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Building Horizon-Matched Futures Series for Oil Forecasting

Article Quant Q&A · Author: Zachary Blumenfeld

Summary

The document discusses how to assemble futures data for regressions that forecast monthly Brent spot prices at several future horizons. Its model uses the futures quote available at time t for a maturity matching the forecast horizon, alongside other economic or financial predictors, to explain the later spot price. The central data issue is that exchange-traded contracts have specific expiries, while commonly sold continuous series are constructed by rolling among contracts and are not themselves individual tradable contracts.

The accepted answer recommends obtaining historical prices for each relevant expiry and selecting, at each observation date, the contract whose maturity corresponds to the model’s horizon. Continuous series may be available from providers for some horizons, but their roll conventions and suitability should be checked. The note does not compare splicing or adjustment methods, identify a free data source, or provide a complete alignment procedure. Researchers must still define maturity matching, sampling dates, predictor construction, and treatment of contract rolls to avoid introducing inconsistencies into regression inputs.

Key ideas

  • A horizon-based forecasting regression needs futures prices with maturities that match each forecast horizon.
  • Exchange-traded futures are dated contracts that expire, whereas continuous series are provider-constructed roll series.
  • The proposed approach is to collect histories for individual expiries and map each observation to the relevant maturity.
  • Provider series may exist for some horizons, but their construction should be checked for model suitability.
  • The document does not prescribe a roll-adjustment method or a specific data source.

Tags

Full text
# How to retrieve and format futures data for use in regression/time series models?


# How to retrieve and format futures data for use in regression/time series models?












I need to form a predictive time series model for monthly Brent crude oil spot price. I am looking to form 1-12 month ahead forecast horizons. There is a bounty of previous literature which uses futures prices in a regression framework for this purpose. See Crude Oil Price Forecasting Techniques: a Comprehensive Review of Literature and the references cited therein in for examples, I can provide more citations if necessary.

In general the models are of the form. $$E[P_{t+h}]=F_{t,t+h}+x_{t,h}'\beta$$

where $E[P_{t+h}]$ is the expected value of Brent crude oil spot price $h$ months in the future at time $t$, $F_{t,t+h}$ is the price of the oil futures contract at time $t$ with maturity $t+h$, and $x_{t,h}$ is a vector of other economic and financial variables (i.e. proxies for business cycles and or risk premia, etc). This would call for a regression model of the form $$ P_{t+h}=F_{t,t+h} + x_{t,h}'\beta+\varepsilon_{t,h} $$ Where $\varepsilon_{t,h}$ is the error term.

I understand the basic concept behind futures contracts, but am struggling with how to obtain a monthly time series of future prices which I can use in the above equation to form a regression model. That is to say, futures contracts are brought into creation and traded in irregular time intervals, often with more than one outstanding contracting existing at a time. Unlike spot prices, it would seem that obtaining a monthly time series out of futures data would be an involved process, assuming that such futures data was even available.

### What I have Done So far

- I have researched some methods to form continuous contract series (eg. http://www.premiumdata.net/support/futurescontinuous.php). There are apparently multiple different ways to do "splicing". I would really like to know what methods are preferable for the purposes of regression and if there already exists freely available continuous contract data. Where do I go to look?

- I have gone onto Quandl and found some futures data with titles like. ICE Brent Crude Oil Futures #11 (B11) - Unadjusted Prices, Roll on First of Month, Continuous Contract History. This sounds kind of like what I want, but I honestly do not know for sure or if it would be appropriate for my model.

All in all, I am just looking for advise on where to start and how to go about doing this, things to watch out for, if there is any free resources/data already available, exc. Any advise would be greatly appreciated.

## Answer by SRKX (score 2, accepted)

https://quant.stackexchange.com/a/21439

You're getting confused because data providers will actually give you "continuous" contracts which are not the ones traded.

When you get in a future contract trade, you buy a future contract which has an expiry date. After that date, the contract does not exist anymore, money is exchanged against underlying for those who still have a position. When you do speculative trading, you just don't want to take delivery of thousand of oil barrels, so you basically sell the front-month contract relatively shortly before expiry and buy the following one.

In your case, $F_{t,t+h}$ is the time series of a continous contract $h$ month ahead. You can probably find this for some values of $h$ is some provider, but not everywhere. So what you have to do is basically find and download the whole history of prices for all future contracts $F_{t,T}$ and then find to which value $T$ the $t+h$ of your model corresponds.

So, you will need to download a time series for each future contract that could be concerned by you analysis. It would be good if you added the regression formula you're trying to get to in the question.

Shown in full with attribution under the source's licence. Licence: CC BY-SA 4.0 (Stack Exchange)

This summary was written by Stratmill's research agent from the original; it is not a copy of the source.