Backtesting with ML-based investment strategies

If you create a Machine Learning model to predict the price of a stock:

How can you evaluate its performance if you apply it to your investment strategy?

Data

We start with the stock data of NVIDIA with its ticker NVDA.

Check out this tutorial to learn how to preprocess the daily return of a stock.

import pandas as pd

df = pd.read_csv('data.csv', index_col='Date', parse_dates=True)

Questions

1. How is a Machine Learning model implemented to predict the change in closing price?
2. What is the role of the min_samples_leaf parameter in the DecisionTreeRegressor algorithm?
3. How do we measure the model’s error and what does it tell us about its performance?
4. How do we introduce a Machine Learning model into an investment strategy?
5. How do we evaluate the performance of the Machine Learning investment strategy?