The adaptive nature of liquidity taking in limit order books

Taranto, Damian Eduardo; Bormetti, Giacomo; Lillo, Fabrizio

doi:10.1088/1742-5468/2014/06/p06002

Cited by 23 publications

(13 citation statements)

References 34 publications

(132 reference statements)

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“…However, once a market order enters the opposite side of the order book, the price returns to the best price on the opposite side, thus restoring market efficiency. This finding is consistent with the result in certain empirical studies, such as Taranto et al (2014), who find that the persistence of order flows reduces and price efficiency is restored when the same sign of order flows enters the order book and that the depth on the opposite side shrinks but the price impact is likely to decrease significantly.…”

Section: Simulation Results In An Order-splitting Economysupporting

confidence: 91%

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Dynamic Predictor Selection and Order Splitting in a Limit Order Market

Yamamoto

2017

Macroecon. Dynam.

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Recent empirical research has documented the clustered volatility and fat tails of return distribution in stock markets, yet returns are uncorrelated over time. Certain agent-based theoretical models attempt to explain the empirical features in terms of investors' order-splitting or dynamic switching strategies, both of which are frequently used by actual stock investors. However, little theoretical research has discriminated among the behavioral assumptions within a model and compared the impacts of the assumptions on the empirical features. Nor has the research simultaneously replicated the return features and empirical features on market microstructure, such as patterns of order choice. This study constructs an artificial limit order market in which investors split orders into small pieces or use fundamental and trend-following predictors interchangeably over time. We demonstrate that, on one hand, the market that features strategies with order splitting and dynamic predictor selection can independently replicate clustered volatility and fat tails with near-zero return autocorrelations. However, we also show that patterns of order choice do not match those found in certain previous empirical studies in both types of economies. Thus, we conclude that, in reality, the two strategies can work to generate the empirical return features but that investors may also use other strategies in actual stock markets. We also demonstrate that the impact of both strategies on the volatility persistence tends to be greater as the number of traders increases in the market; this finding implies that the order-splitting strategy and dynamic predictor selection are more crucial for the empirical phenomena pertaining to larger capital stocks.

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Section: Simulation Results In An Order-splitting Economysupporting

confidence: 91%

“…24. The uncorrelated returns in the presence of persistent order flows are consistent with the result in previous empirical studies, such as Taranto et al (2014).…”

Section: Resultssupporting

confidence: 90%

Dynamic Predictor Selection and Order Splitting in a Limit Order Market

Yamamoto

2017

Macroecon. Dynam.

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“…In the right hand side of the equation, σ and V are, respectively, the volatility of the traded instrument and the total traded volume over the order execution time scale T , Y 0 a dimensionless constant of order unity, and δ is the impact exponent in the range [0.4, 0.7]. Theoretical models allowing one to understand the mechanisms underlying this strongly concave, nonintuitive impact function, have been put forward in [6,9,11,12] (on a related topic, see also [13]). Still, whereas the description of the contemporaneous impact of orders in terms of Eq.…”

Section: Introductionmentioning

confidence: 99%

Slow Decay of Impact in Equity Markets

Brokmann

Sérié

Kockelkoren

et al. 2015

Mark. Microstructure Liq.

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Using a proprietary dataset of meta-orders and prediction signals, and assuming a quasi-linear impact model, we deconvolve market impact from past correlated trades and a predictable return component to elicit the temporal dependence of the market impact of a single daily meta-order, over a ten day horizon in various equity markets. We find that the impact of single meta-orders is to a first approximation universal and slowly decays to zero (or to a small value), possibly as a power-law. We show that auto-correlated order-flows and trade information contents fully accounts for the apparent plateau observed in the raw data. We discuss the possible bias introduced by the quasi-linear assumption.PACS numbers:

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“…The asymmetric liquidity mechanism has been verified empirically [9] and its microscopic origin has been explored and elucidated in [18]. In this last paper it has been shown that agents executing incrementally a large order by splitting it in a large number of trades adjust the size of these trades in order to minimize their impact on price.…”

Section: The Long Memory Of the Marketmentioning

confidence: 91%

Behind the Price: On the Role of Agent’s Reflexivity in Financial Market Microstructure

Barucca¹,

Lillo²

2016

Studies in Applied Philosophy, Epistemology and Rational Ethics

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In this chapter we review some recent results on the dynamics of price formation in financial markets and its relations with the efficient market hypothesis. Specifically, we present the limit order book mechanism for markets and we introduce the concepts of market impact and order flow, presenting their recently discovered empirical properties and discussing some possible interpretation in terms of agent's strategies. Our analysis confirms that quantitative analysis of data is crucial to validate qualitative hypothesis on investors' behavior in the regulated environment of order placement and to connect these micro-structural behaviors to the properties of the collective dynamics of the system as a whole, such for instance market efficiency. Finally we discuss the relation between some of the described properties and the theory of reflexivity proposing that in the process of price formation positive and negative feedback loops between the cognitive and manipulative function of agents are present. * Authors acknowledge partial support by the grant SNS13LILLB "Systemic risk in financial markets across time scales".

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The adaptive nature of liquidity taking in limit order books

Cited by 23 publications

References 34 publications

Dynamic Predictor Selection and Order Splitting in a Limit Order Market

Dynamic Predictor Selection and Order Splitting in a Limit Order Market

Slow Decay of Impact in Equity Markets

Behind the Price: On the Role of Agent’s Reflexivity in Financial Market Microstructure

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