This repository contains a Jupyter Notebook for analyzing historical cryptocurrency data to detect potential pump and dump events. The detection algorithm considers price and trading volume changes, along with a customizable moving average window. The notebook uses data from the CoinGecko API.
Note: This analysis was generated using OpenAI's ChatGPT, an AI language model.
- Analyzes historical data for any cryptocurrency available on CoinGecko.
- Considers price and trading volume changes to identify potential pump and dump events.
- Customizable threshold parameters and moving average window.
- Generates a plot of the cryptocurrency's price history with detected pump and dump events.
- Python 3.7 or higher
- Pandas
- NumPy
- Matplotlib
- Requests
- Clone the repository:
git clone https://github.com/Keoooo/crypto-pump-and-dump-detection.git
-
Change the
coin_id
variable in the Jupyter Notebook to the desired cryptocurrency's CoinGecko ID (e.g., "bitcoin" for Bitcoin). -
Adjust the
price_threshold
,volume_threshold
, andmoving_average_window
variables in the notebook to fine-tune the detection of pump and dump events. -
Run the Jupyter Notebook to analyze the historical data and visualize the results.
This analysis was generated by an AI language model (OpenAI's ChatGPT) and may not capture all true pump and dump events accurately. The provided code and results should be used for educational purposes only and should not be considered as financial advice. Always do your own research before making any investment decisions.