Cheddar Flow: Options Orders, Filters and Dark-Pool Activity

What is Cheddar Flow?

Cheddar Flow is an options-order-flow platform that organizes large and unusual transactions into a searchable feed. It also provides dark-pool activity, historical research and tools for narrowing the information through filters and alerts.

The core use is investigative: identify activity worth attention, examine the contracts behind it and compare that activity with price and relevant events. The feed shows transactions and analytical classifications; it does not reveal a trader’s complete portfolio or the reason for an order.

For users evaluating the product, the most important skill is understanding what each field establishes and what remains an inference. That distinction makes the feed more useful than simply following the largest highlighted print.

At a glance

Table of contents

Read the contract before the color

A useful sequence starts with the underlying symbol, strike, call or put, expiration, size and premium. These describe the traded instrument and the scale of the transaction. The same dollar amount can buy very different exposures across expirations and strikes.

Then inspect where the option traded relative to the bid and ask. Cheddar Flow’s official classification guide distinguishes executions at the ask, above the ask, in the market, at the bid and below it.

The guide makes an important point: interpreting the buyer or seller as the initiator is an assumption. An ask-side transaction can suggest aggressive buying, but buying may close an existing short option rather than open a new long position.

This is why a call label and a buy-side classification do not, by themselves, prove a new bullish bet. They are pieces of an interpretation that needs contract and portfolio context.

Sweeps, splits and large orders

Cheddar Flow distinguishes sweeps from split executions. A sweep can involve parts of an order executing across multiple exchanges; a split can involve executions within a single exchange. These labels help describe how liquidity was accessed.

Aggressive execution can indicate urgency, but it does not identify the trader or establish that the order contains information about the next price move. A time-sensitive hedge can also be executed aggressively.

When related prints appear, investigate whether they represent repeated interest or pieces of one larger execution. Counting every piece as a separate independent vote can exaggerate the apparent strength of the evidence.

A large premium total also needs a reference. An amount that is ordinary for a heavily traded index ETF may be unusual for a less active stock. Compare size with normal activity and liquidity, rather than ranking conviction by dollars alone.

What the highlights mean

The platform’s table-highlights documentation describes categories for large orders, unusual activity, highly unusual contracts and sizeable contract lots. These draw attention to particular combinations of transaction size, volume, open interest, volatility or expiration characteristics.

A highlight is a screening classification. It helps find an observation quickly; it does not resolve whether the trade is a hedge, a spread leg, a closing order or an outright position.

Short-dated, far-out-of-the-money contracts deserve particular care. Their low premium can make a large contract count look compelling, while their sensitivity to time and the required underlying move can make copying them unattractive. The economic structure matters more than the visual prominence.

Use advanced details to test the first impression

Cheddar Flow’s advanced-order-details view includes trade-side distribution, contract volume, open-interest changes and historical contract information such as price and implied volatility.

These views can help distinguish an isolated execution from sustained activity. A contract attracting repeated ask-side activity while its quoted price and IV change deserves a different investigation from a single large print with no follow-through.

However, open interest is a count of outstanding contracts, not a buyer-versus-seller tally. Every option trade has both sides. A subsequent rise in OI can help establish that outstanding contracts increased in aggregate, but it does not identify the owner or prove that one observed order created the entire change.

The help article also documents a different refresh cadence for advanced details than users might assume from a live feed. Check timestamps and current behavior for the particular view instead of treating every chart and historical field as simultaneous.

Build filters around a question

The advanced-filters guide explains that criteria can be combined to refine the feed. A good filter expresses a research question rather than merely reducing the number of rows.

Examples include looking at a short watchlist, restricting the expiration window or requiring a minimum activity scale appropriate to the instruments being studied. Add criteria gradually and keep a record of what each one excludes.

An excessively narrow filter can remove context, including related selling or another expiration that changes the interpretation. Conversely, a broad market-wide feed can encourage reacting to unrelated prints without a consistent decision process.

Saved layouts and sound preferences can make an established routine easier to follow. Alerts are most useful when the event triggering them has already been defined as relevant. More notifications do not necessarily produce more useful observations.

Dark-pool activity is a separate dataset

Cheddar Flow also organizes reported off-exchange stock transactions and the price areas at which activity accumulated. These are stock trades, whereas the options feed concerns derivatives.

A dark-pool price level is a historical concentration of reported activity, not a visible resting limit order. The report alone does not tell a user which side initiated the transaction or whether the buyer is still holding the position. Reporting delays and trade conditions can also separate the time a record appears from the time the economic trade occurred.

Use those areas as references for observing subsequent price behavior. An options-flow signal and a dark-pool concentration may add different context, but their agreement does not transform either into a guaranteed support or resistance level.

Getting started

1. Filter the options feed to a small universe. Begin with a familiar symbol or short watchlist, choose an expiration range and add a size criterion appropriate to those instruments. Keep enough activity visible to see related transactions.
2. Read one row in full. Check the strike, call or put, expiration, premium, size and bid/ask classification. Read a sweep or split label as execution information before assigning a directional interpretation.
3. Open advanced order details. Compare the contract’s volume, published open interest, price and IV history where available. Check that view’s timestamp, then look for related strikes or expirations in the feed.
4. Keep the useful settings. Save the layout and set sound preferences around the activity you intend to monitor. If you also open dark-pool research, review it as a separate stock-trade dataset rather than combining its quantities with the options feed.

For example, a large call execution after an earnings announcement may reflect a different thesis from one before the release. Recreating the original transaction at today’s quote can also produce a different payoff. The fact that someone traded the contract is the start of research, rather than a sufficient reason to copy it.

Access and who it suits

Check the official feature list and current plan terms for live access, historical depth, dark-pool tools, alerts and exports. Feature availability and limits should be confirmed for the subscription being considered.

Cheddar Flow is most useful for traders who want a structured way to inspect options activity and can distinguish execution evidence from inferred intent. A focused evaluation should ask whether its filters and detail views improve the quality of research on a specific watchlist. That is easier to judge than whether a stream of impressive-looking orders predicts every market move.

Official sources

• Cheddar Flow features
• Official help center
• Bought or sold: execution-side assumptions
• Sweeps and splits
• Data-table highlights
• Advanced order details
• Advanced filters
• Dark-pool levels