The limit order book on different time scales

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The limit order book on different time scales

Zoltan Eisler
Janos Kertesz
Fabrizio Lillo
Published on 5/28/2007
Equities
United Kingdom (UK)
High frequency trading
Machine learning

This paper investigates the limit order book of GlaxoSmithKline on the London Stock Exchange across multiple time scales, from monthly to tick-by-tick. The authors show that the qualitative behavior of prices and order book dynamics changes dramatically with the time horizon. On monthly scales, price changes resemble ordinary diffusion with negligible microstructure effects. On daily scales, returns are fat-tailed and volatility is clustered, while the order book exhibits large day-to-day fluctuations in shape and volume imbalance. The average order book shape is not typical; individual snapshots reveal a narrow central region near the spread, a regular striped pattern of orders every 5 ticks, and large orders at round numbers. The imbalance between buy and sell limit order volumes varies strongly but does not directly predict returns. At the intraday and tick-by-tick level, price formation is governed by the impact of individual market orders, limit order placements, and cancellations. Liquidity crises, where a large portion of the book is wiped out, lead to abrupt spread widening followed by slow relaxation (half-life of 10^2-10^3 seconds). The study highlights that microstructure effects are crucial for short-term dynamics but average out at longer horizons, and that current models cannot fully capture the rich structure of very short-term returns.

Highlights

  • 1Compares limit order book dynamics across monthly, daily, and intraday time scales using LSE data.
  • 2Shows that the average order book shape is not typical; daily snapshots vary strongly.
  • 3Identifies three types of limit orders: narrow central range, regular striped pattern every 5 ticks, and large orders at round numbers.
  • 4Demonstrates that order imbalance between buy and sell volumes does not directly predict returns.
  • 5Describes price impact mechanisms at tick-by-tick level, including liquidity crises and spread relaxation.

Methods

  • M
    Analysis of limit order book data from London Stock Exchange (GSK stock, year 2002).
  • M
    Visualization of order book snapshots at different time scales (yearly, daily, intraday).
  • M
    Quantification of order imbalance using buy/sell volume ratios.
  • M
    Event-based analysis of price impact and liquidity fluctuations.

Results

  • R
    Monthly returns are well described by ordinary diffusion; microstructure is negligible.
  • R
    Daily returns are fat-tailed with clustered volatility; order book shape varies greatly day-to-day.
  • R
    The order book exhibits a regular striped pattern of orders every 5 ticks, not visible in time averages.
  • R
    Order imbalance fluctuates but does not directly correlate with returns.
  • R
    At tick-by-tick level, price changes are driven by market order impact and liquidity crises, with spread relaxation times of 10^2-10^3 seconds.
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