Futures & Market Research Glossary

Data revision is a change to a previously published value for the same observation or reference period. Revisions are common in economic and market datasets because an initial estimate may be released before all source information is available and then updated as additional reports, benchmark information, seasonal-adjustment inputs or improved methods become available. The exact revision process depends on the dataset. A revision therefore does not necessarily mean that the original release contained an error; it often reflects the trade-off between publishing timely information and waiting for a more complete estimate.

The historical record can change after publication

The crucial research distinction is between an observation date and a data vintage. The observation date identifies the period being measured; the vintage identifies the version of that observation that was available at a particular time. A value shown today for a past month or quarter may therefore differ from the figure available when that period was first reported. Routine revisions may incorporate late source data, while benchmark or methodological updates can alter longer stretches of a historical series.

This creates a subtle problem for historical analysis. If a researcher builds a strategy using today's revised database, the model may receive historical values that were unavailable when the simulated decision would have been made. Even when every observation carries a date earlier than the decision date, later vintages can therefore introduce look-ahead bias. When revisions could materially affect a variable, signal or decision rule, point-in-time research should use the vintages that were actually available at each historical decision date. Real-time archives can preserve successive versions of observations for precisely this type of reconstruction.

Revision is not the same as economic change

A revision changes the published measurement of an already referenced period; it does not by itself show that the underlying economy or market subsequently changed. This also separates Data Revision from a Structural Break, in which the underlying relationship, regime or data-generating process changes. The distinction matters because revised levels can alter derived quantities such as growth rates, rolling statistics, threshold crossings and model signals. An indicator reconstructed from final data can consequently appear cleaner, earlier or more predictive than it appeared in real time.

For reproducible research, the relevant question is therefore not only “What is the historical value now?” but also “What value was available when the decision was made?” That difference can determine whether a backtest represents a historically executable information set or a reconstruction informed by later data.

A deferred contract is a futures contract with a contract month later than the current front month. The designation is relative rather than permanent: futures markets can have several deferred contracts trading at the same time, so “deferred” does not necessarily mean only the immediately following maturity.

The same calendar contract can therefore change roles as time passes. A later-dated contract remains deferred while a nearer maturity occupies the front position, then can become the front month after the nearer traded maturities expire or otherwise cease to be the nearest traded contracts. Positions are also commonly rolled from an approaching front month into a deferred contract, and in many markets trading activity and open interest can migrate toward the later maturity before the earlier contract expires. That migration affects where liquidity is concentrated, but it does not itself define which contract is the front month.

A later price is not simply a later forecast

The price of a deferred contract is one point on the futures term structure. Its price relationship with a nearer maturity is the relationship traded through a calendar-spread position. In storable commodities, nearby-versus-deferred pricing can reflect financing, storage and other carrying costs, inventory availability and the economic value of holding physical supply. Financial futures have different carry mechanics. Expectations about future conditions can influence prices as well, but a deferred futures price should not be interpreted mechanically as a forecast of the spot price that will prevail when that contract matures.

Why the label matters in historical research

Deferred contract must also be distinguished from contract month. Contract month identifies a specific maturity; deferred contract describes that maturity's position relative to a nearer contract. A historical series described only as “deferred” therefore needs an explicit selection rule, such as the first maturity after the front month, a more distant relative maturity or a specified calendar contract. Without that rule, comparisons of deferred prices, spreads or liquidity can silently combine different underlying maturities as the curve rolls through time.

Delta is the first-order sensitivity of an option’s theoretical value to a small change in the price of its underlying instrument, with other pricing inputs held constant. In calculus notation it is commonly written as Δ = ∂V/∂S when the relevant underlying variable is a spot price S, or as ∂V/∂F when an option is valued relative to an underlying futures price F. A delta of 0.50 therefore means that, for a sufficiently small underlying-price move, the option’s theoretical value changes by approximately 0.50 price units for each 1-unit move in the underlying, before allowing for changes in volatility, time, interest rates, carry or other pricing inputs.

For standard vanilla options, a long call typically has positive delta between 0 and 1, while a long put typically has negative delta between -1 and 0. Traders also commonly quote delta on a 0–100 scale rather than 0–1, so “50 delta” usually means approximately 0.50. Position direction reverses the sign: a short call carries negative delta and a short put positive delta.

Delta is also used as a hedge ratio. If an option portfolio has a net delta equivalent to +250 units of its underlying, offsetting approximately 250 units of underlying exposure can make the position locally delta-neutral, subject to the product’s contract multiplier and quotation conventions. That hedge is not permanent. Gamma measures how delta changes as the underlying moves, so a position that is delta-neutral at one price can acquire meaningful directional exposure after the market moves and may need to be rebalanced.

Why delta is not a fixed property

Delta is generated within an option-pricing framework and depends on the market state and modeling conventions used to calculate it. Relevant inputs can include the underlying price, time to expiration, implied volatility, interest rates, dividends or carry, exercise style and the treatment of intraday time. Two competent analytics systems can therefore report somewhat different deltas for the same listed option when their inputs, models or timestamps differ. The distinction can become especially important for short-dated options and options near the strike, where delta may change rapidly as the underlying moves.

