# How Does VPIN Differentiate between Informed and Uninformed Trading Flow? ▴ Question

**Published:** 2025-08-15
**Categories:** Question

---

![A metallic blade signifies high-fidelity execution and smart order routing, piercing a complex Prime RFQ orb. Within, market microstructure, algorithmic trading, and liquidity pools are visualized](https://options.greeks.live/wp-content/uploads/2025/07/institutional-digital-asset-derivatives-rfq-prime-os-execution-precision.jpg)

![A sleek, multi-component device with a prominent lens, embodying a sophisticated RFQ workflow engine. Its modular design signifies integrated liquidity pools and dynamic price discovery for institutional digital asset derivatives](https://options.greeks.live/wp-content/uploads/2025/07/institutional-digital-asset-derivatives-rfq-engine-microstructure-2.jpg)

## Concept

The core challenge in modern [market microstructure](https://prime.greeks.live/area/market-microstructure/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite) is discerning the intent behind trading volume. Every transaction leaves a footprint, but the aggregate flow of data often obscures the crucial distinction between routine, uninformed liquidity provision and strategic, [informed trading](https://prime.greeks.live/question/what-are-the-primary-quantitative-methods-for-detecting-informed-trading-in-anonymous-venues/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite). Uninformed flow, characteristic of market makers or passive index funds, is typically balanced between buys and sells over time.

Informed flow, conversely, originates from participants possessing private information about an asset’s future value, leading to persistent, one-sided pressure as they seek to capitalize on this knowledge before it becomes public. The Volume-Synchronized Probability of Informed Trading ([VPIN](https://prime.greeks.live/area/vpin/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite)) metric is a system designed to penetrate this data fog, offering a real-time estimate of this informational asymmetry.

VPIN operates on a fundamentally different temporal framework than traditional market indicators. Instead of sampling data at fixed time intervals (e.g. every minute or hour), it samples data in volume-time. This means it analyzes market activity in discrete parcels of constant volume, known as “volume buckets.” The intuition is that information dissemination is not governed by the clock, but by trading activity itself.

A fixed amount of volume, therefore, represents a more consistent unit of information flow than a fixed unit of time, which might contain frantic activity or virtually none at all. By synchronizing its analysis with the volume clock, VPIN attunes itself to the actual rhythm of information absorption in the market, providing a more sensitive measure of [order flow](https://prime.greeks.live/area/order-flow/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite) dynamics.

> VPIN provides a real-time estimate of information asymmetry by analyzing trade data in volume-time, distinguishing between the balanced nature of uninformed trading and the persistent, one-sided pressure of informed flow.

This approach allows the system to quantify what is known as “[order flow toxicity](https://prime.greeks.live/area/order-flow-toxicity/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite).” A market becomes toxic when the proportion of informed traders becomes dangerously high, creating significant [adverse selection risk](https://prime.greeks.live/area/adverse-selection-risk/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite) for liquidity providers. Market makers, who profit from capturing the bid-ask spread on balanced order flow, face escalating losses when trading against a stream of informed participants. If they unknowingly provide liquidity at a loss, they are forced to widen their spreads or withdraw from the market altogether. This withdrawal of liquidity can create a feedback loop, where the remaining order flow becomes even more concentrated with informed traders, leading to sharp increases in volatility and, in extreme cases, market dislocations like flash crashes.

VPIN is engineered to detect the buildup of this toxicity before it reaches a critical point. It achieves this by measuring the degree of [order imbalance](https://prime.greeks.live/area/order-imbalance/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite) within each successive [volume bucket](https://prime.greeks.live/question/did-the-double-volume-caps-succeed-in-moving-trading-volume-to-lit-markets/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite), providing a direct signal of the directional pressure being exerted by participants with superior information.

![A precision instrument probes a speckled surface, visualizing market microstructure and liquidity pool dynamics within a dark pool. This depicts RFQ protocol execution, emphasizing price discovery for digital asset derivatives](https://options.greeks.live/wp-content/uploads/2025/07/institutional-digital-asset-derivatives-rfq-protocol-execution-flow.jpg)

![A central, symmetrical, multi-faceted mechanism with four radiating arms, crafted from polished metallic and translucent blue-green components, represents an institutional-grade RFQ protocol engine. Its intricate design signifies multi-leg spread algorithmic execution for liquidity aggregation, ensuring atomic settlement within crypto derivatives OS market microstructure for prime brokerage clients](https://options.greeks.live/wp-content/uploads/2025/07/precision-rfq-engine-for-crypto-derivatives-liquidity-aggregation.jpg)

## Strategy

The strategic implementation of VPIN hinges on its unique four-stage computational procedure, which transforms raw tick-data into a continuous measure of order flow imbalance. This process is designed to systematically isolate the signature of informed trading from the background noise of market activity. The methodology moves beyond simple volume metrics to capture the directional intensity of trading, which is the hallmark of information-driven behavior.

![A sophisticated mechanism depicting the high-fidelity execution of institutional digital asset derivatives. It visualizes RFQ protocol efficiency, real-time liquidity aggregation, and atomic settlement within a prime brokerage framework, optimizing market microstructure for multi-leg spreads](https://options.greeks.live/wp-content/uploads/2025/07/institutional-digital-asset-rfq-protocol-execution-liquidity-aggregation-system.jpg)

## The VPIN Calculation Protocol

The VPIN metric is not a single calculation but a rolling analysis updated with each new parcel of market volume. The procedure is methodical, ensuring that the final output is a standardized and comparable measure of [flow toxicity](https://prime.greeks.live/area/flow-toxicity/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite) across different time periods and assets.

- 
**Data Aggregation into Time Bars** ▴ The initial step involves aggregating high-frequency tick data into standardized time bars, typically one minute in duration. For each bar, the [total volume](https://prime.greeks.live/question/did-the-double-volume-caps-succeed-in-moving-trading-volume-to-lit-markets/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite) is summed, and the price change is calculated. This step smooths the raw data and prepares it for classification.

- 
**Bulk Classification of Volume** ▴ A core innovation of the VPIN methodology is its approach to classifying volume. Instead of using traditional tick-rule algorithms (like Lee-Ready), which can be problematic in high-frequency settings, VPIN employs a probabilistic “bulk classification” method. The volume in each time bar is classified as buy- or sell-initiated based on the associated price change. A normal distribution is used to assign the volume, where positive price changes lead to a higher proportion of buy-classified volume and negative changes result in more sell-classified volume.

