Every prediction starts with a thesis — a qualitative view on where the stock is headed. But a thesis is only useful if it can be tested. Thesis monitors are the system's way of asking: "What would prove me wrong?"

What Are Falsifiable Hypotheses?

When the LLM generates a thesis, it also produces 2–4 falsifiable hypotheses — specific, testable conditions that would invalidate the thesis if they occur.

Think of them as tripwires: if the metric crosses the threshold, the tripwire fires, and the system knows the thesis may need revision.

Example Hypothesis	What It Means
"If RSI crosses above 70, the bullish thesis is weakened"	Overbought conditions could reverse the uptrend
"If price falls below $145, the bear case is confirmed"	Key support level broken — downside risk realized
"If put/call volume ratio rises above 1.2, hedging pressure is excessive"	Market is betting against the stock
"If sentiment drops below 30, the thesis is invalidated"	News has turned decisively negative

What Makes a Good Hypothesis?

The system validates each hypothesis before registering it:

• Not already breached — if RSI is already 75, a hypothesis saying "RSI above 70" is rejected (it would fire immediately)
• Plausible scale — price thresholds must be within 0.3×–3× of the current price (no "price above $5000" for a $50 stock)
• Testable — the metric must be one the system can actually monitor (price, RSI, volume, sentiment, etc.)

What Are Fuses?

A fuse is the outcome of a hypothesis over the prediction period:

• Triggered fuse (red) — the metric crossed the threshold. The condition that could invalidate the thesis was met.
• Safe fuse (green) — the metric never crossed the threshold. The thesis survived on this point.

At resolution time, the retrospective shows which fuses fired and which survived.

The Full Workflow

📝

Day 0 — Generate

LLM produces thesis + 2–4 falsifiable hypotheses

↓

✅

Validate

Reject already-breached or implausible thresholds

↓

💾

Register

Store as active monitors in database

↓

🔄

Days 1–N — Monitor Daily

Check each monitor against live market data

↓

🚨

Triggered

Metric crossed threshold → injected into next prediction

↓

🛡️

Safe

Threshold not breached → stays active

↓

📊

Day N — Resolution

Prediction resolves → Retrospective shows triggered vs safe fuses

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🧠

Post-Mortem

Fuses inform what invalidated the thesis and why

Stage 1: Generation (Day 0)

When a new prediction is made, the LLM produces a thesis with falsifiable hypotheses. Each hypothesis has:

Field	Description
Statement	Human-readable text: "If RSI crosses above 70, the bullish thesis is weakened"
Trigger type	Category: price_level, rsi_cross, volume_spike, sentiment_shift
Monitoring metric	What to watch: current_price, rsi_1d, put_call_volume_ratio, etc.
Threshold direction	above or below
Threshold value	The numeric trigger point
Impact	Severity if triggered: minor, moderate, or severe

The system validates each hypothesis, then stores it as an active monitor in the database.

Stage 2: Continuous Monitoring (Days 1–N)

Every day, the system checks each active monitor against live market data:

1. Fetches the current value of the monitored metric
2. Compares it against the threshold
3. If breached → marks the monitor as triggered and records the actual value

This happens continuously throughout the prediction period — not just at resolution time. A fuse can fire on Day 2, Day 5, or any day before the target date.

Stage 3: Context Injection

When a fuse fires, it's injected into the next prediction as context:

=== PREVIOUSLY TRIGGERED HYPOTHESES ===
  • If RSI crosses above 70, the bullish thesis is weakened
    Trigger: rsi_1d above 70 (actual: 72.3)
  • If price falls below $145, the bear case is confirmed
    Trigger: current_price below 145 (actual: 143.21)

This tells the LLM: "Your previous thesis had these conditions violated — take that into account."

Stage 4: Resolution & Retrospective

When the prediction's target date passes, the retrospective summarizes the fuse analysis:

• Triggered fuses — which conditions were met (the thesis was invalidated on these points)
• Safe fuses — which conditions never occurred (the thesis survived)

The retrospective generates a 2–3 sentence takeaway explaining what the fuses mean for thesis quality.

Where You'll See This

All thesis monitor data is available at app.f1n.tech/predictions.

Reasoning

On the Predictions page, click View reasoning for any prediction to see the falsifiable hypotheses listed under the thesis. This tells you what conditions the system is monitoring for that prediction.

Retrospective

On the Predictions page, click the retrospective button (book icon) for a specific prediction to see the fuse analysis.

When is the retrospective available?

The retrospective is generated after the prediction's target date passes and the accuracy validation runs. This typically happens on the next trading day after the target date (default schedule: weekdays at 17:00). Until then, the retrospective button will not appear for that prediction.

The retrospective shows:

• "What are Fuses?" — explanation of the concept
• Triggered Fuses (red section) — conditions that were met during the prediction period
• Safe — Never Fired (green section) — conditions that stayed within bounds

Each fuse shows the metric, threshold, and the actual value when it triggered (or didn't).

Why This Matters

Falsifiable hypotheses make the system self-aware. Instead of blindly trusting its own predictions, the system:

1. Defines what would prove it wrong — before the fact, not after
2. Monitors continuously — catches invalidation early, not just at resolution
3. Incorporates feedback — triggered fuses inform the next prediction
4. Learns from outcomes — the retrospective analyzes which assumptions held and which didn't

This creates a feedback loop: the more predictions the system makes, the better it gets at defining meaningful hypotheses and recognizing when its thesis is breaking down.

Key Terms

Term	Definition
Falsifiable hypothesis	A specific, testable condition from the thesis (e.g., "RSI will cross above 58"). Monitored daily — if triggered, the thesis may need revision
Thesis monitor	A database record tracking a falsifiable hypothesis against live market data. Status: active, triggered, or expired
Fuse	The outcome of a hypothesis — either "triggered" (metric crossed threshold) or "safe" (never fired)
Triggered fuse	A hypothesis that fired during the prediction period. The actual metric value crossed the threshold
Safe fuse	A hypothesis that never fired. The metric stayed within bounds throughout the prediction period
Proximity gate	Prevents near-duplicate monitors — rejects a new hypothesis if an existing one has a threshold within ±20% on the same metric