Methodology
We currently report the liquidity of all market pairs using our Liquidity Score, and estimate the number of traders on the exchange using our Web Traffic Factor. Taking these factors into account, together with time and sales, we then construct a machine learning model to estimate volumes of every single market pair that exchanges report. With estimated volumes, we can then detect outliers where exchanges report far higher volumes than the model predicts — based on the amalgamation of all these factors involved — allowing us to flag them accordingly via our Confidence indicator.
The Confidence indicator will be categorized into 3 bands:
- High >75%
- Moderate 50% - 75%
- Low <50%
This Confidence indicator will provide our users with a quick and easy way to understand the level of confidence we have in the market’s reported volume.
This model will gradually improve over time with more data being ingested and processed.
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