- 
**Volume Bucket Formation** ▴ This is the crucial transition from clock-time to volume-time. The classified time bars are sequentially aggregated into “volume buckets” of a constant size. For example, if the average daily volume of a stock is 50 million shares and the chosen number of buckets per day is 50, then each bucket will have a size of 1 million shares. This ensures that each data point for the final VPIN calculation represents an equal amount of trading activity.

- 
**Order Imbalance and VPIN Calculation** ▴ For each completed volume bucket, the total buy- and sell-classified volumes are summed. The absolute difference between these two sums is the order imbalance for that bucket. The VPIN metric is then calculated as a moving average of these order imbalances over a specified number of recent buckets (the sample length). The formula is essentially the sum of absolute order imbalances divided by the total volume in the sample window.

![Two diagonal cylindrical elements. The smooth upper mint-green pipe signifies optimized RFQ protocols and private quotation streams](https://options.greeks.live/wp-content/uploads/2025/07/institutional-digital-asset-derivatives-rfq-execution-microstructure-optimization-1.jpg)

## Architectural Comparison VPIN Vs PIN

VPIN was developed as an evolution of the earlier Probability of Informed Trading (PIN) model. While both aim to measure information asymmetry, their strategic architecture and practical applicability differ significantly, particularly in modern, high-speed markets.

| Feature | PIN (Probability of Informed Trading) | VPIN (Volume-Synchronized Probability of Informed Trading) |
| --- | --- | --- |
| Time Framework | Clock-Time ▴ Analyzes the number of buy and sell orders over fixed time intervals (e.g. a trading day). | Volume-Time ▴ Analyzes order flow within constant volume buckets, synchronizing with market activity. |
| Data Input | Requires the number of buy and sell trades per day. | Uses high-frequency tick data (price, volume, time) as its input. |
| Estimation Method | Relies on complex numerical optimization (maximum likelihood estimation) of a structural market microstructure model. This can be computationally intensive and prone to errors. | Calculated directly from trade data without the need for iterative optimization, making it suitable for real-time application. |
| Output Frequency | Typically produces a single value for a given period (e.g. daily or weekly), capturing risk at a low frequency. | Generates a continuous, high-frequency stream of values, allowing for intraday risk monitoring. |
| Core Concept | Measures the probability of an information event occurring on a given day. | Measures “order flow toxicity,” a broader concept of adverse selection risk relevant to high-frequency liquidity provision. |

![An abstract digital interface features a dark circular screen with two luminous dots, one teal and one grey, symbolizing active and pending private quotation statuses within an RFQ protocol. Below, sharp parallel lines in black, beige, and grey delineate distinct liquidity pools and execution pathways for multi-leg spread strategies, reflecting market microstructure and high-fidelity execution for institutional grade digital asset derivatives](https://options.greeks.live/wp-content/uploads/2025/08/institutional-digital-asset-derivatives-rfq-protocol-displaying-multi-leg-execution-status-and-optimal-liquidity-pathways.jpg)

## Interpreting the VPIN Signal

A rising VPIN level signals an increasing probability that trading is being driven by informed participants. As the metric climbs, it indicates that order flow is becoming persistently imbalanced, a condition that precedes periods of high volatility and liquidity dislocation. A VPIN value of 0.5, for example, would indicate that the order imbalance is equivalent to half of the total volume traded, a highly toxic environment for [market makers](https://prime.greeks.live/question/how-does-market-fragmentation-affect-adverse-selection-for-market-makers/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite). The signal is not a direct prediction of price direction but rather a warning about market stability.

It serves as a lead indicator of fragility, alerting traders and risk managers to the potential for a sudden evaporation of liquidity. This allows for proactive adjustments to trading strategies, such as reducing exposure, widening spreads, or pausing aggressive algorithms, before a crisis materializes.

![Interconnected, precisely engineered modules, resembling Prime RFQ components, illustrate an RFQ protocol for digital asset derivatives. The diagonal conduit signifies atomic settlement within a dark pool environment, ensuring high-fidelity execution and capital efficiency](https://options.greeks.live/wp-content/uploads/2025/07/institutional-digital-asset-derivatives-rfq-execution-protocol-engine.jpg)

![A futuristic, metallic structure with reflective surfaces and a central optical mechanism, symbolizing a robust Prime RFQ for institutional digital asset derivatives. It enables high-fidelity execution of RFQ protocols, optimizing price discovery and liquidity aggregation across diverse liquidity pools with minimal slippage](https://options.greeks.live/wp-content/uploads/2025/07/precision-engineered-platform-for-institutional-digital-asset-derivatives-rfq-protocol-optimized-execution-management-system-with-robust-liquidity-sourcing.jpg)

## Execution

The operationalization of the VPIN metric transforms it from a theoretical construct into a practical risk management and execution tool. Its implementation within an institutional trading framework requires a robust data processing pipeline and a clear protocol for interpreting and acting upon its signals. The true value of VPIN is realized when it is integrated into real-time systems that can dynamically adjust to changing market conditions based on its output.

![Sleek, intersecting planes, one teal, converge at a reflective central module. This visualizes an institutional digital asset derivatives Prime RFQ, enabling RFQ price discovery across liquidity pools](https://options.greeks.live/wp-content/uploads/2025/07/prime-os-digital-asset-derivatives-rfq-engine-optimizing-institutional-liquidity-aggregation-and-best-execution.jpg)

## Quantitative Modeling and Data Analysis

The calculation of VPIN is a sequential process that can be broken down into discrete steps. Understanding this workflow is essential for its correct implementation. The process begins with raw [trade data](https://prime.greeks.live/area/trade-data/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite) and culminates in a single, interpretable metric representing order flow toxicity.

