Depth Characteristics for the Electronic Futures Limit Order Book

Aidov, Alexandre; Daigler, Robert T.

doi:10.1002/fut.21706

Cited by 13 publications

(10 citation statements)

References 34 publications

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“…Wang et al (2014) reconstructed the best bid and ask steps of a limit order book to study the liquidity costs in corn futures markets. Using CME Group RLC market depth data 1 , Aidov (2013) and Aidov and Daigler (2015) reconstruct the five-step LOB for futures contracts of the 10-Year U.S. Treasury note, corn, light sweet crude oil (WTI), euro/U.S. dollar, yen/U.S.…”

Section: Information Contained In the Lobmentioning

confidence: 99%

“…To overcome this problem, Hasbrouck (1995) has proposed calculating upper and lower bounds for 1 RLC market depth data was discontinued in 2009 and the current format of the CME Group market depth data is FIX which is the format used in the present study. The period of study in Aidov (2013) and Aidov and Daigler (2015) for different contracts ranges from January 2008 to March, April, or October 2009, depending on when the RLC data was discontinued for the specific contract. the information shares of price series.…”

Section: Information Share Measuresmentioning

confidence: 99%

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Price Discovery in Agricultural Futures Markets: Should We Look beyond the Best Bid‐Ask Spread?

Arzandeh¹,

Frank²

2019

American J Agri Economics

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Price discovery is defined as the incorporation of information to prices through the actions of traders. Previous studies in financial markets have found evidence that informed traders may submit limit orders instead of market orders. If so, the steps of limit order book (LOB) beyond the best bid and best ask spread (BAS) contain valuable information and contribute to price discovery of the underlying asset. This is the first attempt to examine the informativeness of the LOB beyond the BAS for agricultural commodities. We reconstruct the LOB using market depth data and use three information share approaches to test whether the steps of LOB beyond the BAS contribute to price discovery in agricultural commodity markets. This is done for five major agricultural commodities namely live cattle, lean hogs, corn, wheat, and soybeans as well as the CME E-mini S&P 500. We find that a substantial market depth exists at the steps beyond the best bid and ask prices in the futures markets. The results of the three information share measures show that the steps of the LOB beyond the BAS contribute by over 27% to price discovery of futures contracts. Across agricultural commodities, the steps of the LOB beyond the BAS have more information for grains than meats. Moreover, we find that the steps closer to the top of the book, relative to the steps farther, contain more information. These findings suggest that informed traders in futures electronic markets actively use limit orders with price steps beyond the BAS and especially the steps near the top of the book. The results also show that for E-mini S&P 500, the steps closer to the top of the book contain more information at the beginning and the end of the week whereas steps farther have more information in the middle of the week.

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Section: Information Contained In the Lobmentioning

confidence: 99%

Section: Information Share Measuresmentioning

confidence: 99%

Price Discovery in Agricultural Futures Markets: Should We Look beyond the Best Bid‐Ask Spread?

Arzandeh¹,

Frank²

2019

American J Agri Economics

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“…Most LOB visualizations in the literature show (some form of) liquidity, that is, the volume in the market at different price levels ("depth") and the bid-ask spread ("tightness"). Aidov and Daigler (2015) visualize the LOB in two ways. Figure 1 in their paper (column 2 in Table 3) visualizes the cumulative depth for each level across the book over time, that is, the bid and ask volumes aggregated per level.…”

Section: Particle Physics and The Lob: Illustration For Liquiditymentioning

confidence: 99%

When two worlds collide: Using particle physics tools to visualize the limit order book

Verhulst

Debie

Hageboeck

et al. 2021

Journal of Futures Markets

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We introduce a methodology to visualize the limit order book (LOB) using a particle physics lens. Open-source data-analysis tool ROOT, developed by CERN, is used to reconstruct and visualize futures markets. Message-based data is used, rather than snapshots, as it offers numerous visualization advantages. The visualization method can include multiple variables and markets simultaneously and is not necessarily time dependent. Stakeholders can use it to visualize high-velocity data to gain a better understanding of markets or effectively monitor markets.In addition, the method is easily adjustable to user specifications to examine various LOB research topics, thereby complementing existing methods.

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“…Related research attempts to model the liquidity characteristics within the limit order book (Bouchaud et al 2002;Yura et al 2014). Aidov and Daigler (2015) examine the liquidity characteristics of the limit order book in futures markets but do not explore the relation between depth and spread.…”

Section: Introductionmentioning

confidence: 99%

The Relation between Intraday Limit Order Book Depth and Spread

Aidov

Lobanova

2021

IJFS

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Prior studies that examine the relation between market depth and bid–ask spread are often limited to the first level of the limit order book. However, the full limit order book provides important information beyond the first level about the depth and spread, which affects the trading decisions of market participants. This paper examines the intraday behavior of depth and spread in the five-deep limit order book and the relation between depth and spread in a futures market setting. A dummy-variables regression framework is employed and is estimated using the generalized method of moments (GMM). Results indicate an inverse U-shaped pattern for depth and an increasing pattern for spread. After controlling for known explanatory factors, an inverse relation between the limit order book depth and spread is documented. The inverse relation holds for depth and spread at individual levels in the limit order book as well. Results indicate that market participants actively manage both the price (spread) and quantity (depth) dimensions of liquidity along the five-deep limit order book.

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Depth Characteristics for the Electronic Futures Limit Order Book

Cited by 13 publications

References 34 publications

Price Discovery in Agricultural Futures Markets: Should We Look beyond the Best Bid‐Ask Spread?

Price Discovery in Agricultural Futures Markets: Should We Look beyond the Best Bid‐Ask Spread?

When two worlds collide: Using particle physics tools to visualize the limit order book

The Relation between Intraday Limit Order Book Depth and Spread

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