TorQonnect-Betfair

This is a simple example of a market data capture system using sports exchange (betting) data from betfair.com. This is installed on top of the base TorQ package, and includes a version of kdb+tick.

Prerequisites

To get this framework up and running in a unix environment you need two things:

1. A Windows or Unix environment with python installed.
2. The free 32 bit version of kdb+ set up and available from the command prompt as q.
3. openssl installed (should be present in Unix systems by default). You can download a Windows installer here. It is recommended that you add the loocation of the openssl executable to the PATH environment variable.
4. Python is required (should work fine with v2 or v3). The requests module is also required, more info on it here
5. A betfair.com account. If you don't already have an account you can get one here.

Set Up

• Download a zip of the latest version of TorQ

• Download a zip of this starter pack

• Unzip TorQ

• Unzip the starter pack over the top (this will replace some files)

• Add some account details to config/settings/requestor.q

  • fill in betfair.com username and password

    .requestor.username:"me";
    .requestor.password:"password";
    

  • Betfair also requires something called an Application Key. You can find more information on this and how to obtain it here. If you follow the instructions listed under How to Create An Application Key betfair will give you one. Make sure you are logged into your betfair account while you follow the instructions and the sessionToken will be automatically filled in, making you life alot easier. For the Application name you can choose anything you like.

  • Once you've followed the steps to create an application key, in the API-NG visualizer click getDeveloperAppKeys then Execute. This will return two keys, one with a delay and one without. You probably want the one without. Add this info to requestor.q.

    .requestor.appKey:"eQud5Jawxlq2CuLQ";
    

• Since this framework will collect data automatically it requires a non-interactive authorised login method. Details of how to set this up with Betfair are here. Follow the instructions in the sections Creating a Self Signed Certificate and Linking the Certificate to Your Betfair Account. This will generate 3 files:

  • client-2048.key
  • client-2048.csr
  • client-2048.crt
  • Copy all 3 of these files into the config/certificates folder.

• Finally we need to add some events to collect data on! This configuration is held in the config/requestor.csv file. There are five columns in this config file:

• marketId The unique identifier for the market. MarketId's are prefixed with '1.' or '2.'
• market Free text field used to identify the market in the config
• start Timestamp to indicate when to start polling for data
• end Timestamp to indicate when to stop polling for data
• interval Period of time between polls

• This file will be loaded when the requestor process starts. Additional markets can be added to config when the process is live using the .requestor.addSubscription function.

  .requestor.addSubscription["Grexit";`1.117087478;0Wp;0D00:00:10]
  

• The best way to find the marketId for a particular event is using the betfair Betting API visualiser. Under listMarketCatalogue you can search through the available markets by name, volume traded, sport etc. Again if you're logged in before you click this the Session Token will autofill, and the appKey is the same as the one you filled in above.

• Once you have a few markets setup to collect data on, all that's left to do is run the startup script to start up the TorQ stack and start collecting data!

  sh start_torq_betfair.sh
  

or double-click on the start_torq_betfair.bat file if you are running on Windows.

Using the API

• Once you have some data in the system there are some basic queries that can be run on the gateway to retrieve data.

  • You can run to get a list of available markets for a given date:

    getActiveMarkets[date]
    
    

  eg. getActiveMarkets[2000.01.01] getActiveMarkets[.z.d] ```

  • To return information about the mid price run (pivot will return the different outcomes as columns instead of rows):

  getMid[marketID;pivot]

  eg. getMid[1.117087478;0b] getMid[1.117087478;1b] ```

  • To return the implied odds based on trades matched, and the volume of trades matched, run (bucket is in minutes):

    getOdds[marketID;bucket;pivot]
    
    

  eg. getOdds[1.117087478;10;1b] getOdds[1.117087478;1;0b] ```

  • To return the volume weighted average price you would have to pay if trading a given volume run:

       getVwap[marketID;size]
  
       eg.
       getVwap[`1.117087478;1]
       getVwap[`1.117087478;1000]
       ```