Build a Momentum-Based Algorithmic Trading Program

Data Handling

Criteria	Meet Specification
The student will be able to load data to an SQLite database from a CSV file	The tables prices and positions are created in the database The prices table is correctly populated by the data from the SP500.csv

The GBM Model

Criteria	Meet Specification
The student will be able to calibrate a GBM model to a price series	Correct log-transform of the historical prices Correct estimation of the 1st and the 2nd moments of the price series using bootstrap Correct calculation of the mu and the sigma parameters from the first two moments of the bootstrap sample.
The student will be able to forecast the price at a future time.	Correct calculation of the predicted price and its confidence interval.

Computation of the Expected Shortfall

Criteria	Meet Specification
The student will be able to calculate the expected shortfall.	The formula of the expected shortfall is coded correctly in the GBM.expected_shortfall function.

Tips to make your project standout:

Consider using the Student’s t test to check the significance of an observed momentum. At what level of significance will you act on it?
Find out the days on which your strategy performs the best and the worst, respectively. What happened on these days?
Calculate the mean and the standard deviation of your daily returns. Then calculate the Sharpe ratio of your strategy in the test period. How does it compare to the return of a savings account?