This is the official quantitative and statistical software package by W.Y.N. Associates, LLC or WYN Associates. Artificial Intelligence (AI) is the logical extension of human will. At WYN, we investigate marketable securities through not only the lens of human experience but also by machine power to discover the undiscovered intrinsic value of securities.
- Copyright © Official quantitative and statistical software published by WYN Associates.
- Copyright © 2010 – Present Yiqiao Yin
- Contact: Yiqiao Yin
- Official Site: https://www.WYN-Associates.com
- Email: Yiqiao.Yin@wyn-associates.com
Welcome to install our package. The entire package is written in python. One can use the following code to install this Github package. In some scenarios, it might be more optimal to install the package in a virtual environment. We recommend to set up a docker container by uisng this instruction manual. In other scenarios such as using Colab or AWS Sagemaker Studio, the following code can be used directly.
# from command line (through powershell)
pip install git+https://github.com/yiqiao-yin/WYNAssociates.git
# from jupyter
!pip install git+https://github.com/yiqiao-yin/WYNAssociates.git
For developers, one can clone package by simple git clone command (assuming in a desired directory).
git clone https://github.com/yiqiao-yin/WYNAssociates.git
Then go into the WYNAssociates folder.
cd WYNAssociates
Make sure to create your virtual environment.
virtualenv .some_name
Or use
python -m virtualenv .some_name
Please install the requirements.
pip install -r requirements.txt
Last, you can directly install the package.
pip install .
Do not forget to deactivate virtual environment when you are done.
deactivate
- A sample notebook for RNN education can be found here. We provide some basic education of Recurrent Neural Network (aka Long Short-Term Memory). The term Recurrent Neural Network is short for RNN and Long Short-Term Memory is short for LSTM.
There are three global sections of AI-driven solutions in our enterprise. They are listed below.
- AI_solution - The module contains deployable functions of a variety of different solutions in representation learning.
- FIN_solution - The module contains deployable functions in financial technology.
- ML_solution - The module contains machine learning or ML-driven tools.
| AI Solution | Definition |
|---|---|
| NN3 | LeNet3-style neural network |
| NeuralNet Regressor | Generalized code for neural network based regressor |
| NeuralNet Classifier | Generalized code for neural network based classifier |
| LSTM Regressor | A generalized code for developing sequential models |
| U-Net Model | Inception-style image segmentation model |
| Financial Solution | Definition |
|---|---|
| Yin Timer | A timing algorithm proprietary at W.Y.N. Associates |
| RSI Timer | A timing algorithm based on technical indicator RSI |
| RNN Regressor | A recurrent neural network for stock specifically |
| Neural Sequence Translation | A sequence-to-sequence model for stock data |
| Automated Neural Sequence Translation | A sequence-to-sequence model for tabular data |
| Machine Learning Solution | Definition |
|---|---|
| Logistic Classifier | Logistic-based classifier |
| K-Nearest Neighbors Classifier | K Nearest Neighborhood based classifier |
| Decision Tree Classifier | Decision Tree classifier |
| Decision Tree Regressor | Decision Tree regressor |
| Random Forest Classifier | Random Forest classifier |
| Random Forest Regressor | Random Forest regressor |
| Gradient Boosting Classifier | Gradient Boosting classifier |
| Gradient Boosting Regressor | Gradient Boosting regressor |
| Support Vector Machine Regressor | Support Vector Machine regressor |
| Adam Regressor | A general code for fitting tabgular data using Adam optimization |
| Area-Under-Curve and Receiver-Operating-Characteristics | An efficient function of calculating AUC and plotting ROC |