Building Continuous Futures Series for Return and Volatility Analysis
Summary
The document compares ways to join futures contracts into a continuous price history, focusing on use in return based calculations such as volatility estimation. Its accepted answer recommends ratio adjustment: on a roll date, scale earlier prices by the ratio of the next contract’s settlement to the leading contract’s settlement, applying the adjustment backward through the history. This preserves the returns across contract rolls, unlike a simple unadjusted switch that can introduce price gaps.
The answer relates this construction to excess return commodity indices, which may spread a roll across multiple days rather than execute it all at once. A second response favors using nearby contracts and rolling at expiry, emphasizing consistency across analyses. The discussion does not establish one universal standard or compare the methods empirically. The choice depends on the intended analysis and roll convention; the detailed recommendation is specifically aimed at return based measures, and the document does not address all data handling choices, such as intraday prices or contract-specific liquidity.
Key ideas
- Ratio adjustment can preserve return continuity when stitching futures contracts for volatility analysis.
- On a roll date, the next contract’s settlement price is compared with the leading contract’s settlement price to derive the adjustment.
- The adjustment is applied backward to earlier prices, repeating across the contract history.
- Commodity benchmarks may spread rolls across several days instead of switching contracts in one day.
- A nearby-contract series rolled at expiry is another approach, with consistency across analyses as a guiding principle.
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Full text
# Is there a standard method for getting a continuous time series from futures data? # Is there a standard method for getting a continuous time series from futures data? I would like to be able to analyse futures prices as one continuous time series, so what kinds of methods exist for combining the prices for the various delivery dates into a single time series? I am assuming you would just use the front date for most of the time, and then combine this into some kind of weighted combination of the front and second month to simulate the roll. A quick Google search has shown that there seems to be a number of methods for doing this. Are any considered standard? In terms of my ultimate goal, I would like a single time series of prices (I can live with just using closing prices rather then OHLC data) so that I can estimate historical volatilities in the prices. ## Answer by David-Michael Lincke (score 9, accepted) https://quant.stackexchange.com/a/438 If your intention is to use the resulting continuous contract time series to perform return based calculation as would be the case with a volatility analysis then what you want to use is the ratio-adjustment method. If you are happy to roll on a single day this is trivially implemented by taking the ratio of next contract settlement price to leading contract settlement price on the roll day, then multiplying all historical leading contract prices by that ratio and repeating the process backwards along the contract history. This will result in a time series that exhibits the returns of an excess return commodity index. Note that benchmark commodity indices roll on a multi-day window, e.g. DJ-UBS or GSCI roll in 20% increments over 5 days. ## Answer by Val (score 1) https://quant.stackexchange.com/a/1413 I think the key here is consistency in your analysis. I would use (and do so for my research) the nearby contract(s) - the daily close and roll over on last day of expiry. From my experience this is the best way to approach analyses such as volatility and comparison between different time series...
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