Simple Functions
GLOSSARY/ANALYSIS

Thesis Confidence Score

Confidence is a 0-100% score that measures how certain you are about your probability estimates, not the probability itself. High confidence means your estimates are well-researched; low confidence means they're speculative.

CLI:sf thesis view

Confidence vs. Probability

This distinction trips up new traders constantly:

  • Probability: "I think there's a 40% chance of recession"
  • Confidence: "I'm 75% sure that my 40% estimate is close to correct"

You can have high confidence in a low probability ("I'm very sure this is unlikely") or low confidence in a high probability ("I think this is likely but I haven't done enough research").

Why Confidence Matters

Confidence should drive position sizing, not probability. A 40% probability with 90% confidence warrants a larger position than a 60% probability with 30% confidence.

Confidence in SimpleFunctions

Each causal tree node has both a probability and a confidence score:

  • High confidence (>70%): The node probability is based on hard data (official statistics, confirmed events). The agent sizes positions larger.
  • Medium confidence (40-70%): Reasonable estimates based on analysis, but could shift with new information.
  • Low confidence (<40%): Speculative estimates. The agent flags these nodes for additional research and reduces position sizes.

How Confidence Changes

Confidence increases when:

  • Official data confirms your estimate
  • Multiple independent sources agree
  • Historical base rates support your number

Confidence decreases when:

  • New contradictory information emerges
  • Your estimate is based on a single source
  • The situation is genuinely unprecedented (no base rate)

The evaluation cycle updates both probabilities and confidence scores when new signals arrive.

Example

Causal tree nodes with confidence:

n1: Labor market deterioration
  Probability: 55%
  Confidence:  72%
  Basis: BLS data, weekly jobless claims, JOLTS

n2: Consumer spending decline
  Probability: 45%
  Confidence:  70%
  Basis: Retail sales data, credit card spending

n3: Fed policy error
  Probability: 30%
  Confidence:  45%  ← LOW CONFIDENCE
  Basis: Speculation about Fed reaction function

Action: Node n3 has low confidence. The agent recommends
researching Fed communication more before sizing positions
that depend on this branch.

Related Terms

Causal Tree

A causal tree is a structured probabilistic model that breaks down a complex event into a hierarchy of independent, verifiable sub-conditions. Each node has a probability, and the tree computes the overall probability of the root event.

Thesis

A thesis is a structured investment argument that combines a directional view, a causal model of why the view is correct, and specific market positions that express the view. In SimpleFunctions, a thesis is the core unit of analysis.

Node Probability

Node probability is the estimated likelihood assigned to a specific node in a causal tree. Changes to leaf node probabilities cascade upward through the tree, updating the root probability and all derived edge calculations.

Evaluation Cycle

An evaluation cycle is the automated process by which the agent reviews new signals, updates causal tree probabilities, recalculates edge, and determines whether any strategy conditions are met.

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