We derive an explicit solution for deterministic market impact parameters in the Graewe and Horst (2017) portfolio liquidation model. The model allows to combine various forms of market impact, namely instantaneous, permanent and temporary. We show that the solutions to the two benchmark models...

Functional time series and high-dimensional scalar predictors frequently arise ina wide range of modern economic and business applications, which require statisticalmodels that can simultaneously handle the temporal and causal dependence that areprevalent in large sets of mixed-type data. We...

We propose a reinforcement learning (RL) framework to solve the HJB equations of optimal market making with the presence of rebate. As a numerical solution, the RL algorithm successfully mirrors the analytical solutions under the scheme of no rebate and constant rebate. Under the time-dependent...

Motivated by the category-learning behavior, we propose to use Topic Appearance Probability (TAP) in the financial news as an alternative measure of investor attention. We then investigate the relationship between the investor attention, measured by the widely used the Google Search Volume Index...

Understanding multi-market interactions and identifying leading markets in the global financial network is of interest to investors, regulators and policymakers. To discover the essential dynamic dependencies of digital currency exchanges, we propose TriSNAR, a three-layer sparse estimator for...

In this paper we propose the GHADA risk management model that is based on the generalized hyperbolic (GH) distribution and on a nonparametric adaptive methodology. Compared to the normal distribution, the GH distribution possesses semi-heavy tails and represents the financial risk factors more...