This project is all about the visualization and quant strategy testing for the cryptocurrency market. It allows you to follow the market as closely as possible in real-time, while giving you full control over incoming financial data.

Its very simple to get started. Just clone/download this repository onto your computer.

How to run?

System pre-requesits:

• pipenv,
• Python version 3+,
• Have the dependecies installed (outlined below)

Now, once you got the pre-requisits, run the following in inside the folder

• pipenv shell to start the virtual enviroment,
• install the dependecies into your dev list, from the Pipfile.lock file, using pipenv install --ignore-pipfile --dev,
• that is it!

This project uses

• pandas
• numpy
• matplotlib
• binance

All of which can be found in the Pipfile.lock file.

This project works in the following way:

#1. First, you get the Historical data for a particular period in time from available API Available Exchanges:

• Binance

#2. Parse the gathered data into the strategy simulator, for constructing a table (dataframe) with necessary details, to be used for further analysis.

#3. Pass the strategy specific table (dataframe), into the risk_management() method, to calculate the necessary risk assessment for the respective strategy table (dataframe).

#4. After the strategy has been risk analysed thoroughly, the metrics + the strategy ID are saved/appended to a list of risk_metrics which can then be saved into a target file.

#5. The strategy signals are saved into a JSON file for future further analysis.

• x2 SMA Cross
• x2 EMA Cross

hist_data/ -> contains a snapshot of historical data in JSON format from a target exchange for a particular trading market pair/ticker.

instance/ -> contains local files that are to be filled out and used on a local machine, such as: secret keys, api keys, etc.

other/ -> contains random code used thorughout the project that may or may not be useful in the future.

results/ -> contains the strategy processed output data in JSON format from strategy/, genereated from any target hist_data/ JSON file.

strategy/ -> contains all target and/or experimental strategies used in the project, for testing and validation.

out.json -> contains the strategy processed output data in JSON format from strategy/, genereated from any target hist_data/ JSON file.

main.py -> contains all of the main logic to orchistrate the project from one single file, with stuff like: variables, main, etc.

MarektOnClosePortfolio.py -> contains the backtesting for a strategy dataframe (df) for tracing and tracking the performance of the stratey using real trading values and variables.

This is a flow diagram with represntaition of how the poroject flows and works: