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Measuring price impact and information content of trades in a time-varying setting

F. CampigliG. BormettiF. Lillo
Dec 2022
The estimation of market impact is crucial for measuring the informationcontent of trades and for transaction cost analysis. Hasbrouck's (1991) seminalpaper proposed a Structural-VAR (S-VAR) to jointly model mid-quote changes andtrade signs. Recent literature has highlighted some pitfalls of this approach:S-VAR models can be misspecified when the impact function has a non-linearrelationship with the trade sign, and they lack parsimony when they aredesigned to capture the long memory of the order flow. Finally, theinstantaneous impact of a trade is constant, while market liquidity highlyfluctuates in time. This paper fixes these limitations by extending Hasbrouck'sapproach in several directions. We consider a nonlinear model where we use aparsimonious parametrization allowing to consider hundreds of past lags.Moreover we adopt an observation driven approach to model the time-varyingimpact parameter, which adapts to market information flow and can be easilyestimated from market data. As a consequence of the non-linear specification ofthe dynamics, the trade information content is conditional both on the locallevel of liquidity, as modeled by the dynamic instantaneous impact coefficient,and on the state of the market. By analyzing NASDAQ data, we find that impactfollows a clear intra-day pattern and quickly reacts to pre-scheduledannouncements, such as those released by the FOMC. We show that this fact hasrelevant consequences for transaction cost analysis by deriving an expressionfor the permanent impact from the model parameters and connecting it with thestandard regression procedure. Monte Carlo simulations and empirical analysessupport the reliability of our approach, which exploits the completeinformation of tick-by-tick prices and trade signs without the need foraggregation on a macroscopic time scale.