> Perhaps this:http://jkalman.sourceforge.net/
thanks a lot for first feedback! after a first look at it I have come to the conclusion that this is an enormous task. I think the extensive help of the math gurus here in the group is very important. from my first observations I would estimate that we need an Unscented Kalman Filter as the JBT book data seem to be highly non-linear: http://en.wikipedia.org/wiki/Kalman_filter#Unscented_Kalman_filter what data sets do we have in JBT: * we have the book balance showing the situation on the bid and ask side * we have the price data showing us the price movements * we have some pretty cool indicators showing us the "velocity" in price and book balance movements Kalman filters seem to be highly used in navigation tasks. Here the concepts of speed and movement are incorporated into the Kalman filters to predict movements or to track objects. What do the math gurus say: is it possible to apply theses concepts from navigation to the movements of prices? The (linear) Kalman filter model calculates the next state from a state transition model F and a control-input model B and the process noise w and some other factors like an observation model H. My questions to our math gurus: * are these models relevant for an Unscented Kalman filter? * if they are: how will these models be built? I think the Kalman Filter stuff for JBT is really a very big task! Please give your help and support so that we can bring something to fly :-) -- You received this message because you are subscribed to the Google Groups "JBookTrader" group. To post to this group, send email to [email protected]. To unsubscribe from this group, send email to [email protected]. For more options, visit this group at http://groups.google.com/group/jbooktrader?hl=en.
