Data Fitting

Methodology

Data fitting represents the computational process of constructing a mathematical function that best captures the relationship between observed historical price points or volatility surfaces and a chosen model. Traders employ this technique to minimize the residual sum of squares between predicted and actual market movements within crypto derivative chains. Successful implementation requires a balance between theoretical precision and the inherent noise found in high-frequency trading data.