What really causes large price changes?

By J. Doyne Farmer 5, L. Gillemot, Fabrizio Lillo, Szabolcs Mike, Anindya Sen. 2003

320 citations recorded by the source corpus.

We study the cause of large fluctuations in prices on the London Stock Exchange. This is done at the microscopic level of individual events, where an event is the placement or cancellation of an order to buy or sell. We show that price fluctuations caused by individual market orders are essentially independent of the volume of orders. Instead, large price fluctuations are driven by liquidity fluctuations, variations in the market's ability to absorb new orders. Even for the most liquid stocks there can be substantial gaps in the order book, corresponding to a block of adjacent price levels containing no quotes. When such a gap exists next to the best price, a new order can remove the best quote, triggering a large midpoint price change. Thus, the distribution of large price changes merely reflects the distribution of gaps in the limit order book. This is a finite size effect, caused by the granularity of order flow: in a market where participants place many small orders uniformly across prices, such large price fluctuations would not happen. We show that this also explains price fluctuations on longer timescales. In addition, we present results suggesting that the risk profile varies from stock to stock, and is not universal: lightly traded stocks tend to have more extreme risks.

Subfields: Economics and Econometrics, Finance

View Paper: https://www.semanticscholar.org/paper/772ebe43853eff3e0d11940e47eed234ebc0d01d

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Citations in the corpus

Convolutional neural networks applied to high-frequency market microstructure forecasting (2017, background): “The latter is already a well-documented phenomenon for having an impact on price moves [22].”
An empirical behavioral model of liquidity and volatility (2007, background): “Previous work has shown that liquidity is typically the dominant determinant of volatility, at least for short time scales (Farmer et al. 2004, Weber and Rosenow 2006, Gillemot, Lillo and Farmer 2006).”
Ergodicity and scaling limit of a constrained multivariate Hawkes process (2013, unknown): “On the one hand, an extensive statistical study on the limit order book dynamics and limit order book information content can be found in [9, 26, 39, 19, 30, 10, 25, 14, 41]; on the other hand, many researchers have endeavored to propose different models, including equilibrium model, agent-based mod”
The Impact of Heterogeneous Trading Rules on the Limit Order Book and Order Flows (2007, methodology): “A variety of studies have made clear that the mean market impact is an increasing function of the order size, in contrast Farmer et al. (2004) have shown that large price changes in response to large orders are very rare.”
The price impact of order book events: market orders, limit orders and cancellations (2009, background): “Hence the DMO0’s (and similarly the DCA0’s) correspond to half of the gap between the first and the second best quote just before the level was removed (see also Farmer et al. (2004)).”
Statistical Modeling of High-Frequency Financial Data (2011, background): “…analysis and modeling of high frequency data can provide insight into the interplay between order ﬂow, liquidity and price dynamics [15, 55, 29] and might help bridge the gap between market microstructure theory [12, 51, 30, 33, 45, 54]–which has provided useful insights by focusing on…”
A Stochastic Model for Order Book Dynamics (2010, unknown): “The steady state profile of the order book describes the average market impact of trades Farmer et al. (2004), Bouchaud et al. (2008).”
Power-Law Distributions in Empirical Data (2007, background): “An alternative approach, quite common in the quantitative finance literature, is simply to limit the analysis to the largest observed samples only, such as the largest √ n or 1 10n observations [17].”
The Price Impact of Order Book Events (2010, unknown): “The outstanding limit orders (also known as market depth) significantly affect the impact of an individual trade ([30]) and low depth is associated with large price changes [45, 17].”
Price Dynamics in a Markovian Limit Order Market (2011, background): “On the other hand, empirical studies on limit order books (Bouchaud et al. (2008), Farmer et al. (2004), Gourieroux et al. (1999), Holliﬁeld et al. (2004), Smith et al. (2003)) provide an extensive list of statistical features of order book dynamics that are challenging to incorporate in a single…”
High-Frequency Trading and Extreme Price Movements (2018, unknown): “Farmer et al. (2004) suggest that large price fluctuations in a short time period may be driven by the stock-specific time-varying liquidity supply.”
Relation between bid–ask spread, impact and volatility in order-driven markets (2006, background): “Nevertheless this situation is empirically quite rare on the markets we are concerned with, and corresponds to only a few percent of all cases (Farmer et al. 2004). meaning, as intuitively clear, that this cost is positive when spreads are large, but may become negative if the total price impact…”