The probability shortcut has limits

Delta is sometimes used as a rough shorthand for the probability that an option will finish in the money. That interpretation can provide useful intuition under particular pricing assumptions, but delta is not generally identical to an expiration probability. In standard option models, the mathematical quantities used to calculate delta and risk-neutral exercise probabilities are closely related but distinct. Treating a “25 delta” option as having exactly a 25% chance of expiring in the money therefore creates false precision.

For research and risk management, delta is best understood as a conditional, first-order exposure measure: it describes the local slope of the option’s theoretical value at the current market and model state, not a fixed forecast of future profit, loss, exercise outcome or price direction.

Demand is the relationship between the quantities buyers are willing and able to purchase and the prices at which they would purchase them during a defined period, holding other relevant conditions constant. In physical commodity research, the word is also used more operationally for measured or estimated usage, consumption or market disappearance. Those meanings overlap, but they are not identical: demand is an economic relationship, quantity demanded is the amount associated with a particular price and set of conditions, and consumption is realized use.

Price movement versus a demand shift

A change in a commodity's own price, with other conditions unchanged, produces a movement along the demand relationship rather than a shift in demand itself. A demand shift means buyers would take a different quantity at the same price because some other determinant changed. In commodity markets that can result from economic activity, weather, technology, regulation, substitution between fuels or materials, or expectations about future conditions. Price elasticity summarizes how responsive quantity demanded is to a price change; markets with few near-term substitutes or rigid equipment constraints can show very different short-run responses from markets in which buyers can switch inputs quickly.

What reported demand can actually measure

For traders and researchers, the most important complication is that physical demand is not always observed directly. Some widely followed statistics are balance-derived proxies. In U.S. petroleum data, for example, the Energy Information Administration does not directly survey petroleum consumption; it uses “product supplied” as a proxy. Product supplied measures disappearance from the primary supply chain and is calculated from supply-and-disposition components including production, imports, inventory changes and exports. EIA notes that product supplied and consumption are not identical. This makes the measurement convention part of the meaning of the number, not a footnote.

Demand should therefore be read with its market, geography, unit, time interval and accounting convention attached. A higher price is not, by itself, evidence that demand strengthened, because a supply contraction can raise price even while quantity consumed falls. Likewise, a short-term change in an implied-demand or balance-derived series can reflect estimation, inventory or other accounting components as well as a genuine change in end-user behavior. Good analysis separates the observed quantity from the economic explanation.

The Disaggregated COT Report is a weekly Commodity Futures Trading Commission (CFTC) Commitments of Traders report family for physical commodity markets. It divides reportable open interest among four classifications—Producer/Merchant/Processor/User, Swap Dealers, Managed Money, and Other Reportables—providing finer participant segmentation than the Legacy COT Report’s commercial/non-commercial split. It is published in two report formats, Futures Only and Futures and Options Combined; those are formats of the same classification family, not separate COT families. Nonreportable Positions are shown separately rather than treated as a fifth reportable trader category.

What the report actually measures

The report generally describes each Tuesday’s open interest for markets where at least 20 traders hold positions at or above CFTC reporting levels. Current Disaggregated reports cover physical commodity markets grouped into agriculture, petroleum and products, natural gas and products, electricity, and metals and other; financial futures use the separate Traders in Financial Futures framework. COT reports are generally released Friday at 3:30 p.m. Eastern Time using the immediately preceding Tuesday’s data, although holidays and other disruptions can shift the schedule. In the combined format, option positions are converted to delta-adjusted futures-equivalent amounts and combined with futures positions.

Position structure also differs by category. Producer/Merchant/Processor/User positions are reported as long or short, while Swap Dealers, Managed Money, and Other Reportables also have a spreading column. Spreading is a computed amount of offsetting long and short positions: offsetting futures in different calendar months, or offsetting futures and options in the same or different calendar months in the combined report. Residual exposure remains in the long or short column, and inter-market spreads are not counted. The spreading column is therefore a reporting calculation, not a direct statement of a trader’s strategy or directional conviction.

Classification is not motive

The most important interpretation boundary is that the CFTC classifies traders, not individual trades. Classification is based principally on the trader’s predominant business purpose reported on Form 40 and reviewed by CFTC staff, who may use other information when assigning or revising a category. The CFTC does not know the specific reason for every position. A trader classified as Producer/Merchant/Processor/User therefore has all of its positions in that commodity included in that category whether a particular position is hedging or speculative, and a trader may have different classifications across different commodities. Category totals can also change when a trader is reclassified, so week-to-week moves are not necessarily pure measures of new buying or selling.

The historical series has an additional point-in-time limitation. The CFTC began publishing the Disaggregated COT Report on September 4, 2009, but later released historical data back to June 13, 2006. Because it did not maintain a historical record of large-trader classifications, more recent classifications were used to classify earlier positions—a process the CFTC calls backcasting. The agency notes that this reduces classification accuracy farther back in time, while still describing the series as reasonably representative over the period. For research, the practical distinction is important: pre-launch Disaggregated data are reconstructed history, not evidence that each historical category assignment had been known and recorded contemporaneously.