Advanced Filters and Indicators
Reducing the noise substantially and building a cohesive map of the volume, liquidity and hidden layers of the market microstructure.
GDA makes trades based on market microstructure data which includes liquidity clusters and volume data points.
However, crypto data provided by centralised exchanges (although free) can be unreliable and is full of noise. Users wanting to access this are subject to throttling mechanisms limiting the amount and quality of data they receive.
For GDA to be able to create a next-generation order book for public use, there is a need for high-quality granular data. To make this possible, our R&D team has developed proprietary indicators (filters) to cut the noise included in CEX extracted data.
(Raw data + filtering level 1 formula)
Level 1 Indicators
(Filter + Level 2 formula + TA)
Level 2 Indicators
(Level 1 Indicators + Level 3 formula)
The above image illustrates how the process for refining data works. First, market microstructure data is collected through GDA-designed microservice architecture. Proprietary filters have the ability to transform this data into liquidity cluster charts. This is similar to the type of data available from sites such as ExoCharts.
The application of several techniques and formulas help cut ‘false’ information from the dataset, leaving behind a true representation of a liquidity cluster. This is further processed to produce actionable values - also known as indicators.
The resulting level of high quality and accurate data allows GDA to trade with confidence.
An article on our indicators can be found here.