Version 1.6 · Valid from 22 April 2025

Download the full methodology here.

Introduction

Blocksize produces the 30-Minute VWAP data feed as part of its crypto market data offering. All data points are converted and delivered in U.S. Dollars, Euros and other currencies across an expanding set of cryptocurrencies and digital asset classes.

The 30-Minute VWAP feed is designed to be a transparent, independent pricing source that supports efficient markets, reduces information asymmetry between participants, and helps establish crypto and digital assets as an asset class held to the highest standards.

It supports a wide range of use cases:

• Compliance — monitoring best-execution policies, market abuse regulation and Market Conformity Checks (MCC)

• Performance evaluation — a closing benchmark for comparing performance across days, weeks, months or years

• Index calculation — an input to the values of market indices

• Portfolio valuation — determining the net asset value (NAV) of funds, ETFs and other portfolios

• Trading strategies — identifying trends and patterns from closing levels

• Risk management — calculating volatility, value at risk (VaR) and other risk measures

• Settlement and clearing — settling and clearing transactions at correct values

• Derivatives pricing — pricing options and futures, and triggering events in smart contracts

• Benchmark for contracts — referencing ESOPs and performance-based compensation agreements

The feed is calculated using a transparent, robust methodology governed by the Blocksize Data Committee, with a clear framework of policies and procedures aligned to international best practices.

Definitions

Trade event — the data about a trade observed by Blocksize on an exchange: its price, volume and timestamp, denoted ε = {p, v, t}.

Closing times — 00:00:00 UTC and every 30 minutes thereafter (00:30:00, 01:00:00, 01:30:00, and so on).

Closing price data interval — the 30-minute interval preceding each closing time. Trade events observed within this interval are used to evaluate the closing prices that enter the feed.

Calculation Algorithm

1. The algorithm runs five seconds after each closing time, because some accepted exchanges report trade events with a small delay.

2. For every exchange with trade events observed within the closing price data interval, the last trade event before the closing time is taken. For each closing time, this produces a set S(t) of prices, volumes and timestamps, where Ω denotes the set of all exchanges with trade events.

3. The closing price is the volume-weighted average price of the trade events in S(t):

P(t) = Σ (pₑ × vₑ) / V, where V = Σ vₑ is the total aggregated size of the trade events in S(t).

Data Contingency Rules

1. If trade events from an accepted exchange can't be collected due to a technical problem during the closing price data interval (such as malformed data), those events are excluded from that instance of the feed.

2. If no trade events from a specific accepted exchange exist during the closing price data interval, the feed relies on the other accepted exchanges for its calculation.

3. If none of the accepted exchanges report trade events, the feed reports the closing price of the previous closing time.

Data Exclusion Rules

All observable trade events from accepted exchanges are verified for integrity. If errors are detected, the input is excluded from the calculation. Incomplete trade events — for example, a missing volume or timestamp — are not considered. Where errors can't be reliably identified automatically, the next steps are determined by the expert judgment of the Blocksize Data Committee, which continues including or excluding data from the exchange until the anomaly is resolved. Any exercise of expert judgment must be approved by staff members.

Data Quality Assurance

All observable transactions from accepted markets are evaluated using algorithmic anomaly and outlier detection. Suspected errors or anomalies are excluded from the calculation. Alongside the automated methods, the Blocksize Data Committee applies expert judgment to maintain and improve data quality, adding vetted new sources or excluding markets that begin delivering anomalous data. Any exercise of expert judgment must be approved by staff members.