It's all handled through the C++ api (or C# or Python as required). For pairs we can do market or resting orders (crossing the spread on the second leg when when the first resting order is filled). For triplets we just use market orders and pay the spread on all three legs.
The reason why I ask relates to non-display fees. We offer APIs on Lightspeed Trader, Sterling Trader Pro, Realtick and CBOE Silexx. Lightspeed Trader and Sterling Trader Pro are owned by Sterling Trader Tech (STT) and have been audited by the NYSE and SIP feeds and are required to report all open APIs with market data. To avoid non-display fees from the NYSE, that can run >$9000 per month, we turn off market data to the display. This would require your server/client to get market data from a third party. Lightspeed Trader uses a C++ Library for equity trading only. Realtick uses either C++ or C#.NET and is not subject to reporting open APIs yet, so the API can send market data and offers access to US listed Equities, Options and most liquid CME and ICE US Futures. Silexx is .net not C++, but is also not required to report open APIs yet. Both Realtick and Silexx are multi-broker platforms, which means your clients can custody at a number of clearing brokers and execute on one platfrom with your service. Bob
I don't recall reading anything about using for correlation estimation. It's an interesting idea. But the KF isn't really a prediction tool, as such. So it isn't like using a GARCH model to forecast volatility for option pricing, for example. What KF does is provide a way to estimate the true (unknown) state of a system when the measurements are noisy. So, for instance, it is used in satellite positioning systems and also in hand-held devices like smartphones: you want to know as quickly and accurately as possible what the true position of the phone is, given some noisy measurements from the gyroscope and accelerometer. KF can help with that. Whats the application to pairs trading? Suppose there is a relationship between two stock prices A and B, where B = A * beta. So you have noisy estimates of the true underlying relationship beta = B/A. KF tries to minimize the noise and maximize the accuracy of the estimate, so you can identify misalignments in the relative pricing of A and B.
1. Is it like expecting a reversal of beta to its average historical value? Do I understand this correctly? 2. Don't you have to select a pair of stocks based on their correlation that has meaningful standard deviation?