Consider a simplified example using hypothetical trade data for an instrument. Assume the average daily volume is 1,000,000 shares and we decide to use 50 buckets per day, making the Volume Bucket Size (VBS) 20,000 shares. The sample length for the rolling VPIN calculation will also be 50 buckets.

| Time Bar (1-Min) | Aggregated Volume | Price Change (ΔP) | Buy Volume (Probabilistic) | Sell Volume (Probabilistic) | Bucket Assignment |
| --- | --- | --- | --- | --- | --- |
| 09:30 | 15,000 | +0.02 | 12,000 | 3,000 | Bucket 1 |
| 09:31 | 10,000 | -0.01 | 4,000 | 6,000 | Bucket 1 (5,000), Bucket 2 (5,000) |
| 09:32 | 18,000 | +0.03 | 16,200 | 1,800 | Bucket 2 (15,000), Bucket 3 (3,000) |
| 09:33 | 22,000 | -0.02 | 6,600 | 15,400 | Bucket 3 (17,000), Bucket 4 (5,000) |

The process continues until 50 buckets are filled. At that point, the first VPIN value is calculated:

- 
**For each bucket (τ)** ▴ Calculate Order Imbalance OI(τ) = |Total Buy Volume(τ) – Total Sell Volume(τ)|.

- 
**VPIN Calculation** ▴ The VPIN is the sum of the order imbalances over the sample length (n=50) divided by the total volume over that period. The formula is:

VPIN = (Σ |OI(τ)| for τ=1 to 50) / (n VBS)

Once bucket #51 is filled, bucket #1 is dropped from the calculation window, and a new VPIN value is computed using buckets #2 through #51. This rolling calculation provides a continuous, real-time measure of market toxicity.

![A macro view reveals a robust metallic component, signifying a critical interface within a Prime RFQ. This secure mechanism facilitates precise RFQ protocol execution, enabling atomic settlement for institutional-grade digital asset derivatives, embodying high-fidelity execution](https://options.greeks.live/wp-content/uploads/2025/07/core-secure-institutional-digital-asset-derivatives-rfq-trade-system-element.jpg)

## Predictive Scenario Analysis a Flash Crash Precursor

To illustrate the practical utility of VPIN, consider a hypothetical scenario leading up to a mini-[flash crash](https://prime.greeks.live/area/flash-crash/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite) in a highly liquid futures contract. At 10:00 AM, the market is stable, with VPIN hovering around a normal level of 0.20, indicating balanced, two-sided flow. A hedge fund, possessing non-public information about a large impending order, begins to aggressively sell contracts. Initially, this selling is absorbed by high-frequency market makers.

However, the selling pressure is relentless and one-sided. By 10:15 AM, the VPIN metric starts to climb, reaching 0.35. The system is detecting that the order flow is becoming increasingly imbalanced; sell-side volume is consistently overwhelming buy-side volume within each successive 20,000-contract volume bucket. An automated alert is triggered on the risk management dashboard.

The head of execution, seeing the rising VPIN, instructs the [algorithmic trading](https://prime.greeks.live/area/algorithmic-trading/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite) desk to reduce the aggression of their liquidity-providing strategies and to widen the spreads on their quotes. By 10:25 AM, VPIN has spiked to 0.48. The persistent selling has exhausted the standing buy orders in the limit order book. Market makers, facing mounting losses against the informed flow, begin to pull their quotes en masse.

This withdrawal of liquidity creates a vacuum. A subsequent large market sell order hits the thin book, causing the price to cascade downwards rapidly ▴ a mini-flash crash. However, the trading desk that heeded the VPIN warning had already reduced its exposure, mitigating potential losses. The VPIN metric did not predict the direction of the price move, but it provided a critical, advance warning of the deteriorating liquidity conditions that made the crash possible.

![A sleek, abstract system interface with a central spherical lens representing real-time Price Discovery and Implied Volatility analysis for institutional Digital Asset Derivatives. Its precise contours signify High-Fidelity Execution and robust RFQ protocol orchestration, managing latent liquidity and minimizing slippage for optimized Alpha Generation](https://options.greeks.live/wp-content/uploads/2025/07/high-fidelity-institutional-digital-asset-derivatives-execution-via-optimized-rfq-protocols-enhancing-market-microstructure.jpg)

## System Integration and Technological Architecture

Integrating VPIN into an institutional trading system requires a high-throughput architecture capable of processing every trade in real-time. The core components include:

- 
**Data Feed Handler** ▴ A low-latency connection to the exchange’s market data feed (e.g. via FIX protocol) is necessary to capture every tick.

- 
**VPIN Calculation Engine** ▴ A dedicated server or cloud instance runs the VPIN algorithm. This engine consumes the raw tick data, performs the time bar aggregation, bulk classification, and volume bucketing, and continuously computes the rolling VPIN value.

- 
**Alerting and Visualization Layer** ▴ The output from the calculation engine is fed into a monitoring dashboard. This system visualizes the VPIN metric over time and is configured with predefined thresholds. When VPIN crosses a certain level (e.g. 0.40), it can trigger automated alerts via email, SMS, or on-screen notifications.

- 
**EMS/OMS Integration** ▴ For advanced execution control, the VPIN signal can be piped directly into the Execution Management System (EMS) or Order Management System (OMS). This allows for the creation of automated rules, such as “If VPIN > 0.45, then switch all active algorithms to passive mode” or “If VPIN > 0.50, then pause all new order deployments.” This closes the loop from signal detection to automated risk mitigation, providing a systemic defense against liquidity crises.

![A sleek, circular, metallic-toned device features a central, highly reflective spherical element, symbolizing dynamic price discovery and implied volatility for Bitcoin options. This private quotation interface within a Prime RFQ platform enables high-fidelity execution of multi-leg spreads via RFQ protocols, minimizing information leakage and slippage](https://options.greeks.live/wp-content/uploads/2025/07/prime-os-institutional-digital-asset-derivatives-rfq-execution-hub.jpg)

## References

- Abad, David, and José Yagüe. “From PIN to VPIN ▴ An introduction to order flow toxicity.” The Spanish Review of Financial Economics, vol. 10, no. 2, 2012, pp. 74-83.

- Bambade, Antoine. “A New Way to Compute the Probability of Informed Trading.” Journal of Mathematical Finance, vol. 9, no. 4, 2019, pp. 637-666.

- Easley, David, Marcos M. López de Prado, and Maureen O’Hara. “Flow Toxicity and Liquidity in a High-Frequency World.” The Review of Financial Studies, vol. 25, no. 5, 2012, pp. 1457-1493.

