Algorithmic Markets

 I study how machine intelligence transforms financial markets and institutions. I call this research program Algorithmic Markets, which I define as financial markets in which the core economic functions of information production, capital allocation, and governance are substantially executed by algorithmic systems that operate at scale and adapt faster than human discretionary judgment.

The framework organizes this transformation around three functions. Two dimensions cut across all three. Algorithmic intensity measures the extent to which institutions delegate decisions to machines, and algorithmic commonality the extent to which they rely on shared data, models, and infrastructure.

Algorithmic Information. How machine intelligence reshapes the production, extraction, and interpretation of signals relevant for valuation and price formation. Current work includes Valu(AI)tion, which builds machine-generated intrinsic values from forecasts of corporate profitability, and Algorithmic Exuberance, which studies what happens to prices when algorithmic responses to common signals become mutually reinforcing.

Algorithmic Allocation. How delegated machine decision-making reshapes screening, portfolio choice, and capital allocation, and when individually efficient decisions generate collective fragility. The Algorithmic Markets paper provides the core evidence and model. Institutions using more similar technologies hold more similar portfolios, and greater machine participation can improve price efficiency while increasing fragility.

Algorithmic Governance. How machine intelligence changes the design, regulation, and stability of financial systems, and how institutions assign decision rights and maintain human oversight of algorithmic systems. The Agentic Turn in Finance maps the transition from AI as a decision-support tool to AI as a decision-maker across the financial value chain.

The framework operates at two levels. At the market level, it examines how machine participation affects prices, capital allocation, and financial stability. At the organizational level, it asks how financial institutions build, deploy, and govern the systems that generate these outcomes. Algometrics provides a methodological foundation across all three functions by developing identification theory for forecasting when deployed algorithms alter the data-generating process.

Organizations and Digital Ecosystems

The same questions arise beyond financial markets. I study how organizations adopt, deploy, and govern AI in decision-making, including the emergence of the Chief AI Officer and how firms reorganize authority and accountability around AI. In digital ecosystems, I examine how AI changes cybersecurity and resilience, from generative AI threats and AI-enabled defense to the collective risks that arise when many actors make locally rational security choices.