renatovotto/Nostradamus
Backtesting an algorithmic trading strategy using Machine Learning and Sentiment Analysis.
This program helps quantitative traders and financial analysts evaluate potential algorithmic trading strategies. It takes historical stock price data and Twitter sentiment scores, then simulates a trading strategy based on these inputs. The output provides detailed performance metrics like returns, Sharpe ratio, and drawdown, allowing you to assess how a strategy would have performed.
No commits in the last 6 months.
Use this if you want to backtest an algorithmic trading strategy for a specific stock, incorporating both technical indicators and social media sentiment.
Not ideal if you need to backtest strategies across a broad portfolio of assets or require real-time trading integration.
Stars
45
Forks
29
Language
Jupyter Notebook
License
—
Category
Last pushed
Oct 23, 2022
Commits (30d)
0
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