Synthetic Markets Support Square-Root Impact and Order-Flow Predictions

Summary

This paper builds an artificial market from a previously proposed model of correlated metaorders and examines how price impact, order flow, and volatility interact. Its central premise is that metaorders move prices on average according to a square-root relationship with executed volume, and that the combined activity of correlated orders can account for price volatility.

The simulations reproduce the predicted relationship between generalized order flow and returns, which the authors say is also seen in empirical data. They further derive proxy metaorders from simulated trade flow and find that these proxies reproduce the square-root impact pattern. This offers support for using anonymized trades to estimate the impact of real metaorders. The evidence described is simulation based and supports the earlier model's approximations; it does not establish that the same mechanism fully explains volatility in every market or trading setting.

Key ideas

• The artificial market implements a model of correlated metaorders and their price effects.
• The model assumes average market impact grows with the square root of executed volume.
• Simulated generalized order flow and returns display the correlation structure predicted by the model.
• Proxy metaorders reconstructed from simulated trades reproduce the square-root impact relationship.
• The findings support tape-based impact estimation, while remaining evidence for a specific model.

Tags

# The Subtle Interplay between Square-root Impact, Order Imbalance & Volatility II: An Artificial Market Generator


# The Subtle Interplay between Square-root Impact, Order Imbalance & Volatility II: An Artificial Market Generator









This work extends and complements our previous theoretical paper on the subtle interplay between impact, order flow and volatility. In the present paper, we generate synthetic market data following the specification of that paper and show that the approximations made there are actually justified, which provides quantitative support our conclusion that price volatility can be fully explained by the superposition of correlated metaorders which all impact prices, on average, as a square-root of executed volume. One of the most striking predictions of our model is the structure of the correlation between generalized order flow and returns, which is observed empirically and reproduced using our synthetic market generator. Furthermore, we were able to construct proxy metaorders from our simulated order flow that reproduce the square-root law of market impact, lending further credence to the proposal made in Ref. [2] to measure the impact of real metaorders from tape data (i.e. anonymized trades), which was long thought to be impossible.

Shown in full with attribution under the source's licence. Licence: abstract CC0

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