Market Impact: Cost of Trading and Limits of Strategy Size

Blog Post by Best Fin Investment



Close-up of coins, calculator, and numerical tables on paper, illustrating the concept of market impact and financial analysis.

Table of Contents:


Introduction:
Market Impact refers to the effect that a trade or series of trades has on the price of an asset. When an investor executes a trade, the transaction can cause the asset's price to move, either up or down, depending on whether the trade is a buy or sell order. This effect occurs because the act of trading changes the supply and demand dynamics in the market. Market impact is a key consideration in trading strategies, especially for large trades, as it can lead to additional costs and influence the overall execution price. In this blog post, we will explore the multifaceted aspects of market impact, examining how trade size, order flow, and market conditions collectively influence price dynamics.

Metaorder:
A so-called metaorder refers to a large, often institutionally-driven order that is executed incrementally over time, rather than all at once. The concept is central to understanding market impact, which is the effect that a trade has on the market price of the asset being traded. Meta orders are broken down into smaller, manageable pieces, known as child orders, and executed gradually to minimize market impact and avoid alerting other market participants.

Decomposing Market Impact - Reaction vs. Prediction:
Professor J.P. Bouchaud describes this decomposition of market impact into two components:
- The reaction impact which describes how an action directly affects future prices.
- The prediction impact which describes what would have happened anyway, even in the absence of the action.
The sum of reaction impact and prediction impact will correspond to the observed impact, as measurable by an outside observer [3].

Understanding the Square Root Law of Market Impact for Metaorders:
As empirically observed by Professor J.P. Bouchaud [3] "the peak impact of a metaorder with volume q is an approximate function of the square root of q/VT (for q/VT < 10%) where VT is the contemporaneous volume traded over period T with T the time horizon on which the metaorder is being executed (for T in the order of days)." Hence the peak impact moves with the square root of a metaorder volume, and thus not linearly as popularized by the famous Kyle model [4].
This means that even relatively small metaorders cause surprisingly large impact [1,3], and as stated by Professor J.P. Bouchaud "executing 1% of the daily volume moves the price on average by sqrt(1%) = 10% of its daily volatility". Note also that a metaorder impact is not additive, one finds empirically that the second half of a metaorder impacts the price much less than the first half [3].

Impact of Trade Sequence on Prices:
The price impact of a trade is not only a factor of the trade size but also depends on the sequence of past price changes and order flows. This indicates that the context within which a trade occurs (e.g., following a sequence of buys or sells) can significantly affect the resulting price impact [5].

Strategy Considerations:
The market impact is a crucial factor in the cost of trading and limits the size of trading strategies. It further highlights the complexity of predicting market reactions and planning trade sizes accordingly [2]. As pointed out by Professor J.P. Bouchaud [3] "the impact costs represent the lion's share of costs for moderate to large metaorders. For example when trading 1% of the daily traded volume on a stock with a 2% daily volatility, the square-root law estimates the impact to be about 15 basis points. This is an order of magnitude larger than direct costs and spread costs which are often in the order of 1 basis point." Therefore, modeling impact is critical to devising good execution strategies. This is also one of the reasons why institutional trades may take several days or even several weeks to be completed.

Conclusion:
Understanding market impact is crucial for anyone engaged in trading activities. This knowledge not only helps in anticipating how trades might influence market prices but also assists in the formulation and execution of more effective trading strategies. As financial markets continue to evolve, the ability to analyze and adapt to the dynamics of market impact will remain a valuable skill, enabling traders to minimize cost and mitigate risks.


References:

[1] BARRA, "Market Impact Model Handbook", BARRA Inc., Berkeley, 1997.
[2] Bouchaud J.P., "The endogenous dynamics of markets: price impact, feedback loops and instabilities", Lessons from the credit crisis, pp.345-74, 2011.
[3] Bouchaud J.P., Bonart J., Donier J., Gould M., "Trades, Quotes and Prices: Financial Markets Under the Microscope", Cambridge University Press, 2018.
[4] Kyle A.S., "Continuous auctions and insider trading." Econometrica, vol. 53, pp. 1315-1335, 1985.
[5] Lo A.W., MacKinlay A.C., "A Non-Random Walk Down Wall Street", Princeton University Press, 1999.



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