Data Cleaning

Data

The foundational element of any quantitative model within cryptocurrency, options, or derivatives necessitates rigorous cleaning to ensure integrity and reliability. Raw data streams, originating from exchanges, oracles, and internal systems, frequently contain errors, inconsistencies, and missing values that can severely compromise subsequent analysis and trading strategies. Effective data cleaning establishes a robust foundation for accurate risk assessment, backtesting, and ultimately, informed decision-making, mitigating the potential for flawed conclusions derived from compromised datasets.