arXiv research

dYdX updates liquidity provider incentives to enhance trading efficiency.

Model shows government incentives boost green bond investment.

Study on wealth and trading in PoS blockchain.

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

Short-term incentives lead to riskier trading strategies.

Exchange uses incentives to optimize limit order book dynamics.

Paper proposes incentive mechanism to encourage participation in federated learning.

This paper analyzes the dynamic incentives for technology adoption under a transferable permits system, which allows for strategic trading on the permit market. Initially, firms can invest both in low-emitting production technologies and trade permits. In the model, technology adoption and allowance price are generated…

Study optimizes health incentives to balance efficiency and fairness.

Model shows incentives in shared order book can lead to free-rider problem.

This paper addresses reward estimation and incentive design for agents with hidden rewards.

We investigate the role of networks of alliances in preventing (multilateral) interstate wars. We first show that, in the absence of international trade, no network of alliances is peaceful and stable. We then show that international trade induces peaceful and stable networks: trade increases the density of alliances s…

Paper tackles online learning for DR management with incentives.

Study on time-zero efficiency of European power derivatives markets using statistical tests and trading rules.

The paper proposes a model reward scheme for collaborative ML based on Shapley value and information gain.

Triangle fees adjust fees based on trade size and price movement, improving price accuracy and revenue.

The paper analyzes regret in bilateral trade mechanisms without prior valuations.

Model analyzes trading frictions in cap-and-trade markets, showing how they interact to affect market effectiveness.

We refine toxicity bounds for dynamic liquidation incentives in CP-AMM systems.

We study analytically and numerically Minority Games in which agents may invest in different assets (or markets), considering both the canonical and the grand-canonical versions. We find that the likelihood of agents trading in a given asset depends on the relative amount of information available in that market. More s…

Study optimal incentives for cleaner energy production.

Mobile payment such as Alipay has been widely used in our daily lives. To further promote the mobile payment activities, it is important to run marketing campaigns under a limited budget by providing incentives such as coupons, commissions to merchants. As a result, incentive optimization is the key to maximizing the c…

We consider the issue of a market maker acting at the same time in the lit and dark pools of an exchange. The exchange wishes to establish a suitable make-take fees policy to attract transactions on its venues. We first solve the stochastic control problem of the market maker without the intervention of the exchange. T…

Two-stage mechanism designs reduce regret in recommender systems with stochastic covariates.

Study assesses how much security restaking protocols need to pay for.

Modeling business expansion as a stochastic control problem, the study finds that firms are incentivized to expand but may wait.

AI task delegation faces incentive collapse with unbounded payments as AI accuracy rises.

In an economy with asymmetric information, the smart contract in the blockchain protocol mitigates uncertainty. Since, as a new trading platform, the blockchain triggers segmentation of market and differentiation of agents in both the sell and buy sides of the market, it recomposes the asymmetric information and genera…

US firms improve ESG performance in response to China trade shock.

A novel incentive mechanism improves fairness and participation in federated learning.

The paper develops an economic foundation for multi-agent learning in markets.

Incentive-aware recommender system for online platforms.

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…

The relationship between international trade and foreign direct investment (FDI) is one of the main features of globalization. In this paper we investigate the effects of FDI on trade from a network perspective, since FDI takes not only direct but also indirect channels from origin to destination countries because of f…

We study online learning settings in which experts act strategically to maximize their influence on the learning algorithm's predictions by potentially misreporting their beliefs about a sequence of binary events. Our goal is twofold. First, we want the learning algorithm to be no-regret with respect to the best fixed …

Method uses ANN to estimate incentive salience from large behavioral data.

How can we design safe reinforcement learning agents that avoid unnecessary disruptions to their environment? We show that current approaches to penalizing side effects can introduce bad incentives, e.g. to prevent any irreversible changes in the environment, including the actions of other agents. To isolate the source…

Centralized exchanges influence staking behavior and decentralization in Proof of Stake blockchain ecosystems.

Framework trains safe agents avoiding deceptive behavior.

Study shows ethanol blends and incentives can significantly reduce transportation carbon emissions.

When the planning horizon is long, and the safe asset grows indefinitely, isoelastic portfolios are nearly optimal for investors who are close to isoelastic for high wealth, and not too risk averse for low wealth. We prove this result in a general arbitrage-free, frictionless, semimartingale model. As a consequence, op…

Study shows visual feedback and monetary incentives reduce plugload energy consumption in commercial buildings.

Promising federated learning coupled with Mobile Edge Computing (MEC) is considered as one of the most promising solutions to the AI-driven service provision. Plenty of studies focus on federated learning from the performance and security aspects, but they neglect the incentive mechanism. In MEC, edge nodes would not l…

The study compares M6 competitors' performance to industry benchmarks and discusses incentives for investment managers.

COBRA addresses strategic behavior in online platforms by ensuring truthful reporting without monetary incentives.

Study allocates resources to strategic agents while balancing cost and incentives.

Study incentive efficiency in monopoly insurance markets with hidden information.

Forward hedging reshapes incentive provision in firms.