Large price changes on small scales

Zawadowski, Ádám; Kertész, János; Andor, György

doi:10.1016/j.physa.2004.06.121

Cited by 27 publications

(26 citation statements)

References 10 publications

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“…With trade volumes increasing 10-fold in developed markets through the 1990's, it became possible to quantify regularities in price response to establish the relationship between averaged price shifts and transaction volumes [1,7,8,11,20,[23][24][25][26]28]. This has led to a more refined but heuristic definition of price impact as the correlation between trade size and direction and the resultant price change.…”

Section: Introductionmentioning

confidence: 99%

Deviations in expected price impact for small transaction volumes under fee restructuring

Harvey

Hendricks

Gebbie

et al. 2017

Physica A: Statistical Mechanics and its Applications

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We report on the occurrence of an anomaly in the price impacts of small transaction volumes following a change in the fee structure of an electronic market. We first review evidence for the existence of a master curve for price impact on the Johannesburg Stock Exchange (JSE). On attempting to re-estimate a master curve after fee reductions, it is found that the price impact corresponding to smaller volume trades is greater than expected relative to prior estimates for a range of listed stocks. We show that a master curve for price impact can be found following rescaling by an appropriate liquidity proxy, providing a means for practitioners to approximate price impact curves without onerous processing of tick data.

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Section: Introductionmentioning

confidence: 99%

Deviations in expected price impact for small transaction volumes under fee restructuring

Harvey

Hendricks

Gebbie

et al. 2017

Physica A: Statistical Mechanics and its Applications

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show abstract

“…Apart from the dynamic of occurrence rate of aftershocks, another related topic is the relaxation dynamics of some financial measures after large price change / large bid-ask spread change. Zawadowski et al examined high frequency data from NYSE and NASDAQ to conclude that volatility, volume and in case of the NYSE bid-ask spread increase sharply at the large intraday price change and decay according to a power law [8,9]. Ponzi et al studied the dynamics of the bid-ask spread and the mid-price after a sudden variation of spread, and then found that the spread decays as a power law to its normal value [10].…”

Section: Introductionmentioning

confidence: 99%

Short-term market reaction after trading halts in Chinese stock market

Zhang

Liu

2014

Physica A: Statistical Mechanics and its Applications

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In this paper, we study the dynamics of absolute return, trading volume and bid-ask spread after the trading halts using high-frequency data from the Shanghai Stock Exchange. We deal with all three types of trading halts, namely intraday halts, one-day halts and inter-day halts, of 203 stocks in Shanghai Stock Exchange from August 2009 to August 2011. We find that absolute return, trading volume, and in case of bid-ask spread around intraday halts share the same pattern with a sharp peak and a power law relaxation after that. While for different types of trading halts, the peaks' height and the relaxation exponents are different. From the perspective of halt reasons or halt durations, the relaxation exponents of absolute return after inter-day halts are larger than those after intraday halts and one-day halts, which implies that inter-day halts are most effective. From the perspective of price trends, the relaxation exponents of excess absolute return and excess volume for positive events are larger than those for negative events in case of intraday halts and one-day halts, implying that positive events are more effective than negative events for intraday halts and one-day halts. In contrast, negative events are more effective than positive events for inter-day halts.

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“…On the other hand a relative filter, in which one selects those events which are larger than the average fluctuations at the same time of the day, will suffer from the effect of an opposite uneven selection. As a consequence, in this work we use a combination of the two filters, following [23,26,27]. If one chooses suitable thresholds for both filters an uniform distribution of events over the day can be recovered.…”

Section: Selection Of Large Eventsmentioning

confidence: 99%

Liquidity crises on different time scales

2015

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We present an empirical analysis of the microstructure of financial markets and, in particular, of the static and dynamic properties of liquidity. We find that on relatively large time scales (15 minutes) large price fluctuations are connected to the failure of the subtle mechanism of compensation between the flows of market and limit orders: in other words, the missed revelation of the latent order book breaks the dynamical equilibrium between the flows, triggering the large price jumps. On smaller time scales (30 seconds), instead, the static depletion of the limit order book is an indicator of an intrinsic fragility of the system, which is related to a strongly non linear enhancement of the response. In order to quantify this phenomenon we introduce a measure of the liquidity imbalance present in the book and we show that it is correlated to both the sign and the magnitude of the next price movement. These findings provide a quantitative definition of the effective liquidity, which results to be strongly dependent on the considered time scales.

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Large price changes on small scales

Cited by 27 publications

References 10 publications

Deviations in expected price impact for small transaction volumes under fee restructuring

Deviations in expected price impact for small transaction volumes under fee restructuring

Short-term market reaction after trading halts in Chinese stock market

Liquidity crises on different time scales

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