Kalman Filter and Predictor Formulation for Predicting the Price Signal and the Optimal Spacing Interval

Abstract

本文目的是想藉由卡門濾淨與預測方法，來預測價格變動訊號，並提出一個一般化之預測公式。此外，我們也將探討預測之訊息增益與取樣區間長短之關係，由此，推導出最適之取樣區間。The purpose of this note is intended to propose a general formula for predicting the price signal by way of Kalman filter and predictor algorithm. Additionally, we will also explore the relationship between the predictor gain and the time interval of spacing samples, and thereby derive the optimal spacing interval.