Nicolas32

I'm not BlueHorseshoe but I try to bring my own answer. Price moves because there is an imbalance between: - demand of liquidity (market orders) - supply of liquidity (limit orders). For instance, if there is more BUY market orders coming in the market than the numbers of limit SELL orders waiting in first level of the DOM, all this first level of the DOM will be "eaten", and price will increase by one tick. So liquidity is key. Because it is the basis of price movement. Just my opinion. Nicolas

BlueHorseshoe, Your code here-above is supposed to calculate what? The "optimal" ratio between the two price series? Something different? Kalman filter is a methodology to calculate "adaptative" things. There is not one unique formula. It depends on what we try to do. Let's A and B be the 2 instruments. In pairs trading, typically: - cointegration is checked (Dickey-Fuller or other) on the long term (typically > 1 year). - hedge ratio (let's call it gamma) is calculated on the in-sample data by linear regression - then, on out-of-sample data, we enter "long A short B with appropriate position sizing" each time the spread A-gamma*B departs too much from its mean. For this "basic" approach, Kalman filter is not really useful. It may become useful if you want to calculate a shorter-term gamma, in order to have a more "dynamic" and short-term spread. Then, we may consider these 2 equations { B[t] (observed) = gamma[t] (to be assessed by KF) * A[t] (observed) + noise (unknown) { gamma[t] = gamma[t-1] + noise (unknown) We have the 2 typical equations (state equation and measurement equation) on which we can the KF methodology. There is a research paper on intraday pairs trading which implements the above KF approach (as well as other methodologies) to assess a short-term gamma: Dunis and al Statistical Arbitrage and High-Frequency Data with an Application to Eurostoxx 50 Equities March 2010 http://www.ljmu.ac.uk/Images_Everyone/Jozef_1st(1).pdf What is above is only my understanding so... may be wrong! Nicolas Nicolas