How Synthetic Exposure calculates Exposure Scores

An Exposure Score is a number between 0.0 and 1.0 that measures how similarly a crypto asset and a stock have moved in price over the past 90 days.

A score of 0.78 means the two assets have had a strong positive price-movement relationship. A score of 0.0 means no positive relationship was detected.

This is not a forecast. A high Exposure Score reflects past similarity, not guaranteed future behaviour.

• Adjusted daily closing prices for the selected stock (Marketstack)
• Daily crypto prices sampled at a consistent UTC timestamp (CoinGecko)
• Default lookback: 90 calendar days
• Only dates on which the stock has a valid close are used
• Minimum 45 aligned observations required to compute a score

1. Sort prices oldest → newest
2. Convert each price series to daily log returns:
   return_t = ln(price_t / price_{t-1})
3. Align stock and crypto returns by date
4. Calculate Pearson correlation r across aligned observations
5. Apply floor and ceiling:
   exposure_score = max(0, min(1, r))

Negative or zero correlation is treated as zero positive exposure. The raw Pearson r value (which can be negative) is preserved in the API response for transparency.

Scores are always displayed as decimals: 0.78, not “78%”. A score does not represent ownership, guaranteed exposure, or an equivalent percentage of price movement.

Scores are recalculated after the relevant stock market closes and optionally every 6 hours. Scores are pre-computed and cached — they are not recalculated during a page request.

Data freshness is shown on every score card and graph node.

• The 90-day window may not capture long-term structural relationships
• Correlation can change rapidly with market regime shifts
• The crypto universe is limited to 30 curated assets
• Stock market holidays reduce observation counts
• Scores reflect price-movement similarity, not ownership, market-cap exposure, or guaranteed equivalent performance