Browse: L

LSV show contrarian strategies outperform because investors extrapolate past growth too far, not because value strategies are riskier. Value stocks do NOT have higher risk in bad times.

Effective investment management is currently hindered by the huge disconnect between global market intelligence and personal fiscal reality. Traditional methodologies and foundational frameworks focus primarily on market-centric analysis but remain context blind to personal liquidity, lack long-term...

Continuous latent reasoning enables language models to perform intermediate computation without generating explicit reasoning traces. Advances in stochastic latent reasoning allow multiple paths to be

From Savigny's historical school to Hart's open texture: how law evolves the way language does, why natural-language rules always carry a penumbra of uncertainty, and what that means for turning legislative sentences into executable compliance predicates.

Interactive lessons, quizzes, and tutorials on AML, financial markets, and science.

Motivated by modern marketplaces, where the platform or the seller routinely gathers detailed user profiles, we study a novel learning theoretic model that simultaneously involves information and mech

We build a tractable heterogeneous-firm business cycle model where firms face Knightian uncertainty about their profitability and learn it through production. The cross-sectional mean of firm-level uncertainty is high in recessions because firms invest and hire less. The higher uncertainty reduces a...

Levi and Reuter critically review the evidence for AML effectiveness, questioning whether the massive global investment in AML compliance reduces crime. Foundational critique of AML regime effectiveness.

Liquid democracy permits voters to vote directly or delegate their votes to others. Existing algorithmic analyses assign each voter a single scalar parameter, interpreted as an independent probability

Comprehensive analysis of the latest room temperature superconductivity claim, following rigorous replication attempts by 15 independent laboratories showing partial resistance drops but no definitive zero resistance.

Robotic navigation typically assumes a collision-free route to the goal exists; in cluttered environments with movable obstacles, however, reaching the goal may require physical interaction. Classical

We propose a two-stage large language model (LLM) framework for zero-shot detection of insider threats and advanced persistent threats (APTs) from heterogeneous security logs. The framework models use