Back Adjusted Continuous Contract Data from Quandl

I finally got around to programming an easy Python down loader for CME data from Quandl.  I promised this in my last book, but haven’t got that many requests.   On the Ultimate Algorithmic Trading System…. page I have provided some data going back to early 2008 on several markers.  This is a work in progress.  I also wrote a back adjuster that rolls when the Open Interest + Volume is greater in the next contract and adjusts the data retroactively (Panama process) by the discount on the roll date.  As I state on the web page this data is not all that great even though it looks like it comes directly from CME.   I do fill in gaps and try to fix glaring errors so take it for what it is.  Its good data for preliminary testing, but to finalize an algorithm or to trade by I would definitely go the “paid” route.  Although the later data looks pretty good.

Before downloading the data I would sign up for Quandl and get an API key.  You will be amazed at the amount of data they make available – free and paid subscriptions.



6 thoughts on “Back Adjusted Continuous Contract Data from Quandl”

  1. I subscribe to Quandl for data. Would you agree that the most appropriate futures continuous contract data for simulating historical trades in doaars would be 1st contract, backwards panama, open interest switch? Thank you.

    1. Hi, again Richard. Quandl no longer offers the individual CME data contracts that I was using to link the contracts together. They do offer a database that includes all of the front months in a single file. They also have the second month in files as well. From this data, you can splice together an adjusted continuous contract. The backwards panama with OI triggers is a great algorithm to use. Some prefer a volume and OI trigger. But I think you can get a robust database using just OI.

    1. Hello Jirong,

      Quandl uses the number following the futures name to show which “month out” the data refers to.
      For example #1 for SP500 is the front month contract and it will flip when the contract expires [Mar, June, Sep, Dec]
      Prior to expiration of #1 the #2 contract will experience higher volume and or open interest – when this occurs you would switch to #2 before #1 expires
      Once contract #1 expires it #2 is implemented and #3 becomes #2 and so on.
      Normally you would trade #1 in the SP
      Contract #1
      March Contract Dec 1x, Jan, Feb, March 1x
      June Contract March 1x, Apr, May, June 1x
      Sept Contract June1x, July, Aug, Sept 1x
      Dec Contract Sept 1x, Oct, Nov, Dec 1x
      Contract #2
      June Contract Mar 1x +1, Contract #1 expiration date [March] – about 5 trading days
      Sept Contract June 1x +1, Contract #1 expiration date [June]
      Dec Contract Sept 1x+ 1, Contract #1 expiration date [Sept]
      Mar Contract Dec 1x +1, Contract #1 expriration date[Dec’

      1. Hi George

        Thanks for your reply. Cant believe that I missed it (no email notification or I might have missed it).

        When constructing the continuous futures data, do you account for the fact that it\’s possible that 1st 2 contracts may not be the most liquid? If we go down the depth (beyond second contract), I would imagine that the panama stitching is going to be a nightmare.


        1. Hi Jirong,

          The stitching is a nightmare for sure. You absolutely correct sometimes you have to dig down to 4 levels of contracts to get the data you need – high volume and high opInt. My code goes 4 levels but I am still disappointed with the quality of the QUANDL free data. It was great when the CME posted their historical data for free in individual contract format. I wished they would publish it once every six months – even if it was a few months old. One day maybe!

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