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12 - The Impact of Metaorders

from PART V - PRICE IMPACT

Published online by Cambridge University Press:  26 February 2018

Jean-Philippe Bouchaud
Affiliation:
Capital Fund Management, Paris
Julius Bonart
Affiliation:
University College London
Jonathan Donier
Affiliation:
Capital Fund Management
Martin Gould
Affiliation:
CFM - Imperial Institute of Quantitative Finance
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Summary

It doesn't matter how beautiful your theory is, it doesn't matter how smart you are. If it doesn't agree with experiment, it's wrong.

(Richard P. Feynman)

In the previous chapter, we considered how the arrival of a single market order impacts the mid-price. However, as we noted in Section 10.5.1, most traders do not execute large trades via single market orders, but instead split up their trades into many small pieces. These pieces are executed incrementally, using market orders, limit orders, or both, over a period of several minutes to several days. As we saw in the last chapter, the chaining of market orders greatly affects their impact. Therefore, understanding the impact of a single market order is only the first step towards understanding the impact of trading more generally. To develop a more thorough understanding, we must also consider the impact of metaorders (defined in Section 10.4.3).

The empirical determination of metaorder impact is an important experiment whose results, when measured properly, are of great interest to academics, investors and market regulators alike. From a fundamental point of view, how does a metaorder of size Q contribute to price formation? From the point of view of investors, what is the true cost of performing such a trade? How does it depend on market conditions, execution strategies, time horizons, and so on? From the point of view of regulators, can large metaorders destabilise markets? Is marked-to-market accounting wise when, as emphasised above, the market price is (at best) only meaningful for infinitesimal volumes?

Naively, it might seem intuitive that the impact of a metaorder should scale linearly in its total size Q. Indeed, as we will discuss in this chapter, many simple models of price impact predict precisely a linear behaviour. Perhaps surprisingly, empirical analysis reveals that in real markets, this scaling is not linear, but rather is approximately square-root. Throughout this chapter, we present this square-root law of impact and discuss several of its important consequences.

Metaorders and Child Orders

Assume that a trader decides to buy or sell some quantity Q of a given asset. Ideally, the trader would like to buy or sell this whole quantity immediately, at the market price.

Type
Chapter
Information
Trades, Quotes and Prices
Financial Markets Under the Microscope
, pp. 229 - 244
Publisher: Cambridge University Press
Print publication year: 2018

