Data Cleaning Accuracy

Computation

Data cleaning accuracy serves as the foundational requirement for quantifying the reliability of raw market feeds within cryptocurrency derivatives exchanges. It involves the systematic removal of noise, redundant websocket packets, and erroneous price ticks that could otherwise corrupt historical backtesting results or real-time arbitrage execution. Quantitative analysts demand high precision here to prevent the propagation of latent errors into volatility surface models or Greeks estimation.