- Easley, David, Marcos M. López de Prado, and Maureen O’Hara. “The Microstructure of the ‘Flash Crash’ ▴ Flow Toxicity, Liquidity Crashes, and the Probability of Informed Trading.” The Journal of Portfolio Management, vol. 37, no. 2, 2011, pp. 118-128.

- Easley, David, Nicholas M. Kiefer, Maureen O’Hara, and Joseph B. Paperman. “Liquidity, Information, and Infrequently Traded Stocks.” The Journal of Finance, vol. 51, no. 4, 1996, pp. 1405-1436.

- Andersen, Torben G. and Oleg Bondarenko. “VPIN and the flash crash.” Journal of Financial Markets, vol. 17, 2014, pp. 1-46.

- Wu, Kesheng, et al. “A Big Data Approach to Analyzing Market Volatility.” Algorithmic Finance, vol. 2, no. 3-4, 2013, pp. 241-267.

![A sleek, dark sphere, symbolizing the Intelligence Layer of a Prime RFQ, rests on a sophisticated institutional grade platform. Its surface displays volatility surface data, hinting at quantitative analysis for digital asset derivatives](https://options.greeks.live/wp-content/uploads/2025/07/institutional-digital-asset-derivatives-rfq-platform-intelligence-layer-optimizing-high-fidelity-execution.jpg)

## Reflection

The integration of a metric like VPIN into an operational framework marks a shift in perspective. It moves market analysis from a reactive posture, focused on interpreting past price movements, to a proactive one centered on the underlying stability of the trading environment itself. The knowledge gained is not merely an indicator but a component in a larger system of intelligence.

The ultimate objective is to build an operational architecture that is resilient by design, capable of sensing and adapting to the subtle, systemic risks that precede major market events. The strategic potential lies in transforming the very nature of execution, from a simple act of transaction to a sophisticated process of navigating and managing the complex dynamics of market liquidity.

![A spherical Liquidity Pool is bisected by a metallic diagonal bar, symbolizing an RFQ Protocol and its Market Microstructure. Imperfections on the bar represent Slippage challenges in High-Fidelity Execution](https://options.greeks.live/wp-content/uploads/2025/07/institutional-digital-asset-derivatives-rfq-protocol-execution-optimization-within-principals-market-microstructure-framework.jpg)

## Glossary

<a href="https://prime.greeks.live/area/market-microstructure/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite" class="glossary-item-box">
![Geometric forms with circuit patterns and water droplets symbolize a Principal's Prime RFQ. This visualizes institutional-grade algorithmic trading infrastructure, depicting electronic market microstructure, high-fidelity execution, and real-time price discovery](https://options.greeks.live/wp-content/uploads/2025/07/digital-asset-derivatives-rfq-engine-prime-os-microstructure-analytics.jpg)

## Market Microstructure

Meaning ▴ Market Microstructure refers to the study of the processes and rules by which securities are traded, focusing on the specific mechanisms of price discovery, order flow dynamics, and transaction costs within a trading venue. </a><a href="https://prime.greeks.live/question/what-are-the-primary-quantitative-methods-for-detecting-informed-trading-in-anonymous-venues/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite" class="glossary-item-box">
![A sleek, angled object, featuring a dark blue sphere, cream disc, and multi-part base, embodies a Principal's operational framework. This represents an institutional-grade RFQ protocol for digital asset derivatives, facilitating high-fidelity execution and price discovery within market microstructure, optimizing capital efficiency](https://options.greeks.live/wp-content/uploads/2025/08/prime-os-rfq-for-institutional-digital-asset-derivatives-execution.jpg)

## Informed Trading

Primary quantitative methods transform raw trade data into a real-time probability of adverse selection, enabling dynamic risk control. </a><a href="https://prime.greeks.live/area/vpin/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite" class="glossary-item-box">
![A precision metallic instrument with a black sphere rests on a multi-layered platform. This symbolizes institutional digital asset derivatives market microstructure, enabling high-fidelity execution and optimal price discovery across diverse liquidity pools](https://options.greeks.live/wp-content/uploads/2025/07/prime-os-rfq-protocol-engine-component-digital-asset-derivatives-market-microstructure.jpg)

## Vpin

Meaning ▴ VPIN, or Volume-Synchronized Probability of Informed Trading, is a quantitative metric designed to measure order flow toxicity by assessing the probability of informed trading within discrete, fixed-volume buckets. </a><a href="https://prime.greeks.live/area/order-flow/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite" class="glossary-item-box">
![A sleek Prime RFQ interface features a luminous teal display, signifying real-time RFQ Protocol data and dynamic Price Discovery within Market Microstructure. A detached sphere represents an optimized Block Trade, illustrating High-Fidelity Execution and Liquidity Aggregation for Institutional Digital Asset Derivatives](https://options.greeks.live/wp-content/uploads/2025/08/advanced-rfq-protocol-engine-for-institutional-digital-asset-derivatives.jpg)

## Order Flow

Meaning ▴ Order Flow represents the real-time sequence of executable buy and sell instructions transmitted to a trading venue, encapsulating the continuous interaction of market participants' supply and demand. </a><a href="https://prime.greeks.live/area/adverse-selection-risk/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite" class="glossary-item-box">
![A precise lens-like module, symbolizing high-fidelity execution and market microstructure insight, rests on a sharp blade, representing optimal smart order routing. Curved surfaces depict distinct liquidity pools within an institutional-grade Prime RFQ, enabling efficient RFQ for digital asset derivatives](https://options.greeks.live/wp-content/uploads/2025/07/high-fidelity-digital-asset-derivatives-execution-via-rfq-protocols.jpg)

## Adverse Selection Risk

Meaning ▴ Adverse Selection Risk denotes the financial exposure arising from informational asymmetry in a market transaction, where one party possesses superior private information relevant to the asset's true value, leading to potentially disadvantageous trades for the less informed counterparty. </a><a href="https://prime.greeks.live/area/order-flow-toxicity/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite" class="glossary-item-box">
![A futuristic circular financial instrument with segmented teal and grey zones, centered by a precision indicator, symbolizes an advanced Crypto Derivatives OS. This system facilitates institutional-grade RFQ protocols for block trades, enabling granular price discovery and optimal multi-leg spread execution across diverse liquidity pools](https://options.greeks.live/wp-content/uploads/2025/07/institutional-digital-asset-derivatives-rfq-execution-microstructure-platform.jpg)

