Quant Data: Options Flow, Net Drift and Exposure Analytics

What is Quant Data?

Quant Data is an options analytics platform that brings transaction flow, exposure models and equity-market activity into one research environment. The official website presents real-time and historical tools for monitoring US options, alongside customizable dashboards and mobile access.

Its appeal is the ability to move between several levels of evidence. A transaction feed shows what traded. Net Drift summarizes premium activity through time. Exposure maps organize Greek-weighted sensitivity by strike and expiration. Off-exchange equity data adds another view of underlying-market activity.

Those layers are most useful when they answer a defined question. Seeing a large options print is a starting point; understanding its contract, execution context and relationship to the wider chain is the actual research task.

At a glance

Table of contents

Consolidated flow versus the individual tape

An options order can appear as several executions rather than one neat transaction. Quant Data offers consolidated flow, grouping activity into categories such as blocks, splits and sweeps, as well as an unconsolidated trade-by-trade view.

The consolidated-flow documentation identifies fields including ticker, contract type, strike, expiration, premium, size, implied volatility and trade-side classification. Its API can also return the comprising executions behind a consolidated row.

Consolidation helps make a fragmented tape readable. However, a grouped row does not necessarily reveal the trader’s complete strategy. A call purchase can be one leg of a spread or a hedge against another position. A transaction near the ask may suggest aggressive execution, but it does not establish the participant’s identity or total directional exposure.

This is why premium, contract count and execution label should be read together. A high-premium trade in a distant expiration can have a different sensitivity from a smaller trade in a short-dated at-the-money option. The largest dollar number is not automatically the most relevant transaction for the next hour.

Net Drift: following premium through time

Net Drift organizes call and put premium over a selected slice of the options chain and time window. It helps turn a series of individual prints into a view of how activity develops during a session.

The important analytical choice is the filter. An all-expiration reading can combine long-dated positioning with same-day speculation. Restricting the expiration range can reveal a different pattern. Neither is inherently better; they describe different collections of trades.

There is also a distinction between premium flow and Greek exposure. Dollars paid for options do not directly equal shares of directional risk. Two contracts with equal premium can have different delta, gamma and time sensitivity. Call-versus-put activity also needs interpretation because both calls and puts can be bought or sold as part of larger structures.

For users working with the API, the documentation makes another useful distinction: Net Drift responses contain per-time-bucket values, rather than a precomputed running total. A cumulative curve requires accumulating those buckets. Keep the aggregation method consistent when comparing a dashboard chart with an exported calculation.

A productive use is to ask whether a change in premium activity coincides with a change in the underlying price, then inspect the contracts responsible. Divergence can generate a research question; it does not identify its cause on its own.

Exposure by strike and expiration

Quant Data’s exposure tools add a structural perspective to transaction flow. The Exposure By Strike documentation describes Greek-weighted values aggregated by expiration and strike, with delta, gamma, vanna and charm modes.

These sensitivities address different drivers:

• Delta measures sensitivity to an underlying-price move.
• Gamma describes how delta changes as the underlying moves.
• Vanna links delta sensitivity to a change in implied volatility.
• Charm concerns the change in delta as time passes, subject to the model’s time convention.

Do not compare the heights of bars until their units match. Quant Data’s documented representations include raw exposure and scaling per one-dollar or one-percent move. A change of scale can alter the displayed magnitude without representing a new position.

A strike map is also a snapshot. Exposure can change as price, volatility, time and the selected contract set change. Comparing two maps requires compatible timestamps and filters, rather than treating every numerical difference as newly initiated trading.

For gamma specifically, understand the assumptions used to assign position signs. Greek-weighted chain data should not automatically be described as a fully observed dealer book. The displayed number is useful within its methodology; it does not disclose every participant’s hedge or execution schedule.

Heatmaps and volatility context

The platform also presents exposure heatmaps, interval-based views and volatility tools. These can make concentrations easier to locate than a long contract table, especially when several expirations are relevant.

A useful sequence is to find a concentration in a map, isolate its expiration, then return to the underlying contracts or flow. That connects the visual pattern with the data producing it.

Volatility tools answer a separate question: how options are priced across the chain and through time. A bullish underlying thesis can coexist with expensive calls, while a decline in implied volatility can reduce an option’s value even when price moves in the expected direction. Keep a price scenario and an option-pricing scenario separate when evaluating an idea.

What Dark Flow does and does not show

Quant Data’s Dark Flow documentation describes off-exchange equity activity aggregated over time. The documented fields include notional value, share count, trade count and the underlying price.

This adds context about executed equity activity. It is different from the options tape, and different again from visible resting orders in an exchange order book.

A large off-exchange print has both a buyer and a seller. Its size alone does not establish that an institution is making a fresh bullish bet. Reporting context, timing and subsequent price behavior matter. Treat an unusually active price area as something to investigate, rather than converting every print into guaranteed support or resistance.

Getting started

Begin with one liquid ticker and build the dashboard around a single expiration horizon.

1. Open consolidated flow for the ticker. Set the expiration range, then use strike, premium or execution-side filters only as needed. Inspect the contract and any related executions behind a selected row.
2. Add Net Drift for the same slice. Match ticker, expirations and time window before comparing its premium activity with price. When using exported API buckets, distinguish interval values from a cumulative curve.
3. Choose an exposure view. Select the Greek and representation units, such as gamma per one-dollar move. Keep the expiration set consistent with the chain being researched.
4. Verify time and retain the setup. Check the exposure snapshot against the flow window and underlying chart. Record the filters and timestamps before adding another panel, such as Dark Flow, for a separate equity-activity question.

This workflow keeps the dashboard manageable. Adding more panels is useful only when they resolve an uncertainty in the existing process.

Access, audience and subscription checks

Quant Data is particularly relevant to traders who want broad options-flow research rather than a single level service. It can also suit analysts who need to compare transaction activity with exposure and volatility information.

Before subscribing, confirm instrument coverage, historical lookback, refresh behavior and professional versus nonprofessional market-data requirements. Mobile access can be useful for monitoring, but a compact screen changes how much contract detail is practical to inspect.

The company also offers a separate API product. Dashboard access should not be assumed to include API credentials, endpoint quotas or programmatic entitlements. Match the access method to the intended workflow before comparing subscription costs.

Official sources

• Quant Data platform overview
• Consolidated options flow documentation
• Net Drift documentation
• Exposure By Strike documentation
• Dark Flow documentation
• Quant Data API