Computational Liquidity (CL)
CLDegree to Which an Asset Can Be Discovered, Interpreted, Verified, Compared, and Acted Upon by Computational Agents
Proposed hypothesis — not yet testedpublished
CL measures machine-processability under bounded inference.
By Marco Patrone
clcomputational_liquiditymachine_processabilityinference_costrepresentation_primitive
Definition
CL measures machine-processability under bounded inference. Higher CL indicates better allocability with lower computational cost.
CL assesses how easily computational agents can discover, interpret, verify, compare, and act upon an asset at low inference cost.
Conceptual Formula
CL(a) = f(representation, verification, structure, timeliness, actionability).Methodology
Type
index construction
Data Sources
synthetic
Confidence Level
medium
Description
CL(a) = f(representation, verification, structure, timeliness, actionability).
Limitations
- Requires multi-dimensional assessment
- Inference cost estimation is heuristic
Key Takeaways
Key Points
- CL scales 0-100
- Multi-dimensional processability
- Inverse to inference burden
Target Audience
asset managersai systemsinfrastructure designers
Relevance Tags
clcomputational_liquiditymachine_processabilityinference_cost
Source Paper
Citation
For Computational Liquidity (CL), see HomeSelf Research (2026), The AI Allocability Discount.