## Order Flow Toxicity

Meaning ▴ Order flow toxicity refers to the adverse selection risk incurred by market makers or liquidity providers when interacting with informed order flow. </a><a href="https://prime.greeks.live/area/order-imbalance/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite" class="glossary-item-box">
![An exposed high-fidelity execution engine reveals the complex market microstructure of an institutional-grade crypto derivatives OS. Precision components facilitate smart order routing and multi-leg spread strategies](https://options.greeks.live/wp-content/uploads/2025/07/institutional-digital-asset-derivatives-rfq-execution-engine-microstructure-2.jpg)

## Order Imbalance

Meaning ▴ Order Imbalance quantifies the net directional pressure within a market's limit order book, representing a measurable disparity between aggregated bid and offer volumes at specific price levels or across a defined depth. </a><a href="https://prime.greeks.live/question/did-the-double-volume-caps-succeed-in-moving-trading-volume-to-lit-markets/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite" class="glossary-item-box">
![Precision instrument featuring a sharp, translucent teal blade from a geared base on a textured platform. This symbolizes high-fidelity execution of institutional digital asset derivatives via RFQ protocols, optimizing market microstructure for capital efficiency and algorithmic trading on a Prime RFQ](https://options.greeks.live/wp-content/uploads/2025/07/precision-engineered-algorithmic-execution-infrastructure-for-institutional-digital-asset-derivatives-request-for-quote-protocols-optimal-liquidity.jpg)

## Volume Bucket

The Double Volume Caps succeeded in shifting volume from dark pools to lit markets and SIs, altering market structure without fully achieving a transparent marketplace. </a><a href="https://prime.greeks.live/area/flow-toxicity/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite" class="glossary-item-box">
![A sleek, institutional grade sphere features a luminous circular display showcasing a stylized Earth, symbolizing global liquidity aggregation. This advanced Prime RFQ interface enables real-time market microstructure analysis and high-fidelity execution for digital asset derivatives](https://options.greeks.live/wp-content/uploads/2025/07/institutional-grade-digital-asset-derivatives-trading-platform-displaying-global-liquidity-aggregation-and-real-time-price-discovery-for-rfq-protocols.jpg)

## Flow Toxicity

Meaning ▴ Flow Toxicity refers to the adverse market impact incurred when executing large orders or a series of orders that reveal intent, leading to unfavorable price movements against the initiator. </a><a href="https://prime.greeks.live/question/did-the-double-volume-caps-succeed-in-moving-trading-volume-to-lit-markets/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite" class="glossary-item-box">
![A stylized abstract radial design depicts a central RFQ engine processing diverse digital asset derivatives flows. Distinct halves illustrate nuanced market microstructure, optimizing multi-leg spreads and high-fidelity execution, visualizing a Principal's Prime RFQ managing aggregated inquiry and latent liquidity](https://options.greeks.live/wp-content/uploads/2025/07/principal-rfq-execution-engine-optimizing-digital-asset-derivatives-market-microstructure-for-institutional-liquidity-aggregation.jpg)

## Total Volume

The Double Volume Caps succeeded in shifting volume from dark pools to lit markets and SIs, altering market structure without fully achieving a transparent marketplace. </a><a href="https://prime.greeks.live/question/how-does-market-fragmentation-affect-adverse-selection-for-market-makers/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite" class="glossary-item-box">
![A metallic, modular trading interface with black and grey circular elements, signifying distinct market microstructure components and liquidity pools. A precise, blue-cored probe diagonally integrates, representing an advanced RFQ engine for granular price discovery and atomic settlement of multi-leg spread strategies in institutional digital asset derivatives](https://options.greeks.live/wp-content/uploads/2025/08/institutional-digital-asset-derivatives-rfq-protocol-system-facilitating-high-fidelity-execution-price-discovery.jpg)

## Market Makers

Market fragmentation amplifies adverse selection by splintering information, forcing a technological arms race for market makers to survive. </a><a href="https://prime.greeks.live/area/trade-data/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite" class="glossary-item-box">
![Abstractly depicting an institutional digital asset derivatives trading system. Intersecting beams symbolize cross-asset strategies and high-fidelity execution pathways, integrating a central, translucent disc representing deep liquidity aggregation](https://options.greeks.live/wp-content/uploads/2025/07/institutional-digital-asset-derivatives-ecosystem-unifying-rfq-protocols-for-high-fidelity-execution-and-deep-liquidity-aggregation-across-multi-leg-spreads.jpg)

## Trade Data

Meaning ▴ Trade Data constitutes the comprehensive, timestamped record of all transactional activities occurring within a financial market or across a trading platform, encompassing executed orders, cancellations, modifications, and the resulting fill details. </a><a href="https://prime.greeks.live/area/flash-crash/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite" class="glossary-item-box">
![A sleek, multi-layered device, possibly a control knob, with cream, navy, and metallic accents, against a dark background. This represents a Prime RFQ interface for Institutional Digital Asset Derivatives](https://options.greeks.live/wp-content/uploads/2025/07/precision-control-interface-for-institutional-digital-asset-derivatives-rfq-protocols-and-prime-os.jpg)

## Flash Crash

Meaning ▴ A Flash Crash represents an abrupt, severe, and typically short-lived decline in asset prices across a market or specific securities, often characterized by a rapid recovery. </a><a href="https://prime.greeks.live/area/algorithmic-trading/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite" class="glossary-item-box">
![A central crystalline RFQ engine processes complex algorithmic trading signals, linking to a deep liquidity pool. It projects precise, high-fidelity execution for institutional digital asset derivatives, optimizing price discovery and mitigating adverse selection](https://options.greeks.live/wp-content/uploads/2025/07/prime-os-rfq-protocols-high-fidelity-digital-asset-derivatives-execution.jpg)

## Algorithmic Trading

Meaning ▴ Algorithmic trading is the automated execution of financial orders using predefined computational rules and logic, typically designed to capitalize on market inefficiencies, manage large order flow, or achieve specific execution objectives with minimal market impact. </a>

