elvinwangyh's Stars
eugeneyan/open-llms
📋 A list of open LLMs available for commercial use.
jasonstrimpel/volatility-trading
A complete set of volatility estimators based on Euan Sinclair's Volatility Trading
qdrant/qdrant
Qdrant - High-performance, massive-scale Vector Database for the next generation of AI. Also available in the cloud https://cloud.qdrant.io/
sktime/sktime
A unified framework for machine learning with time series
isadoranun/FATS
alteryx/featuretools
An open source python library for automated feature engineering
blue-yonder/tsfresh
Automatic extraction of relevant features from time series:
georgebv/pyextremes
Extreme Value Analysis (EVA) in Python
AyrtonB/Merit-Order-Effect
Code and analysis used for calculating the merit order effect of renewables on price and carbon intensity of electricity markets
polakowo/vectorbt
Find your trading edge, using the fastest engine for backtesting, algorithmic trading, and research.
hootnot/oanda-api-v20
OANDA REST-V20 API wrapper. Easy access to OANDA's REST v20 API with oandapyV20 package. Checkout the Jupyter notebooks!
cerlymarco/MEDIUM_NoteBook
Repository containing notebooks of my posts on Medium
pat-alt/deepvars
Vector Autoregression augmented with deep learning.
srivastavaprashant/mgarch
DCC-GARCH(1,1) for multivariate normal distribution.
awesomedata/awesome-public-datasets
A topic-centric list of HQ open datasets.
antoinecarme/pyaf
PyAF is an Open Source Python library for Automatic Time Series Forecasting built on top of popular pydata modules.
Nixtla/statsforecast
Lightning ⚡️ fast forecasting with statistical and econometric models.
JerBouma/ThePassiveInvestor
Passive Investing for the Average Joe
andreachello/Applied-Econometric-Time-Series
A repository to explore the concepts of applied econometrics in the context of financial time-series.
open-risk/portfolioAnalytics
A Python library for generating analytic tests for credit portfolio loss distributions
open-risk/equinox
Equinox is an open source platform that supports the holistic risk management of sustainable finance projects
py-why/EconML
ALICE (Automated Learning and Intelligence for Causation and Economics) is a Microsoft Research project aimed at applying Artificial Intelligence concepts to economic decision making. One of its goals is to build a toolkit that combines state-of-the-art machine learning techniques with econometrics in order to bring automation to complex causal inference problems. To date, the ALICE Python SDK (econml) implements orthogonal machine learning algorithms such as the double machine learning work of Chernozhukov et al. This toolkit is designed to measure the causal effect of some treatment variable(s) t on an outcome variable y, controlling for a set of features x.
matheusfacure/python-causality-handbook
Causal Inference for the Brave and True. A light-hearted yet rigorous approach to learning about impact estimation and causality.
uber/causalml
Uplift modeling and causal inference with machine learning algorithms
python-poetry/poetry
Python packaging and dependency management made easy
rstudio/bookdown
Authoring Books and Technical Documents with R Markdown
cerlymarco/tspiral
A python package for time series forecasting with scikit-learn estimators.
Topaceminem/DCC-GARCH
DCC GARCH modeling in Python
Crunch-UQ4MI/neuraluq
jankrepl/deepdow
Portfolio optimization with deep learning.