Kernel Density Estimation: How KDE Works and How It Differs From Kernel Smoothing
Financial markets are full of noise. Prices fluctuate, returns vary, and market conditions can change quickly, making it challenging to understand where data is concentrated or which observations are unusual. This is where Kernel Density Estimation (KDE) can help. KDE is a non-parametric statistical technique that estimates the probability distribution of financial data, giving traders…