**Tags:** [Order Flow](https://options.greeks.live/area/order-flow/), [Market Microstructure](https://options.greeks.live/area/market-microstructure/), [Liquidity Risk](https://options.greeks.live/area/liquidity-risk/), [Order Flow Toxicity](https://options.greeks.live/area/order-flow-toxicity/), [High-Frequency Trading](https://options.greeks.live/area/high-frequency-trading/), [Trade Data](https://options.greeks.live/area/trade-data/)	

## Discover More

- 
### [What Are the Technological Prerequisites for Implementing a Real-Time VPIN Calculation System?](https://options.greeks.live/question/what-are-the-technological-prerequisites-for-implementing-a-real-time-vpin-calculation-system/)
![A metallic rod, symbolizing a high-fidelity execution pipeline, traverses transparent elements representing atomic settlement nodes and real-time price discovery. It rests upon distinct institutional liquidity pools, reflecting optimized RFQ protocols for crypto derivatives trading across a complex volatility surface within Prime RFQ market microstructure.](https://options.greeks.live/wp-content/uploads/2025/07/institutional-digital-asset-derivatives-trade-execution-pipeline-optimizing-rfq-protocols-for-best-execution-and-capital-efficiency.jpg)

A real-time VPIN system requires a low-latency data pipeline to transform tick data into predictive liquidity risk signals.

- 
### [What Is the Difference between Adverse Selection Risk and Inventory Risk for a Market Maker?](https://options.greeks.live/question/what-is-the-difference-between-adverse-selection-risk-and-inventory-risk-for-a-market-maker/)
![A multi-faceted digital asset derivative, precisely calibrated on a sophisticated circular mechanism. This represents a Prime Brokerage's robust RFQ protocol for high-fidelity execution of multi-leg spreads, ensuring optimal price discovery and minimal slippage within complex market microstructure, critical for alpha generation.](https://options.greeks.live/wp-content/uploads/2025/07/institutional-digital-asset-derivatives-rfq-protocol-execution-precision-2.jpg)

Adverse selection is information risk from informed traders; inventory risk is position risk from market volatility.

- 
### [Can Minimum Quote Duration Rules Effectively Mitigate the Risks Associated with High-Frequency Trading?](https://options.greeks.live/question/can-minimum-quote-duration-rules-effectively-mitigate-the-risks-associated-with-high-frequency-trading/)
![A spherical, eye-like structure, an Institutional Prime RFQ, projects a sharp, focused beam. This visualizes high-fidelity execution via RFQ protocols for digital asset derivatives, enabling block trades and multi-leg spreads with capital efficiency and best execution across market microstructure.](https://options.greeks.live/wp-content/uploads/2025/07/institutional-grade-prime-os-rfq-protocol-digital-asset-derivatives-block-trade-execution.jpg)

MQD rules can mitigate HFT risks by mandating temporal commitment, enhancing liquidity integrity at the cost of higher spreads.

- 
### [What Is the Direct Relationship between RFQ Latency and Adverse Selection for a Market Maker?](https://options.greeks.live/question/what-is-the-direct-relationship-between-rfq-latency-and-adverse-selection-for-a-market-maker/)
![Sleek, intersecting planes, one teal, converge at a reflective central module. This visualizes an institutional digital asset derivatives Prime RFQ, enabling RFQ price discovery across liquidity pools. It ensures high-fidelity execution for multi-leg spreads and atomic settlement within complex market microstructure.](https://options.greeks.live/wp-content/uploads/2025/07/prime-os-digital-asset-derivatives-rfq-engine-optimizing-institutional-liquidity-aggregation-and-best-execution.jpg)

RFQ latency creates a time-based information gap that informed traders exploit, defining the market maker's adverse selection cost.

- 
### [How Do Machine Learning Models Enhance Predictive Accuracy in Quote Fading?](https://options.greeks.live/question/how-do-machine-learning-models-enhance-predictive-accuracy-in-quote-fading/)
![Precision-engineered institutional grade components, representing prime brokerage infrastructure, intersect via a translucent teal bar embodying a high-fidelity execution RFQ protocol. This depicts seamless liquidity aggregation and atomic settlement for digital asset derivatives, reflecting complex market microstructure and efficient price discovery.](https://options.greeks.live/wp-content/uploads/2025/07/institutional-digital-asset-derivatives-rfq-protocol-prime-os-core.jpg)

Machine learning models enhance quote fading prediction by discerning informed order flow signals, optimizing liquidity interaction.

- 
### [How Does Algorithmic Trading Impact Quote Durations during Flash Crashes?](https://options.greeks.live/question/how-does-algorithmic-trading-impact-quote-durations-during-flash-crashes/)
![Abstract forms depict institutional liquidity aggregation and smart order routing. Intersecting dark bars symbolize RFQ protocols enabling atomic settlement for multi-leg spreads, ensuring high-fidelity execution and price discovery of digital asset derivatives.](https://options.greeks.live/wp-content/uploads/2025/07/institutional-digital-asset-derivatives-rfq-high-fidelity-execution-2.jpg)

Algorithmic trading systems compress quote durations during flash crashes by design, as their risk protocols trigger a cascading, high-speed withdrawal of liquidity from the order book.

- 
### [What Are the Primary Types of Risk That Degrade Quote Firmness for Market Makers?](https://options.greeks.live/question/what-are-the-primary-types-of-risk-that-degrade-quote-firmness-for-market-makers/)
![A symmetrical, intricate digital asset derivatives execution engine. Its metallic and translucent elements visualize a robust RFQ protocol facilitating multi-leg spread execution. This system optimizes market microstructure and price discovery, ensuring high-fidelity execution and aggregated inquiry for capital efficiency.](https://options.greeks.live/wp-content/uploads/2025/07/institutional-digital-asset-derivatives-rfq-protocol-best-execution.jpg)

Quote firmness reflects the integrity of a market-making system's capacity to manage information and inventory risk.

