Methodology
Plain-English notes for trusting and auditing SlabSignal scores.
SlabSignal Methodology v2.0.0
Scores are based on the current SlabSignal methodology version.Fair Value
Uses non-outlier comp sales with higher weight on recent sales. Sales older than 365 days are ignored in Analytics Engine v2.
Opportunity Score
A 0-100 weighted score combining value, momentum, liquidity, confidence, risk, data quality, and margin of safety with caps for thin evidence.
Conviction Score
A separate 0-100 trust score based on confidence, data quality, liquidity, volatility, comp depth, recency, and source diversity.
SlabSignal Rating
A 1-5 star rating that translates Opportunity Score, Confidence Score, Risk Score, and Data Quality into labels such as Strong Buy, Buy, Watch, Speculative, and Pass.
Margin of Safety
Compares fair value with asking price when entered, otherwise latest sale. Positive margin means the card is priced below estimated fair value.
Capital Allocation Planner
Ranks eligible cards by opportunity, confidence, liquidity, and positive margin of safety, then normalizes suggested allocations against a fixed budget and max per-card cap.
Value Score
Rewards cards trading below estimated fair value and penalizes cards trading above fair value.
Momentum Score
Compares recent 30-day pricing against the 90-day average to detect short-term price direction.
Liquidity Score
Measures how many valid sales occurred in the last 90 days. More recent sales means easier price discovery.
Confidence Score
Uses comp count, latest sale recency, source diversity, and volatility to estimate how trustworthy the signal is.
Risk Score
Higher is safer. Penalizes high volatility, limited comps, and high population growth when population data exists.
Data Quality Score
Scores the underlying dataset from comp count, latest comp recency, source count, volatility, and missing population data.
Margin of Safety Score
Converts the percentage discount or premium to fair value into a 0-100 score used by Opportunity Score v2.
Score Caps
Very poor confidence, weak data quality, or fewer than three comps can cap Opportunity Score so thin data does not look falsely attractive.
Limitations
Scores are decision-support research only. They do not predict guaranteed returns and should be validated with fresh market comps before purchase.
