arXiv research

The paper analyzes trading strategies in a competitive market with incomplete information.

Paper analyzes strategic underreporting in competitive insurance markets.

LLMs can collude in market divisions, maximizing profits.

Study examines strategic exit timing in uncertain competition.

New paper finds strategic trade centralization benefits firms, while naive centralization often harms them.

The goal of this study is to determine which strategic model, either IO or RBV, allows firms to generate the highest performance on a competitive market. Contrasting with classical studies that mobilize analyses as VARCOMP, we deploy a multi-agent system simulating the behavior of firms adopting RBV or IO strategic mod…

Neoclassical economics has two theories of competition between profit-maximizing firms (Marshallian and Cournot-Nash) that start from different premises about the degree of strategic interaction between firms, yet reach the same result, that market price falls as the number of firms in an industry increases. The Marsha…

Study strategic competition in commodity markets using impulse-switching controls.

Models analyze strategic risk-taking in continuous action games.

Study examines pricing strategies in competitive supply chains with discrete prices.

Game theory models storage investment to balance market competition and profits.

Data competitions rely on real-time leaderboards to rank competitor entries and stimulate algorithm improvement. While such competitions have become quite popular and prevalent, particularly in supervised learning formats, their implementations by the host are highly variable. Without careful planning, a supervised lea…

Study examines how traders with asymmetric information and adaptive learning strategies affect market efficiency.

The paper analyzes strategic irreversible investments with novel dynamic strategies.

Informed traders strategically reveal noisier signals, making prices less responsive to public information.

Study optimal treatment assignment policies under strategic agent responses.

Investors' strategic trading affects asset prices, modeled as a game.

Study explores optimal strategies in games with multiple players and mean-field interactions.

Investment challenge study finds luck and strategy equally important.

Competition has been introduced in the electricity markets with the goal of reducing prices and improving efficiency. The basic idea which stays behind this choice is that, in competitive markets, a greater quantity of the good is exchanged at a lower and a lower price, leading to higher market efficiency. Electricity …

We consider thin incomplete financial markets, where traders with heterogeneous preferences and risk exposures have motive to behave strategically regarding the demand schedules they submit, thereby impacting prices and allocations. We argue that traders relatively more exposed to market risk tend to submit more elasti…

Modeling dealer competition, internalisation and externalisation impact market dynamics and costs.

The paper tackles strategic behavior in decision-making with counterfactual explanations.

The paper analyzes strategic interactions in a multi-agent reinsurance chain using game theory.

A game-theoretic analysis of DEX competition through dynamic trading fees.

Two firms compete in a financial market, choosing dividend strategies to avoid default and maximize profits.

We investigate a randomization procedure undertaken in real option games which can serve as a basic model of regulation in a duopoly model of preemptive investment. We recall the rigorous framework of [M. Grasselli, V. Leclère and M. Ludkovsky, Priority Option: the value of being a leader, International Journal of Theo…

Paper studies competitive networks where teams aim to minimize their own objectives, adapting to each other's strategies.

A new method for analyzing product competition using low-dimensional embeddings.

Financial markets are not random, but hard to predict due to hidden causes and strategic use.

Real-time advertising allows advertisers to bid for each impression for a visiting user. To optimize specific goals such as maximizing revenue and return on investment (ROI) led by ad placements, advertisers not only need to estimate the relevance between the ads and user's interests, but most importantly require a str…

Study optimal liquidation strategies in lit and dark pools with and without regulation.

The paper analyzes reinsurance strategies in a competitive multi-agent system.

Most sales applications are characterized by competition and limited demand information. For successful pricing strategies, frequent price adjustments as well as anticipation of market dynamics are crucial. Both effects are challenging as competitive markets are complex and computations of optimized pricing adjustments…

Dynamic pricing policy converges to Nash equilibrium with low regret.

New framework for robust uncertainty quantification in strategic settings.

An ability to postpone one's execution without penalty provides an important strategic advantage in high-frequency trading. To elucidate competition between traders one has to formulate to a quantitative theory of formation of the execution price from market expectations and quotes. This theory was provided in 2005 by …

Paper generalizes strategic classification framework and introduces SVC for PAC-learning.

Study strategic dynamic pricing for buyers with unknown manipulation costs.

Study analyzes market equilibrium returns with price impact and transaction costs.

New framework reduces strategic manipulation cost for minority groups in fair classification.

Study compares employers with and without anticipating strategic labor force responses.

Study uses Open Banking data to estimate customer value, showing potential 21% increase.

New algorithm learns optimal policies in strategic MDPs with private types.

Deep neural network (DNN) has demonstrated its success in multiple domains. However, DNN models are inherently vulnerable to adversarial examples, which are generated by adding adversarial perturbations to benign inputs to fool the DNN model to misclassify. In this paper, we present a cross-layer strategic ensemble fra…

New analysis shows rational actors will deploy AGI despite negative social value due to catastrophic risk.

New findings show strategic interactions can undermine model expressiveness in machine learning.

Consequential decision-making typically incentivizes individuals to behave strategically, tailoring their behavior to the specifics of the decision rule. A long line of work has therefore sought to counteract strategic behavior by designing more conservative decision boundaries in an effort to increase robustness to th…