13 research outputs found
The nature of price returns during periods of high market activity
By studying all the trades and best bids/asks of ultra high frequency
snapshots recorded from the order books of a basket of 10 futures assets, we
bring qualitative empirical evidence that the impact of a single trade depends
on the intertrade time lags. We find that when the trading rate becomes faster,
the return variance per trade or the impact, as measured by the price variation
in the direction of the trade, strongly increases. We provide evidence that
these properties persist at coarser time scales. We also show that the spread
value is an increasing function of the activity. This suggests that order books
are more likely empty when the trading rate is high.Comment: 17 pages, 11 figure
Uncovering Causality from Multivariate Hawkes Integrated Cumulants
We design a new nonparametric method that allows one to estimate the matrix
of integrated kernels of a multivariate Hawkes process. This matrix not only
encodes the mutual influences of each nodes of the process, but also
disentangles the causality relationships between them. Our approach is the
first that leads to an estimation of this matrix without any parametric
modeling and estimation of the kernels themselves. A consequence is that it can
give an estimation of causality relationships between nodes (or users), based
on their activity timestamps (on a social network for instance), without
knowing or estimating the shape of the activities lifetime. For that purpose,
we introduce a moment matching method that fits the third-order integrated
cumulants of the process. We show on numerical experiments that our approach is
indeed very robust to the shape of the kernels, and gives appealing results on
the MemeTracker database
First- and Second-Order Statistics Characterization of Hawkes Processes and Non-Parametric Estimation
The nature of price returns during periods of high market activity
By studying all the trades and best bids/asks of ultra high frequency snapshots recorded from the order books of a basket of 10 futures assets, we bring qualitative empirical evidence that the impact of a single trade depends on the intertrade time lags. We find that when the trading rate becomes faster, the return variance per trade or the impact, as measured by the price variation in the direction of the trade, strongly increases. We provide evidence that these properties persist at coarser time scales. We also show that the spread value is an increasing function of the activity. This suggests that order books are more likely empty when the trading rate is high.