- 
### [How Has the Rise of Dark Pools Affected the Traditional Roles of Liquidity Providers?](https://options.greeks.live/question/how-has-the-rise-of-dark-pools-affected-the-traditional-roles-of-liquidity-providers/)
![A polished metallic modular hub with four radiating arms represents an advanced RFQ execution engine. This system aggregates multi-venue liquidity for institutional digital asset derivatives, enabling high-fidelity execution and precise price discovery across diverse counterparty risk profiles, powered by a sophisticated intelligence layer.](https://options.greeks.live/wp-content/uploads/2025/08/principal-rfq-hub-digital-asset-derivatives-liquidity-aggregation.jpg)

The rise of dark pools has transformed liquidity providers from passive price-makers into active, technology-driven liquidity aggregators.

- 
### [Can the VPIN Metric Be Manipulated by Sophisticated Market Participants?](https://options.greeks.live/question/can-the-vpin-metric-be-manipulated-by-sophisticated-market-participants/)
![A sophisticated digital asset derivatives execution platform showcases its core market microstructure. A speckled surface depicts real-time market data streams. A teal intelligence layer optimizes price discovery, channeling through a central metallic hub, symbolizing robust atomic settlement and deep liquidity pool integration for institutional RFQ execution.](https://options.greeks.live/wp-content/uploads/2025/07/institutional-digital-asset-derivatives-rfq-execution-core-microstructure.jpg)

The VPIN metric's sensitivity to its core inputs creates architectural flaws that can be systematically exploited by sophisticated actors.

