis.
problem Dynamic data generation and analysis create endogeneity issues.
method Instrument variable (IV)-based reinforcement learning (RL) algorithms.
result Established theoretical properties of IV-RL algorithms.
ddml aids causal inference in econometrics with machine learning.
problem Estimation of causal effects with endogenous variables and unknown functional forms.
method Double/Debiased Machine Learning (DDML) in Stata.
result Monte Carlo evidence supports using DDML with stacking for causal inference.