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Measuring Market Liquidity with Spreads, Depth, and Price Impact

Article Quant Q&A · Author: Zarbouzou

Summary

The document surveys ways to measure market liquidity and explains why trading volume alone can be an incomplete proxy. Quote-based measures include the bid-ask spread, top-of-book size, and depth across the order book or venues; spreads indicate trading cost, while available size helps estimate how much can trade before prices move. For less transparent venues, historical execution data may be needed to infer liquidity.

It also describes broader measures based on turnover, the relation between volume and returns, and price impact. Examples mentioned include spread proxies, illiquidity ratios, and VPIN, which combines trading volume with concurrent price movements and is presented as a signal of toxic order flow and potential liquidity deterioration. Liquidity is multidimensional, including tightness, depth, and resiliency, and market liquidity differs from funding liquidity. The answers emphasize that no single measure is universally accepted; data availability, market structure, asset, and intended use shape the choice.

Key ideas

  • Volume alone may not capture liquidity because it does not describe available selling interest or the cost of trading.
  • Bid-ask spreads and displayed quote sizes measure tightness and accessible depth near the current price.
  • Full order-book and cross-venue data can provide a richer view of depth and potential market impact.
  • Daily-data measures often use turnover, volume-return relationships, spreads, or price impact.
  • Liquidity has multiple dimensions, and market liquidity is distinct from funding liquidity.

Tags

Full text
# Measuring liquidity


# Measuring liquidity












While liquidity is one of the key figure of financial markets, It seems to be very difficult to measure. Volume is sometime used as a proxy but can sometimes be completly irrelevant.

Could you point to relevant research on what data to use and how to compute the measure?

## Answer by chrisaycock (score 9, accepted)

https://quant.stackexchange.com/a/1346

Volume merely indicates how much buy-side interest exists in a stock. For liquidity, the sell-side interest is more relevant, which implies the quote characteristics (the limit-order book).

In addition to the bid-ask spread, I look at the top-of-book quote size. Here's an example from BATS:

```
sym | bid    ask    bidsize asksize
----| -----------------------------
AAPL| 325.12 325.21  100     100    
MSFT|  24.70  24.71 3900    5900
```

I can only buy \$32,521 worth of Apple without impacting price, as opposed to \$145,789 of Microsoft. So the slippage is smaller.

There are more sophisticated measurements for order book entries. I could look at the full book ("level II data") to see the depth of the order chain. I could look across multiple exchanges, which is what a smart order router must do anyway. I could even look at related asset classes if the investor's goal is merely to gain exposure to general risk.

To be really swanky, I could investigate dark pools, though that's harder since the quotes aren't displayed. For this, a quant would need historical data regarding how much has been executed in the past. That's one reason why the big banks have a competitive advantage in dark-pool aggregator algorithms: they have enough client flow to record execution patterns.

## Answer by SRKX (score 6)

https://quant.stackexchange.com/a/1344

For my master thesis, I used the bid-ask spread as a liquidity measure. Intuitively, it is the price to the have the liquidity (or even the price of liquidity); the bigger the bid-ask spread, the lower the liquidity.

I know that Carlo Acerbi of MSCI is also looking into liquidity risk management and has a very interesting model for liquidity which is explained in this presentation. Maybe it can give you some ideas.

## Answer by RockScience (score 3)

https://quant.stackexchange.com/a/1367

You can have a look at what the guys at Nanex.

Here is an example of what they look at. The chart is colour coded for market depth (the colder the colour the less depth)

## Answer by Tal Fishman (score 2)

https://quant.stackexchange.com/a/1520

You may also be interested in a series of papers by Easley, de Prado, and O'Hara (2011), Flow Toxicity and Volatility in a High Frequency World. This paper follows up on a measure of the effect of trades on prices developed by two of the authors in 1987. They show that the new measure, which takes volume and concurrent price movements into account, can predict rapid changes in liquidity such as the "flash crash". From the abstract (published in JPM Winter 2011):

> The ‘flash crash’ of May 6th 2010 was the second largest point swing (1,010.14 points) and the biggest one-day point decline (998.5 points) in the history of the Dow Jones Industrial Average. For a few minutes, $1 trillion in market value vanished. In this paper, we argue that the ‘flash crash’ is the result of the new dynamics at play in the current market structure. We highlight the role played by order toxicity in affecting liquidity provision, and we show that a measure of this toxicity, the Volume-Synchronized Probability of Informed Trading (VPIN)*, captures the increasing toxicity of the order flow in the hours and days prior to collapse.

## Answer by lehalle (score 2)

https://quant.stackexchange.com/a/8673

The "Navigating Liquidity" serie by CA Cheuvreux's former quant research team addresses different means to measure liquidity in a post MiFID (in europe) and post Reg NMS (for US) world.

Unfortunately, CA Cheuvreux having been sold by CAcib, most of the links in the upper google search seems to be broken. You will find informations about measuring liquidity in the first Chapter of Market Microstructure in Practice.

## Answer by JohnAndrews (score 1)

https://quant.stackexchange.com/a/8664

A list of various liquidity measures is described in the paper:

Economic Valuation of Liquidity Timing

See page 11, starting with the paragraph

> (...) We consider a variety of monthly liquidity measures which together capture all aspects of liquidity: Roll, Effective Tick, Zeros, High-Low, and Illiquidity Ratio (ILR).10 The first four measures proxy for the bid-ask spread and the fifth measure is a proxy for price impact. All liquidity variables measure illiquidity, i.e. higher estimates correspond to lower liquidity.

## Answer by Malick (score 1)

https://quant.stackexchange.com/a/9973

Measuring liquidity is a key problem in market risk management, it is probably due to its multi-dimension property (tightness, depth and resiliency.). Loosely speaking , market liquidity refers to the ease with which an asset can be traded. It should be distinguish from funding liquidity which refers to the ability to fulfill its commitments. Regarding market liquidity: There are several metrics available to measure it but, as far i read, no one reach a consensus . Some are based on intraday data (contents of the book order ..) but most parts of metrics are based on daily data (prices returns). We can distinguish three mains types of liquidity metrics depending’s if they are focus on the quantity (turnover ratio,volume..) , the volume/return relation (volume to return ratio, Amivest metric, ) or more on the tightness dimension (bid ask spread based metrics). Liquidity literature is very large, I recommend you these authors: Chordia , Subrahmanyam , Brunnermeier, and Amihud.

http://rfs.oxfordjournals.org/content/22/6/2201

## Answer by user7056 (score 0)

https://quant.stackexchange.com/a/10471

Any spread that adds to the risk free rate is made by credit spread (the counterparty will not return the security) and liquidity spread (the need of the market for that security).

In a Repurchase agreement, when you give a security against receiving cash, the credit risk still stays with you. The haircut in the repo's security is to cover the market risk. In addition, any dividents the counterparty receives will be manufactured/repayed to you. The repo-rate will therefore be the liquidity spread of the security against the currency you make the repo within. The term of the spread is the duration of the repo. A perfectly liquid security will have the spread zero. The extra cost supported due to this spread is the price of illiquidity.

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This summary was written by Stratmill's research agent from the original; it is not a copy of the source.