---

## Raw Schema Data

```json
{
    "@context": "https://schema.org",
    "@type": "BreadcrumbList",
    "itemListElement": [
        {
            "@type": "ListItem",
            "position": 1,
            "name": "Home",
            "item": "https://options.greeks.live"
        },
        {
            "@type": "ListItem",
            "position": 2,
            "name": "Question",
            "item": "https://options.greeks.live/question/"
        },
        {
            "@type": "ListItem",
            "position": 3,
            "name": "How Does VPIN Differentiate between Informed and Uninformed Trading Flow?",
            "item": "https://options.greeks.live/question/how-does-vpin-differentiate-between-informed-and-uninformed-trading-flow/"
        }
    ]
}
```

```json
{
    "@context": "https://schema.org",
    "@type": "Organization",
    "@id": "https://greeks.live/#organization",
    "name": "Greeks.Live",
    "url": "https://greeks.live/",
    "description": "Greeks.live is the definitive toolkit for the professional options trader, dedicated to empowering our users with institutional-grade data, advanced analytics, and a comprehensive suite of trading tools designed to provide a decisive edge in the market. Every article and guide published under the Greeks.live name is a product of our deep commitment to data-driven analysis and our mission to support the global trading community.",
    "email": "support@greeks.live",
    "logo": {
        "@type": "ImageObject",
        "url": "https://options.greeks.live/wp-content/uploads/2025/07/Greeks.Live-Logo-Icon.svg"
    },
    "hasPart": [
        {
            "@type": "WebSite",
            "name": "About Us",
            "url": "https://about.greeks.live"
        },
        {
            "@type": "WebSite",
            "name": "App Download Page",
            "url": "https://about.greeks.live/#/download/basic_trade"
        },
        {
            "@type": "WebSite",
            "name": "Newcomers' Guide",
            "url": "https://twisty-sign-c8b.notion.site/Guide-for-Greeks-live-X-Deribit-Newbies-5a08a3052822427d800af6eaf3704c8d"
        },
        {
            "@type": "WebSite",
            "name": "Knowledge Base",
            "url": "https://linktr.ee/greeks.live"
        },
        {
            "@type": "WebSite",
            "name": "Option Terminology",
            "url": "https://greekslive.notion.site/88dfc00e7c584d4d8969b6302a79a12f?pvs=4"
        },
        {
            "@type": "WebSite",
            "name": "Terms of Service",
            "url": "https://greeks.live/#/tos"
        },
        {
            "@type": "WebSite",
            "name": "Disclaimer",
            "url": "https://greeks.live/#/disclaimer"
        }
    ],
    "sameAs": [
        "https://x.com/greekslive",
        "https://youtube.com/@greeks_live?si=-KjT0Lkw4WUCI0tD",
        "https://t.me/greekslive_notifications",
        "https://t.me/greekslive",
        "https://pinterest.com/greekslive/"
    ],
    "makesOffer": [
        {
            "@type": "Offer",
            "itemOffered": {
                "@type": "Service",
                "name": "RFQ Platform",
                "url": "https://rfq.greeks.live",
                "description": "Execute institutional-grade block trades for crypto options and futures. This platform provides deep, over-the-counter (OTC) liquidity via a professional Request for Quote system.",
                "provider": {
                    "@id": "https://greeks.live/#organization"
                }
            }
        },
        {
            "@type": "Offer",
            "itemOffered": {
                "@type": "Service",
                "name": "Lending Tools",
                "url": "https://lend.greeks.live",
                "description": "Manage crypto lending and borrowing activities to earn yield or secure loans. This suite of tools helps users analyze interest rates and manage collateralized debt positions.",
                "provider": {
                    "@id": "https://greeks.live/#organization"
                }
            }
        },
        {
            "@type": "Offer",
            "itemOffered": {
                "@type": "Service",
                "name": "Data Lab",
                "url": "https://greeks.live/#/deribit/tools/datalab/BTC",
                "description": "Analyze historical and real-time options data with advanced metrics. This tool is designed for backtesting strategies and identifying market trends through comprehensive data visualization.",
                "provider": {
                    "@id": "https://greeks.live/#organization"
                }
            }
        },
        {
            "@type": "Offer",
            "itemOffered": {
                "@type": "Service",
                "name": "Profit & Loss Analysis (PnL)",
                "url": "https://greeks.live/#/deribit/tools/pnl_analysis",
                "description": "Track and analyze the Profit and Loss (PnL) of your options portfolio. This tool provides detailed performance metrics to help traders evaluate and refine their strategies.",
                "provider": {
                    "@id": "https://greeks.live/#organization"
                }
            }
        },
        {
            "@type": "Offer",
            "itemOffered": {
                "@type": "Service",
                "name": "Position Visualization",
                "url": "https://greeks.live/#/deribit/tools/pv/BTC",
                "description": "Visualize complex options positions and their corresponding risk profiles. This tool generates payoff diagrams to help traders intuitively understand potential profit, loss, and exposure.",
                "provider": {
                    "@id": "https://greeks.live/#organization"
                }
            }
        },
        {
            "@type": "Offer",
            "itemOffered": {
                "@type": "Service",
                "name": "Options Calculator",
                "url": "https://greeks.live/#/deribit/tools/calculator",
                "description": "Calculate the theoretical price and risk parameters ('the Greeks') of crypto options. An essential tool for pricing new trades and analyzing the sensitivity of existing positions.",
                "provider": {
                    "@id": "https://greeks.live/#organization"
                }
            }
        },
        {
            "@type": "Offer",
            "itemOffered": {
                "@type": "Service",
                "name": "Greeks.live Main Platform",
                "url": "https://greeks.live/",
                "description": "The central hub for the Greeks.live suite of professional cryptocurrency options and derivatives trading tools. Access analytics, manage positions, and explore the ecosystem.",
                "provider": {
                    "@id": "https://greeks.live/#organization"
                }
            }
        },
        {
            "@type": "Offer",
            "itemOffered": {
                "@type": "Service",
                "name": "Community Forum",
                "url": "https://t.greeks.live",
                "description": "Join the official Greeks.live community. Connect with other traders, share insights, and receive the latest updates directly from the team.",
                "provider": {
                    "@id": "https://greeks.live/#organization"
                }
            }
        },
        {
            "@type": "Offer",
            "itemOffered": {
                "@type": "Service",
                "name": "Greeks.live for Deribit",
                "url": "http://deribit.greeks.live",
                "description": "A dedicated interface for trading on the Deribit exchange. This platform leverages Greeks.live's advanced analytics and tools specifically for users of Deribit's options and futures markets.",
                "provider": {
                    "@id": "https://greeks.live/#organization"
                }
            }
        },
        {
            "@type": "Offer",
            "itemOffered": {
                "@type": "Service",
                "name": "Greeks.live for OKX",
                "url": "http://okx.greeks.live",
                "description": "A dedicated interface for trading on the OKX exchange. This platform integrates Greeks.live's powerful analytics with the OKX marketplace, focusing on its options and derivatives products.",
                "provider": {
                    "@id": "https://greeks.live/#organization"
                }
            }
        },
        {
            "@type": "Offer",
            "itemOffered": {
                "@type": "Service",
                "name": "GLVS.AI Trading Platform",
                "url": "https://www.glvs.ai/",
                "description": "An AI-powered platform for automated crypto options trading. Leverage advanced algorithms and data-driven signals to develop and deploy sophisticated, hands-free trading strategies.",
                "provider": {
                    "@id": "https://greeks.live/#organization"
                }
            }
        },
        {
            "@type": "Offer",
            "itemOffered": {
                "@type": "Service",
                "name": "API Testnet & Sandbox",
                "url": "https://test.greeks.live",
                "description": "A dedicated testnet environment for developers to test their API integrations and automated trading strategies. This sandbox allows for full functionality testing without risking real funds.",
                "provider": {
                    "@id": "https://greeks.live/#organization"
                }
            }
        }
    ],
    "subOrganization": [
        {
            "@type": "Organization",
            "name": "GreeksLive HK Co., Limited",
            "email": "support@greeks.live",
            "telephone": "+852-56418949",
            "address": {
                "@type": "PostalAddress",
                "streetAddress": "Unit 11, 27/F, K. Wah Centre, 191 Java Road",
                "addressLocality": "Hong Kong",
                "addressRegion": "North Point",
                "addressCountry": "CN",
                "postalCode": "0000"
            },
            "geo": {
                "@type": "GeoCoordinates",
                "latitude": "22.2932357",
                "longitude": "114.2022026"
            },
            "image": "https://options.greeks.live/wp-content/uploads/2025/08/Wah-Centre-Hong-Kong.jpg"
        }
    ]
}
```

```json
{
    "@context": "https://schema.org",
    "@type": "Article",
    "mainEntityOfPage": {
        "@type": "WebPage",
        "@id": "https://options.greeks.live/question/how-does-vpin-differentiate-between-informed-and-uninformed-trading-flow/"
    },
    "headline": "How Does VPIN Differentiate between Informed and Uninformed Trading Flow? \u25b4 Question",
    "description": "VPIN quantifies order flow toxicity by measuring trade imbalance in volume-time to signal rising adverse selection risk. \u25b4 Question",
    "url": "https://options.greeks.live/question/how-does-vpin-differentiate-between-informed-and-uninformed-trading-flow/",
    "datePublished": "2025-08-15T06:28:04+00:00",
    "dateModified": "2025-08-15T06:28:06+00:00",
    "articleSection": [
        "Question"
    ],
    "author": {
        "@id": "https://greeks.live/#organization"
    },
    "publisher": {
        "@id": "https://greeks.live/#organization"
    },
    "image": {
        "@type": "ImageObject",
        "url": "https://options.greeks.live/wp-content/uploads/2025/07/prime-os-rfq-protocol-for-institutional-digital-asset-derivatives.jpg",
        "caption": "Sleek, abstract platform with glowing green channels and dark components. This visualizes a Prime RFQ for institutional digital asset derivatives, driving RFQ-based high-fidelity execution. It optimizes market microstructure for block trade aggregation, ensuring private quotation and price discovery. Integrated pre-trade analytics and algorithmic trading enhance capital efficiency, managing multi-leg spread strategies and portfolio margin for Bitcoin options and Ethereum futures, minimizing slippage and adverse selection."
    },
    "keywords": [
        "Adverse Selection Risk",
        "Algorithmic Trading",
        "Flash Crash",
        "Flow Toxicity",
        "High-Frequency Trading",
        "Liquidity Risk",
        "Market Microstructure",
        "Order Flow",
        "Order Flow Toxicity",
        "Order Imbalance",
        "PIN Model",
        "Selection Risk",
        "Trade Data",
        "Volume Buckets",
        "VPIN"
    ]
}
```

```json
{
    "@context": "https://schema.org",
    "@type": "WebSite",
    "url": "https://options.greeks.live/",
    "potentialAction": {
        "@type": "SearchAction",
        "target": "https://options.greeks.live/?s=search_term_string",
        "query-input": "required name=search_term_string"
    }
}
```


---

**Original URL:** https://options.greeks.live/question/how-does-vpin-differentiate-between-informed-and-uninformed-trading-flow/
