kurucan Goto Github PK

electric-load-forecasting-with-recency-effect

Paper reproduce of "Electric load forecasting with recency effect"

empirical-asset-pricing-via-machine-learning-evidence-from-the-german-stock-market

Machine learning methods for identifing investment factors

empirical_asset_pricing_via_boosting

Stock risk premium prediction via FM/ EXT/ GBDT/ XGB/LBGM. Mengxuan Chen's graduation thesis at WHU.

ensemble-pytorch

Implementation of ensemble methods in Pytorch to boost the performance of your model.

ensemblerl

entity-embedding-rossmann

ep-chan-book-algo-trading

Recreate EP Chan algo trading book strategies

epex-machine-learning

Define a strategy to trade between day ahead and intraday electricity markets with the help of machine learning models

epftoolbox

An open-access benchmark and toolbox for electricity price forecasting

es-rnn

es-rnn-pytorch

This is a work in progress Pytorch implementation of the recently proposed ES-RNN by Slawek Smyl, winner of the M4 competition

esrnn

Hybrid ES-RNN models for time series forecasting

esrnn-gpu

PyTorch GPU implementation of the ES-RNN model for time series forecasting

etc3550slides

Slides for a forecasting course based on "Forecasting: Principles and Practice"

evaluatingensemblepostprocessing

evds

TCMB tarafından yayımlanan istatistiki verilere python aracılığıyla erişmenize imkan sağlar.

event-driven-stock-prediction-using-deep-learning

A deep learning method for event driven stock market prediction. Deep learning is useful for event-driven stock price movement prediction by proposing a novel neural tensor network for learning event embedding, and using a deep convolutional neural network to model the combined influence of long-term events and short-term events on stock price movements

evolutionaryforest

An open source python library for automated feature engineering based on Genetic Programming

examples

Example deep learning projects that use wandb's features.

excel

Transforming Excel Analysis into Python and pandas Data Models

factor-models-machine-learning-and-asset-pricing-

Recent methodological contributions in asset pricing using factor models and machine learning. I presented Giglio et al. (2021) paper during Econometrics and ML reading group.

fama-french-portfolio-construction

Constructing Fama French Three Factors 6 Portfolios for SMB and HML

fama_french

famafrench

Implementation of 5-factor Fama French Model

famafrench-1

Python package designed to construct and replicate datasets from Ken French's online library by accessing WRDS remotely through its cloud server "wrds-cloud".

feature-engineering-for-time-series-forecasting

featureengineering

The repository showcases feature engineering for finance data and use of automated libraries

fin-ml

This github repository contains the code to the case studies in the O'Reilly book Machine Learning and Data Science Blueprints for Finance

financeandpython.com-corporatefinance

financeops

Research in investment finance with Python Notebooks