STAT 198 Quantitative Finance
Fall 2020
We implement a trading strategy for an index (NASDAQ) based on moving averages of changes in Google Trend data for certain selected keywords.
The notebook can be found in Presentation Notebook.ipynb
We will use Google Trends search volume data to make predictions about the movements of an index.
Data is downloaded through the Pytrends module using the Google Trends API.
Financial data is from yfinance
Backtesting is done using the Backtesting.py package
Paper to implement: https://www.researchgate.net/publication/326503702_Algorithmic_Trading_Systems_Based_on_Google_Trends
https://jackdry.com/predicting-realized-volatility-using-google-trends