Tick Data Filtering

Tick data filtering is the process of cleaning and processing raw, high-frequency trade data to remove errors and irrelevant noise. This data, which records every individual trade and quote, is extremely large and contains significant market microstructure artifacts.

Effective filtering allows analysts to derive accurate signals for trading strategies and risk models. It involves techniques such as removing outliers, handling duplicate records, and correcting for data gaps.

Without proper filtering, quantitative models may produce misleading results based on faulty inputs. This is a foundational step in the data pipeline for any sophisticated trading system.