Several trading strategies with Python
Students: Antonio Antona, Emanuele Fogliati, Riccardo Iacueo
The project is divided in four parts. In the first we created a class to import financial data from Binance.com of one or more cryptocurrencies using the site's API, then display the results on the Jupyter notebook and manipulate the data for our purpose. In the second part we presented a Mean Reverting Trading Strategy (in our case we used Ethereum and Bitcoin, but both can be substituted by other currencies by simply changing the imputs).
In the third part we run a Classical Linear Regression Model (CLRM) to see if there was any linear relationship between two cryptocurrency (also there we used Ethereum and Bitcoin, but both can be substituted by other currencies) and we also run unit root test to see if there was stationary or at least mean reverting properties on our data sample.
And finally we show another automatic strategy, in this strategy we use the basic principle of trading: Buy low, sell high. "Buy low, sell high" is a strategy where you buy stocks or securities at a low price and sell them at a higher price. So at the end,this strategy can be difficult as prices reflect emotions and psychology and are difficult to predict, for that reason we create an automatic strategy, so we delete the emotional part to have more chance to get a profit.