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on Market Microstructure |
| By: | Alexander Wehrli (ETH Zürich); Spencer Wheatley (ETH Zürich); Didier Sornette (ETH Zürich - Department of Management, Technology, and Economics (D-MTEC); Swiss Finance Institute) |
| Abstract: | The statistical estimate of the branching ratio η of the Hawkes model, when fitted to windows of mid-price changes, has been reported to approach criticality (η = 1) as the fitting window becomes large. In this study -- using price changes from the EUR/USD currency pair traded on the Electronic Broking Services (EBS) interbank trading platform and the S&P 500 E-mini futures contract traded at the Chicago Mercantile Exchange (CME) -- it is shown that the estimated branching ratio depends little upon window size and is usually far from criticality. This is done by controlling for exogenous non-stationarities/heterogeneities at inter- and intraday scales, accomplished by using information criteria to select the degree of flexibility of the Hawkes immigration intensity, either piecewise constant or adaptive logspline, estimated using an expectation maximization (EM) algorithm. The bias incurred by keeping the immigration intensity constant is small for time scales up to two hours, but can become as high as 0.3 for windows spanning days. This emphasizes the importance of choosing an appropriate model for the immigration intensity in the application of Hawkes processes to financial data and elsewhere. The branching ratio is also found to have an intraday seasonality, where it appears to be higher during times where market activity is dominated by supposedly reflexive automated decisions and a lack of fundamental news and trading. The insights into the microstructure of the two considered markets derived from our Hawkes process fits suggest that equity futures exhibit more complex non-stationary features, are more endogenous, persistent and traded at higher speed than spot foreign exchange. We complement our point process study with EM-estimates of integer-valued autoregressive (INAR) time series models at even longer scales of months. Transferring our methodologies to the aggregate bin-count setting confirms that even at these very long scales, criticality can be rejected. |
| Keywords: | Hawkes process; Integer-valued autoregressive process; Econometrics; High frequency financial data; Market microstructure; Spurious inference; Nonstationarity; EM algorithm |
| JEL: | C01 C40 C52 |
| Date: | 2020–05 |
| URL: | http://d.repec.org/n?u=RePEc:chf:rpseri:rp2039&r=all |
| By: | Antoine Fosset (LadHyX - Laboratoire d'hydrodynamique - X - École polytechnique - CNRS - Centre National de la Recherche Scientifique); Jean-Philippe Bouchaud (CFM - Capital Fund Management - Capital Fund Management); Michael Benzaquen (LadHyX - Laboratoire d'hydrodynamique - X - École polytechnique - CNRS - Centre National de la Recherche Scientifique) |
| Abstract: | Empirical data reveals that the liquidity flow into the order book (depositions, cancellations andmarket orders) is influenced by past price changes. In particular, we show that liquidity tends todecrease with the amplitude of past volatility and price trends. Such a feedback mechanism inturn increases the volatility, possibly leading to a liquidity crisis. Accounting for such effects withina stylized order book model, we demonstrate numerically that there exists a second order phasetransition between a stable regime for weak feedback to an unstable regime for strong feedback,in which liquidity crises arise with probability one. We characterize the critical exponents, whichappear to belong to a new universality class. We then propose a simpler model for spread dynamicsthat maps onto a linear Hawkes process which also exhibits liquidity crises. If relevant for thereal markets, such a phase transition scenario requires the system to sit below, but very close tothe instability threshold (self-organised criticality), or else that the feedback intensity is itself timedependent and occasionally visits the unstable region. An alternative scenario is provided by a classof non-linear Hawkes process that show occasional "activated" liquidity crises, without having to bepoised at the edge of instability. |
| Date: | 2020–05–07 |
| URL: | http://d.repec.org/n?u=RePEc:hal:wpaper:hal-02567495&r=all |
| By: | Valerio Volpati (CEA Paris Saclay - CEA - Commissariat à l'énergie atomique et aux énergies alternatives); Michael Benzaquen (LadHyX - Laboratoire d'hydrodynamique - X - École polytechnique - CNRS - Centre National de la Recherche Scientifique); Zoltán Eisler; Iacopo Mastromatteo (SISSA / ISAS - Scuola Internazionale Superiore di Studi Avanzati / International School for Advanced Studies); Bence Tóth; Jean-Philippe Bouchaud (CFM - Capital Fund Management - Capital Fund Management) |
| Abstract: | Crowding is most likely an important factor in the deterioration of strategy performance, the increase of trading costs and the development of systemic risk. We study the imprints of crowding on both anonymous market data and a large database of metaorders from institutional investors in the U.S. equity market. We propose direct metrics of crowding that capture the presence of investors contemporaneously trading the same stock in the same direction by looking at fluctuations of the imbalances of trades executed on the market. We identify significant signs of crowding in well known equity signals, such as Fama-French factors and especially Momentum. We show that the rebalancing of a Momentum portfolio can explain between 1-2% of order flow, and that this percentage has been significantly increasing in recent years. |
| Keywords: | market microstructure,momentum,equity factors,crowding |
| Date: | 2020–05–07 |
| URL: | http://d.repec.org/n?u=RePEc:hal:wpaper:hal-02567503&r=all |
| By: | Craig Burnside; Mario Cerrato; Zhekai Zhang |
| Abstract: | This paper proposes a set of novel pricing factors for currency returns that are mo- tivated by microstructure models. In so doing, we bring two strands of the exchange rate literature, namely market-microstructure and risk-based models, closer together. Our novel factors use order fl ow data to provide direct measures of buying and selling pressure related to carry trading and momentum strategies. We find that they appear to be good proxies for currency crash risk. Additionally, we show that the association between our order-fl ow factors and currency returns differs according to the customer segment of the foreign exchange market. In particular, it appears that financial cus- tomers are risk takers in the market, while non-financial customers serve as liquidity providers. |
| Keywords: | foreign, exchange, order fl ow, risk factor. |
| JEL: | E44 E51 F3 F4 G21 |
| Date: | 2018–10 |
| URL: | http://d.repec.org/n?u=RePEc:gla:glaewp:2018_04&r=all |