Computational Intermediation and Financial Market Economics
Firm Valuation, Capital Allocation, and Market Efficiency
Abstract
This paper examines financial market economics under AI-mediated intermediation. We analyze how computational consideration, qualification, and transaction infrastructure may affect firm valuation, capital allocation, market efficiency, and investor-relevant measurement in financial markets.
The framework extends Representation Economy concepts to financial markets, examining how representation quality affects cost of capital, market multiples, and liquidity. All analysis is theoretical and requires empirical validation.
Epistemic Status: Theoretical / Non-Empirical
This paper presents a theoretical framework. All claims about financial markets and firm valuation are speculative and require empirical validation.
Financial Market Applications
How AI-mediated intermediation may affect financial markets
Cost of Capital
How representation quality may affect cost of capital through computational admissibility and AI-mediated capital allocation.
Market Multiples
How AI-mediated consideration and representation quality may affect market multiples and valuation metrics.
Capital Allocation
How AI-mediated intermediation may affect capital allocation efficiency and market liquidity.
Firm Valuation
How representation quality and AI-mediated discoverability may affect firm valuation in equity markets.
Citation
How to cite this research publication
APA Style
Patrone, M. (2026). Computational Intermediation and Financial Market Economics: Firm Valuation, Capital Allocation, and Market Efficiency. Representation Economy Research Program, Volume VI. HomeSelf Research. DOI: 10.5281/zenodo.21183982