Deep surrogate model for the probability of informed trading model
Project description
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"
The figure above shows the log-likelihood value of the PIN model (left) and the Deep-Surrogate (right)
Authors
- Guillaume Pavé (guillaumepave@gmail.com)
Supervisors
- Simon Scheidegger (Department of Economics, HEC Lausanne, simon.scheidegger@unil.ch)
- Antoine Didisheim (Swiss Finance Institute, antoine.didisheim@unil.ch)
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distributions
No source distribution files available for this release.See tutorial on generating distribution archives.
Built Distribution
File details
Details for the file DeepSurrogatepin-0.11-py3-none-any.whl
.
File metadata
- Download URL: DeepSurrogatepin-0.11-py3-none-any.whl
- Upload date:
- Size: 10.0 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/4.0.1 CPython/3.8.1
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | 2f49c8bcc5a861dd629cf0b379f7c1a1f0f781ad39cec5b02a4307e637de8e71 |
|
MD5 | e6d0919d2700a949f1a7a230f3717006 |
|
BLAKE2b-256 | bedcdc90992c97e53110201f873c480288c6efec081d1d76ca7e4441eae47572 |