Open interest explained: calculation, units and positioning

Reconstruct contract changes, normalise reporting conventions and test what open interest can really tell you about positioning.

Course outline

1. 1

   Reconstruct open interest from opening and closing trades

   Reconstruct open interest from opening and closing trades. See why 27 contracts can trade while open interest rises by only four.

   7 min

   In short: In the single-sided count, each outstanding long/short pair is one unit of open interest. A new long matched with a new short raises OI by one, two closing sides lower it by one, and an opener trading with a closer leaves it unchanged. Volume rises in all three cases.

2. 2

   Read the price–open interest matrix as competing hypotheses

   Price up with OI up is an observation, not a motive. Read the four price and open interest combinations as competing hypotheses with a rejection rule.

   7 min

   In short: Price up with OI up means new exposure during the rise, with shorts entering too; price up with OI down means net closures, possibly short covering. Price down with OI up adds exposure; price down with OI down removes it, possibly including long liquidations. None identifies the winning side.

3. 3

   Normalise open interest: contracts, coins and dollars

   Two open interest charts can measure different units. Split notional growth into price and quantity: notional rises 15.5% while quantity grows only 5%.

   8 min

   In short: Open interest can be reported in contracts, coins or quote value. For a linear product, notional = quantity × price (apply the contract multiplier first), so notional can rise without new positions. From 100 BTC at 60,000 to 105 BTC at 66,000, notional rises 15.5% while quantity grows 5%.

4. 4

   Build an open interest profile and state its limits

   Allocate open interest additions to price buckets, keep closures explicit and separate an estimated activity profile from traders' surviving entries.

   8 min

   In short: Fix the range, bucket size and allocation rule first, then assign each positive sampled OI change to a price bucket, such as the interval's volume-weighted price. Keep net decreases separate and unallocated. The profile estimates where exposure grew, not where remaining traders entered.

5. 5

   Test a trapped-trader hypothesis without inventing positions

   Frame a trapped-trader hypothesis with a fixed range, normalised open interest and price response. Separate supporting evidence from proof of entries or stops.

   8 min

   In short: A trapped-trader idea is a hypothesis, not a position count. Rising normalised OI in a range, a break and a failed reclaim are compatible with pressure on losing positions, but aggregate data cannot show entries, stops or how many are trapped. Predefine the reclaim threshold and what weakens the idea.

Open full-size diagram

1. Reconstruct open interest from opening and closing trades
2. Read the price–open interest matrix as competing hypotheses
3. Normalise open interest: contracts, coins and dollars
4. Build an open interest profile and state its limits
5. Test a trapped-trader hypothesis without inventing positions

Educational material. Examples do not establish a profitable strategy. Trading costs, gaps and liquidation can produce losses beyond a planned stop.