Data Distribution Fitting

Methodology

Data distribution fitting involves mapping empirical market returns onto specific probability density functions to estimate the likelihood of future price movements. Quantitative analysts utilize this process to quantify tail risk, ensuring that the heavy-tailed nature of cryptocurrency assets is captured beyond traditional normal distribution assumptions. Precise alignment between observed data and selected models reduces estimation error when calculating Greeks for complex options portfolios.