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backtesting-de-value-at-risk

data-science-ipython-notebooks

Data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe, Keras), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce, HDFS), matplotlib, pandas, NumPy, SciPy, Python essentials, AWS, and various command lines.

data_management_with_sas

This repository present the basic SAS command you need for data management, analysis or preparation tasks.

datavisualisation-on-financial-stocks

Using Dash to visualise and apply machine learning model on S&P 500 stocs

detect-hft-traders-machine-learning-

This work is part of a challenge of the French Financial Markets Authority organized by the Ecole Normale Supérieure, whose goal is to build a machine learning model for the detection of high frequency traders. Beyond a good model with a maximum score of true positives, the goal is to define the major variables that make the difference between HFT, Non HFT and MIX

economy

forecasting

Forecasting an unuivariate time series using R

markowitz_python

Dans ce notebook, j'implémente les différentes formulations (rendement cible, risque fixé, approche avec pénalisation) de la théorie de Markowitz (1990) sous le langage python, pour l'optimisation d'un portefeuille d'actifs

pyspark

Spark in python

python_basics

Basics python for finance