https://github.com/lnshuti/meta-labelling-architecture
Automated Trading Strategy deployed to AWS
https://github.com/lnshuti/meta-labelling-architecture
aws lambda python
Last synced: 11 months ago
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Automated Trading Strategy deployed to AWS
- Host: GitHub
- URL: https://github.com/lnshuti/meta-labelling-architecture
- Owner: LNshuti
- License: mit
- Created: 2023-04-08T01:22:09.000Z (about 3 years ago)
- Default Branch: main
- Last Pushed: 2024-03-19T02:50:51.000Z (over 2 years ago)
- Last Synced: 2025-03-28T05:22:37.414Z (over 1 year ago)
- Topics: aws, lambda, python
- Language: Jupyter Notebook
- Homepage:
- Size: 1.19 MB
- Stars: 3
- Watchers: 3
- Forks: 1
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
## Meta Labeling
Deploy a full stack application that automatically downloads live Bitcoin prices from an exchange such as CoinmarketCap. Use Advanced ML forecasting methods to build a trading strategy based on ensemble modeling. Backtest strategy.
### Null Hypothesis
------------------------------------
There exists alpha in developing and deploying a custom trading bot using an ensemble model and experimenting with proprietary datasets.
This collaborative project aims to examine this hypothesis. We will build a full-stack application following software engineering and MLOPS best practices with **the goal of disproving our null hypothesis**.
**Team:**
------------------------------------
* Leonce
* Indrit
* Dipta
* You?
**Disclaimer: This is for Educational Purposes Only.**
**Models taken into consideration:**
------------------------------------
* Moving Average Crossover Strategy: When the short-term moving average crosses above the long-term moving average, that indicates a positive trend and hence a buy. If it crosses from the top down, it is a short signal.
* Minervini Trend Filter
* Hedgefundie's Ultimate Adventure
* Antonacci Dual Momentum
* Radge ADX Day Trade
* Radge BBO
* Radge Weekend Trend Trader
* Bensdorp books
* Connors' 7 day high/low
**Figure 1. Meta Labeling Architecture.**
# How to create architecture diagram using Drawio in VSCode
[here](https://www.loom.com/share/f96d2241e6b54d81a529ea2527c776ae)
# How to access BTC data
We use **OpenBB Terminal**, an incredible open-source [library](https://my.openbb.co/app/sdk) that provides APIs for accessing prices, news, data, and models. A comparable commercial tool is the Bloomberg Terminal.
Follow Installation instructions from OpenBB's [website](https://my.openbb.co/app/sdk/installation)
# How to use the code
```python
# Step 1: Clone the repo
https://github.com/LNshuti/meta-labelling-architecture.git
# Step 2: Create an isolated environment to manage dependencies
conda env create --file=environment.yaml
# Step 3: install required Python packages
pip install -r requirements.txt
## Install the OpenBB python package from PIP
pip install openbb
# Step 4: Open openbb using the terminal command
$ openbb
# Get Historical Bitcoin Prices
$ historical --ticker BTC
```
**Commonly used Ticker mapping**
```python
| Ticker | Name |
|--------|--------------|
| BTC | Bitcoin |
| ETH | Ether |
```
**References**
1. Marcos Lopez de Prado. Advances in Financial Machine Learning. Lopez de Prado, M. (2018). Advances in Financial Machine Learning. United Kingdom: Wiley.
2. Chip Huyen. Designing Machine Learning Systems. An Iteative Process for Production Ready Application.