Nonlinear price impact from linear models.
Summary
The impact of trades on asset prices is a crucial aspect of market dynamics
for academics, regulators and practitioners alike. Recently, universal and
highly nonlinear master curves were observed for price impacts aggregated on
all intra-day scales [1]. Here we investigate how well these curves, their
scaling, and the underlying return dynamics are captured by linear "propagator"
models. We find that the classification of trades as price-changing versus
non-price-changing can explain the price impact nonlinearities and short-term
return dynamics to a very high degree. The explanatory power provided by the
change indicator in addition to the order sign history increases with
increasing tick size. To obtain these results, several long-standing technical
issues for model calibration and -testing are addressed. We present new
spectral estimators for two- and three-point cross-correlations, removing the
need for previously used approximations. We also show when calibration is
unbiased and how to accurately reveal previously overlooked biases. Therefore,
our results contribute significantly to understanding both recent empirical
results and the properties of a popular class of impact models.Comment: Companion paper to [1]: arXiv:1706.0416.
Publisher
IOP Publishing
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