
on Market Microstructure 
By:  Felix Patzelt; JeanPhilippe Bouchaud 
Abstract:  How and why stock prices move is a centuriesold question still not answered conclusively. More recently, attention shifted to higher frequencies, where trades are processed piecewise across different timescales. Here we reveal that price impact has a universal nonlinear shape for trades aggregated on any intraday scale. Its shape varies little across instruments, but drastically different master curves are obtained for ordervolume and sign impact. The scaling is largely determined by the relevant Hurst exponents. We further show that extreme order flow imbalance is not associated with large returns. To the contrary, it is observed when the price is "pinned" to a particular level. Prices move only when there is sufficient balance in the local order flow. In fact, the probability that a trade changes the midprice falls to zero with increasing (absolute) ordersign bias along an arcshaped curve for all intraday scales. Our findings challenge the widespread assumption of linear aggregate impact. They imply that market dynamics on all intraday timescales are shaped by correlations and bilateral adaptation in the flows of liquidity provision and taking. 
Date:  2017–06 
URL:  http://d.repec.org/n?u=RePEc:arx:papers:1706.04163&r=mst 
By:  Massil Achab; Emmanuel Bacry; JeanFran\c{c}ois Muzy; Marcello Rambaldi 
Abstract:  We introduce a new non parametric method that allows for a direct, fast and efficient estimation of the matrix of kernel norms of a multivariate Hawkes process, also called branching ratio matrix. We demonstrate the capabilities of this method by applying it to highfrequency order book data from the EUREX exchange. We show that it is able to uncover (or recover) various relationships between all the first level order book events associated with some asset when mapped to a 12dimensional process. We then scale up the model so as to account for events on two assets simultaneously and we discuss the joint highfrequency dynamics. 
Date:  2017–06 
URL:  http://d.repec.org/n?u=RePEc:arx:papers:1706.03411&r=mst 
By:  S\"uhan Altay; Katia Colaneri; Zehra Eksi 
Abstract:  We consider an investor faced with the utility maximization problem in which the risky asset price process has purejump dynamics affected by an unobservable continuoustime finitestate Markov chain, the intensity of which can also be controlled by actions of the investor. Using the classical filtering theory, we reduce this problem with partial information to one with full information and solve it for logarithmic and power utility functions. In particular, we apply control theory for piecewise deterministic Markov processes (PDMP) to our problem and derive the optimality equation for the value function and characterize the value function as the unique viscosity solution of the associated dynamic programming equation. Finally, we provide a toy example, where the unobservable state process is driven by a twostate Markov chain, and discuss how investor's ability to control the intensity of the state process affects the optimal portfolio strategies as well as the optimal wealth under both partial and full information cases. 
Date:  2017–06 
URL:  http://d.repec.org/n?u=RePEc:arx:papers:1706.03567&r=mst 