arXiv research

Model financial markets using open quantum systems to understand market imperfections.

New numerical method for quantile hedging in imperfect markets.

Study on liquidity and market efficiency in auction games with imperfect information.

Volatility smiles emerge from imperfect hedging in financial markets.

We study pricing and superhedging strategies for game options in an imperfect market with default. We extend the results obtained by Kifer in \cite{Kifer} in the case of a perfect market model to the case of an imperfect market with default, when the imperfections are taken into account via the nonlinearity of the weal…

We present a novel methodology for predicting future outcomes that uses small numbers of individuals participating in an imperfect information market. By determining their risk attitudes and performing a nonlinear aggregation of their predictions, we are able to assess the probability of the future outcome of an uncert…

Study pricing and hedging for American options in a market with default risk.

We derive asset pricing formula for markets with incomplete information and subjective views.

I study the limit of a large random economy, where a set of consumers invests in financial instruments engineered by banks, in order to optimize their future consumption. This exercise shows that, even in the ideal case of perfect competition, where full information is available to all market participants, the equilibr…

Study completes financial markets in complex models without external probabilities.

The paper analyzes insurance pricing and capital allocation in imperfect markets.

The paper develops a new discount rate for derivatives using imperfect securities as collateral.

Paper proposes a novel policy distillation method for better order execution in noisy markets.

Develops methods to improve demand counterfactuals from imperfect proxies.

Heuristic pricing strategy compensates for imperfect market anticipation in dynamic pricing competition.

Model shows disclosure reduces trading costs in oligopolistic markets.

New method improves IL from imperfect demos using confidence scores.

The importance of collateralization through the change of funding cost is now well recognized among practitioners. In this article, we have extended the previous studies of collateralized derivative pricing to more generic situation, that is asymmetric and imperfect collateralization with the associated counter party c…

High-frequency traders manage inventories to exploit price information, leading to mean-reverting inventories and excess trading.

We propose a new non parametric technique to estimate the CALL function based on the superhedging principle. Our approach does not require absence of arbitrage and easily accommodates bid/ask spreads and other market imperfections. We prove some optimal statistical properties of our estimates. As an application we firs…

We study the problem of optimal execution of a trading order under Volume Weighted Average Price (VWAP) benchmark, from the point of view of a risk-averse broker. The problem consists in minimizing mean-variance of the slippage, with quadratic transaction costs. We devise multiple ways to solve it, in particular we stu…

The paper explores how regularization can lead to convergence in imperfect information games.

The paper tackles learning from imperfect human feedback, especially in dueling bandit problems.

Model learns tensor representations from imperfect multimodal data.

The paper proposes a new framework to generate synthetic data with human-like imperfections to prevent model collapse.

Investigates a Kyle model with imperfect information and risk aversion.

This paper studies the equilibrium pricing of asset shares in the presence of dynamic private information. The market consists of a risk-neutral informed agent who observes the firm value, noise traders, and competitive market makers who set share prices using the total order flow as a noisy signal of the insider's inf…

It is believed by the majority today that the efficient market hypothesis is imperfect because of market irrationality. Using the physical concepts and mathematical structures of quantum mechanics, we construct an econophysics framework for the stock market, based on which we analogously map massive numbers of single s…

New method tackles simulator imperfection in data assimilation.

Study liquidity impact on spread option pricing.

Study on how imperfect labels affect classification methods.

In a financial market, for agents with long investment horizons or at times of severe market stress, it is often changes in the asset price that act as the trigger for transactions or shifts in investment position. This suggests the use of price thresholds to simulate agent behavior over much longer timescales than are…

We study the optimal trading policies for a wind energy producer who aims to sell the future production in the open forward, spot, intraday and adjustment markets, and who has access to imperfect dynamically updated forecasts of the future production. We construct a stochastic model for the forecast evolution and deter…

Policy gradient method proves convergence in imperfect-information games.

New method robustly discovers causal relationships from imperfect data.

Study on teaching with imperfect knowledge, showing its impact on optimal teaching sets.

This paper performs the numerical analysis and the computation of a Spread option in a market with imperfect liquidity. The number of shares traded in the stock market has a direct impact on the stock's price. Thus, we consider a full-feedback model in which price impact is fully incorporated into the model. The price …

JPS improves joint policies for multi-agent collaboration in imperfect information games.

Triangle lasso improves clustering and optimization in noisy graphs.

The paper models rating transitions and calibrates them to market data for XVA calculations.

CPP improves predictive model outputs for better intervention decisions.

Deep neural network learns to play Big 2, a 4-player imperfect information game, outperforming amateurs.

Algorithm learns NE in imperfect information games with imperfect feedback.

Paper studies fairness postprocessing with imperfect attribute information.

Improves off-policy evaluation with imperfect annotations.

Market trade-routes can support infectious-disease transmission, impacting biological populations and even disrupting causal trade. Epidemiological models increasingly account for reductions in infectious contact, such as risk-aversion behaviour in response to pathogen outbreaks. However, market dynamics clearly differ…

Bayesian machine learning algorithm for causal effects with imperfect compliance.

The study examines how verifier imperfections impact test-time scaling techniques.