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References

Loeb, T. F. (1983). Trading cost: The critical link between investment information and results. Financial Analysts Journal, 39, 39–44.CrossRefGoogle Scholar
Torre, N., & Ferrari, M. (1997). Market impact model handbook. BARRA Inc. Available at www.barra.com/newsletter/nl166/miminl166.asp.Google Scholar
Almgren, R., Thum, C., Hauptmann, E., & Li, H. (2005). Direct estimation of equity market impact. Risk, 18(5752), 10.Google Scholar
Kissel, R., & Malamut, R. (2006). Algorithmic decision-making framework. Journal of Trading, 1(1), 12–21.Google Scholar
Moro, E., Vicente, J., Moyano, L. G., Gerig, A., Farmer, J. D., Vaglica, G., & Mantegna, R. N. (2009). Market impact and trading profile of hidden orders in stock markets. Physical Review E, 80(6), 066102.CrossRefGoogle ScholarPubMed
Tóth, B., Lemperiere, Y., Deremble, C., De Lataillade, J., Kockelkoren, J., & Bouchaud, J. P. (2011). Anomalous price impact and the critical nature of liquidity in financial markets. Physical Review X, 1(2), 021006.CrossRefGoogle Scholar
Engle, R., Ferstenberg, R., & Russell, J. (2012). Measuring and modelling execution cost and risk. The Journal of Portfolio Management, 38(2), 14–28.Google Scholar
Mastromatteo, I., Tóth, B., & Bouchaud, J. P. (2014). Agent-based models for latent liquidity and concave price impact. Physical Review E, 89(4), 042805.CrossRefGoogle ScholarPubMed
Donier, J., & Bonart, J. (2015). A million metaorder analysis of market impact on the Bitcoin. Market Microstructure and Liquidity, 1(02), 1550008.CrossRefGoogle Scholar
Zarinelli, E., Treccani, M., Farmer, J. D., & Lillo, F. (2015). Beyond the square root: Evidence for logarithmic dependence of market impact on size and participation rate. Market Microstructure and Liquidity, 1(02), 1550004.CrossRefGoogle Scholar
Kyle, A. S., & Obizhaeva, A. A. (2016). Large bets and stock market crashes. https:// ssrn.com/abstract=2023776.
Bacry, E., Iuga, A., Lasnier,M., & Lehalle, C. A. (2015).Market impacts and the life cycle of investors orders. Market Microstructure and Liquidity, 1(02), 1550009.CrossRefGoogle Scholar
Tóth, B., Eisler, Z., & Bouchaud, J.-P. (2017). The short-term price impact of trades is universal. https://ssrn.com/abstract=2924029.
Several internal bank documents have also reported such a concave impact law, e.g.: Ferraris, A. (2008). Market impact models. Deutsche Bank internal document, http://dbquant.com/Presentations/Berlin200812.pdf.
Bershova, N., & Rakhlin, D. (2013). The non-linear market impact of large trades: Evidence from buy-side order flow. Quantitative Finance, 13(11), 1759–1778.CrossRefGoogle Scholar
Brokmann, X., Serie, E., Kockelkoren, J., & Bouchaud, J. P. (2015). Slow decay of impact in equity markets. Market Microstructure and Liquidity, 1(02), 1550007.CrossRefGoogle Scholar
Gomes, C., & Waelbroeck, H. (2015). Is market impact a measure of the information value of trades?Market response to liquidity vs. informed metaorders. Quantitative Finance, 15(5), 773–793.CrossRefGoogle Scholar
see also: Moro, E. et al.; Zarinelli, E. et al. in the previous subsection.
Zhang, Y. C. (1999). Toward a theory of marginally efficient markets. Physica A: Statistical Mechanics and Its Applications, 269(1), 30–44.CrossRefGoogle Scholar
Grinold, R. C., & Kahn, R. N. (2000). Active portfolio management. McGraw-Hill.Google Scholar
Gabaix, X., Gopikrishnan, P., Plerou, V., & Stanley, H. E. (2003). A theory of power-law distributions in financial market fluctuations. Nature, 423(6937), 267–270.CrossRefGoogle ScholarPubMed
Barato, A. C., Mastromatteo, I., Bardoscia, M., & Marsili, M. (2013). Impact of meta-order in the Minority Game. Quantitative Finance, 13(9), 1343–1352.CrossRefGoogle Scholar
Farmer, J. D., Gerig, A., Lillo, F., & Waelbroeck, H. (2013). How efficiency shapes market impact. Quantitative Finance, 13(11), 1743–1758.CrossRefGoogle Scholar
Mastromatteo, I., Tóth, B., & Bouchaud, J. P. (2014). Anomalous impact in reaction-diffusion financial models. Physical Review Letters, 113(26), 268701.CrossRefGoogle ScholarPubMed
Donier, J., Bonart, J., Mastromatteo, I., & Bouchaud, J. P. (2015). A fully consistent, minimal model for non-linear market impact. Quantitative Finance, 15(7), 1109–1121.CrossRefGoogle Scholar
Donier, J., & Bouchaud, J. P. (2016). From Walras auctioneer to continuous time double auctions: A general dynamic theory of supply and demand. Journal of Statistical Mechanics: Theory and Experiment, 2016(12), 123406.CrossRefGoogle Scholar
Pohl, M., Ristig, A., Schachermayer, W., & Tangpi, L. (2017). The amazing power of dimensional analysis: Quantifying market impact. arXiv preprint arXiv:1702.05434.
see also: K., Rodgers, https://mechanicalmarkets.wordpress.com/2016/08/15/priceimpact- in-efficient-markets/.

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