arXiv research

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

Model predicts trading strategies based on latent demand and price impact.

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

Investors can enhance their portfolios by strategically using LETFs, especially with dynamic strategies.

Study identifies a Strategic Gap in market efficiency due to AI-driven timing and complexity in disclosure.

Investors can achieve optimal risk-reward trade-offs with bonds and stocks under mean-reverting stock returns.

Investors' strategies in a market influenced by price impact are analyzed, showing aggressive behavior when impact exceeds a critical point.

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

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

This paper investigates the equilibrium interactions between trading targets and private information in a multi-period Kyle (1985) market. There are two investors who each follow dynamic trading strategies: A strategic portfolio rebalancer who engages in order splitting to reach a cumulative trading target and an uncon…

Study shows cognitive load impacts financial market efficiency, especially for less sophisticated investors.

In illiquid markets, option traders may have an incentive to increase their portfolio value by using their impact on the dynamics of the underlying. We provide a mathematical framework within which to value derivatives under market impact in a multi-player framework by introducing strategic interactions into the Almgre…

Investor and firm optimize sustainable investment and emission reduction through a dynamic game.

We consider a stochastic game between a trader and a central bank in a target zone market with a lower currency peg. This currency peg is maintained by the central bank through the generation of permanent price impact, thereby aggregating an ever increasing risky position in foreign reserves. We describe this situation…

Optimizes information acquisition to reduce estimation risk and maximize utility.

Game-theoretic model captures investor interactions for stock price forecasting.

Study optimizes resource allocation in noisy systems for better control.

The purpose of this article is to propose a new "theory," the Strategic Analysis of Financial Markets (SAFM) theory, that explains the operation of financial markets using the analytical perspective of an enlightened gambler. The gambler understands that all opportunities for superior performance arise from suboptimal …

In this paper, we propose an innovative investment framework incorporating asset allocation and class diversification oriented specifically for the biotechnology industry. With growing interests and capitalization in multiple biotech markets, investors require a more dynamic method of managing their assets within indiv…

In this paper we examine the process involved in the design and implementation of a port-graph model to be used for the analysis of an agent-based rational negligence model. Rational negligence describes the phenomenon that occurred during the financial crisis of 2008 whereby investors chose to trade asset-backed secur…

This article presents results from the first statistically significant study of cost escalation in transportation infrastructure projects. Based on a sample of 258 transportation infrastructure projects worth US$90 billion and representing different project types, geographical regions, and historical periods, it is fou…

Study uses LLMs to improve Black-Litterman portfolio optimization.

AI agents manage portfolios, improving on human oversight.

Firms disclosing positive earnings surprises are more likely to disclose ESG information.

New framework for robust uncertainty quantification in strategic settings.

Research shows eco-innovation boosts earnings management, especially in constrained firms.

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

Study strategic dynamic pricing for buyers with unknown manipulation costs.

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

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

Optimizes asset allocation with illiquid assets using MPC.

Paper examines financial engineering problems and introduces AlphaZero for better replication strategies.

The study identifies core and satellite segments in the cryptocurrency market.

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…

This paper extends financial theory to measure learnable market structure under computational constraints.

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…

Strategic feature selection in high-stakes domains like healthcare.

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

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

Algorithm learns optimal coordination for strategic agents in uncertain settings.

Randomised classifiers outperform deterministic ones in strategic classification.

Study one-shot strategic classification under unknown costs, improving worst-case accuracy.

Rebellion Research's AI strategy outperformed the S&P 500 for 14 years.

Consequential decision-making incentivizes individuals to strategically adapt their behavior to the specifics of the decision rule. While a long line of work has viewed strategic adaptation as gaming and attempted to mitigate its effects, recent work has instead sought to design classifiers that incentivize individuals…

AI model automates financial investment research tasks.

Proof-of-Stake networks with EIP-1559 exhibit stable token prices and secure network security.