DeepSurrogatepin 0.12

Deep surrogate model for the probability of informed trading model

Master thesis: Deep Structural estimation: with an application to market microstructure modelling

This package proposes an easy application of the master thesis: "Deep Structural estimation: with an application to market microstructure modelling"

Authors

• Guillaume Pavé (HEC Lausanne,[e-mail])

Supervisors

• Simon Scheidegger (Department of Economics, HEC Lausanne, [e-mail])
• Antoine Didisheim (Swiss Finance Institute, [e-mail])

Instructions

1. Download parameters of the surrogate (https://drive.google.com/drive/folders/1RTtYqOipJ-OJpveLu9Ui9NbYGvCDJtNL?usp=sharing)
2. Create a folder "model_save" and put parameters inside
3. Download training datatset "simulation_data_PIN.txt" from https://drive.google.com/file/d/1iUR-Zsd_UAo8bnZEMh5hpQ0SjYtpmtQA/view?usp=sharing
4. Create a folder "data" and put the dataset inside.
5. Now, you can use the train dataset or you could generate your own dataset (https://github.com/edwinhu/pin-code)

Github project is available at: https://github.com/GuillaumePv/pin_surrogate_model If you find bugs, do not hesitate to create Issues inside of the github project.