Large stock price changes: volume or liquidity?

Weber, Philipp; Rosenow, Bernd

doi:10.1080/14697680500168008

Cited by 88 publications

(69 citation statements)

References 31 publications

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“…Hypothesis (3) is that this is due to selective liquidity taking, i.e. that liquidity takers submit large orders when liquidity is high and small orders when it is low (see ), Weber and Rosenow [2006], and Hopman [2006]). …”

Section: Why Is Individual Transaction Impact Concave?mentioning

confidence: 99%

“…This is defined as the average price change that would instantaneously occur for an effective market order of size v (Weber and Rosenow [2006]), Farmer and Zamani [2007]). In Figure 6 we show the virtual impact for AZN, computed by hypothetically submitting orders for a range of different values of v and measuring the immediate price response.…”

Section: Why Is Individual Transaction Impact Concave?mentioning

confidence: 99%

See 1 more Smart Citation

How Markets Slowly Digest Changes in Supply and Demand

2008

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In this article we revisit the classic problem of tatonnement in price formation from a microstructure point of view, reviewing a recent body of theoretical and empirical work explaining how fluctuations in supply and demand are slowly incorporated into prices. Because revealed market liquidity is extremely low, large orders to buy or sell can only be traded incrementally, over periods of time as long as months. As a result order flow is a highly persistent long-memory process. Maintaining compatibility with market efficiency has profound consequences on price formation, on the dynamics of liquidity, and on the nature of impact. We review a body of theory that makes detailed quantitative predictions about the volume and time dependence of market impact, the bid-ask spread, order book dynamics, and volatility. Comparisons to data yield some encouraging successes. This framework suggests a novel interpretation of financial information, in which agents are at best only weakly informed and all have a similar and extremely noisy impact on prices. Most of the processed information appears to come from supply and demand itself, rather than from external news. The ideas reviewed here are relevant to market microstructure regulation, agent-based models, cost-optimal execution strategies, and understanding market ecologies.

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Section: Why Is Individual Transaction Impact Concave?mentioning

confidence: 99%

Section: Why Is Individual Transaction Impact Concave?mentioning

confidence: 99%

How Markets Slowly Digest Changes in Supply and Demand

2008

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“…It is found that the virtual price impact is much stronger than the actual impact [4] and large price fluctuations are not necessarily caused by large orders but rather the liquidity [5,6]. It is rational that a large trader prefers to split his large order and submit when the opposite LOB is thick such that the price does not change much.…”

Section: Introductionmentioning

confidence: 99%

Empirical shape function of limit-order books in the Chinese stock market

Chen

Zhou

2008

Physica A: Statistical Mechanics and its Applications

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We have analyzed the statistical probabilities of limit-order book (LOB) shape through building the book using the ultra-high-frequency data from 23 liquid stocks traded on the Shenzhen Stock Exchange in 2003. We find that the averaged LOB shape has a maximum away from the same best price for both buy and sell LOBs. The LOB shape function has nice exponential form in the right tail. The buy LOB is found to be abnormally thicker for the price levels close to the same best although there are much more sell orders on the book. We also find that the LOB shape functions for both buy and sell sides have periodic peaks with a period of five. The 1-min averaged volumes at fixed tick level follow lognormal distributions, except for the left tails which display power-law behaviors, and exhibit long memory. Academic implications of our empirical results are also discussed briefly.

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“…Arriving limit orders significantly reduce the impact of trades [44] and the concave shape of the price impact function changes depending on the contemporaneous limit order arrivals [41]. 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]. Hasbrouck and Seppi [22] use depth as one of the factors that determine price impact.…”

Section: Introductionmentioning

confidence: 99%

The Price Impact of Order Book Events

2012

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We study the price impact of order book events -limit orders, market orders and cancelations -using the NYSE TAQ data for 50 U.S. stocks. We show that, over short time intervals, price changes are mainly driven by the order flow imbalance, defined as the imbalance between supply and demand at the best bid and ask prices. Our study reveals a linear relation between order flow imbalance and price changes, with a slope inversely proportional to the market depth. These results are shown to be robust to seasonality effects, and stable across time scales and across stocks. We argue that this linear price impact model, together with a scaling argument, implies the empirically observed "square-root" relation between price changes and trading volume. However, the relation between price changes and trade volume is found to be noisy and less robust than the one based on order flow imbalance.

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Large stock price changes: volume or liquidity?

Cited by 88 publications

References 31 publications

How Markets Slowly Digest Changes in Supply and Demand

How Markets Slowly Digest Changes in Supply and Demand

Empirical shape function of limit-order books in the Chinese stock market

The Price Impact of Order Book Events

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