On the estimation of Volatility in the Samuelson-Economic Model

摘要

We outline a highly error resistant method of volatility estimation that is inspired by the most successful, Hough Transform method for extracting geometrical shapes from noisy digital images. Test results on simulated Samuelson Economic model (geometric Brownian motions) are presented; we also present the results of extracting drift and volatility from a short-time history of a real stock price.