What you will learn
- Continuous-series distortions
- Roll schedule
- Data synchronization
- Stress widening basis
Continuous-series distortions
Continuous series join contracts using a roll rule and possibly adjustments. These transformations can create a useful research display while altering historical price levels or returns. Preserve the raw contracts for execution-sensitive analysis.
Roll schedule
A roll schedule can be based on dates, volume or another criterion. It must be known at the relevant time. A retrospective rule using later information about liquidity can bias the series used in a strategy test.
Data synchronization
Synchronize both legs and the spot reference where used. A relationship calculated from different observation times can reflect market movement between samples rather than a true contemporaneous spread.
Stress widening basis
Stress widening basis and reduced liquidity, including the cost of closing both legs. Report assumptions that cannot be validated from the available data. A single smooth continuous chart is not enough to establish realistic spread execution.
Worked example
A back-adjusted series removes a five-point contract gap visually. That adjustment does not mean an actual roll occurred at zero cost or that the historical absolute prices remained tradable.
Try it yourself
Describe a reproducible dataset for a spread study, including raw contracts, roll decisions and synchronized observations.
Show the worked solution
Store expiry-specific quotes, timestamps, units and liquidity fields, plus the rule and decision date for each roll. Keep transformed series separate and document costs and missing observations.
Apply this to your course project
Build a two-expiry scenario sheet with carry assumptions and roll-cost sensitivity.
Keep the calculation inputs, assumptions and decisions with your work. Practical exercises are self-reviewed; the scored knowledge checks assess the questions shown, not an independent certification of practical competence.