"Trading is statistics and time series analysis." This blog details my progress in developing a systematic trading system for use on the futures and forex markets, with discussion of the various indicators and other inputs used in the creation of the system. Also discussed are some of the issues/problems encountered during this development process. Within the blog posts there are links to other web pages that are/have been useful to me.
In the Spring of 2012 and again in the Spring of 2019 I posted a series of posts about the Kalman Filter , which readers can access via the blog archive on the right. In both cases I eventually gave up those particular lines of investigation because of disappointing results. This post is the first in a new series about using the Kalman Filter for sensor fusion , which I had known of before, but due to the paucity of clear information about this online I had never really investigated. However, my recent dis
The first step in this process is to determine the measurement noise covariance or, in Kalman Filter terms, the "R" covariance matrix. To do this, I have used the average of two of the outputs from the above mentioned functions to create a new cycle and similarly used two extracted trends (price minus these cycles) averaged to get a new trend. The new cycle and new trend are simply added to each other to create a new price series which is almost identical to the original price series. The screenshot below s