Emperical Mode Decomposition (EMD) for stock data analyze

About

This method based on decomposing signal (natural analog signals or artificial stock pricing in that case) into Intrinsic Mode Functions (IMF)

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Quick Start

1. Clone the repo

   git clone https://github.com/Andy666Fox/emd_traiding.git

2. Check and install requiered dependencies

   uv/pip install -r requirements.txt

3. There may be problems installing the price_loaders package which is responsible for getting data from tradingview. In this case, you can drag it from here https://github.com/batprem/price-loaders

4. Entry point is get_data_slope() function with ticket argument

   get_data_slope("BTCUSDT")

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Docker

It's possible to run it in Docker. I spent a lot of time unifying the configurations, so just run

docker compose up -d --build

The UI will be available at localhost:80, the address for the API is localhost:80/api

If that doesn't work, the source code includes nginx configs and the configuration for each service. There's nothing particularly buggy there, so I'm almost certain everything will run without a hitch.

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Features

1. Easy data loading
2. Ability to customize IMF level
3. A negative slope value indicates a downward price movement, and the opposite is also true.

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EMD on wiki

EMD python library