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chaudharigauravi/Machine_learning_In_Finance

Built a trading algorithm in Python for the Tesla stocks returning in 39% higher returns than a simple buy and hold strategy, over a period of 2016-2018 . Designed random forest algorithm that combines CAPM, FAMA (French three factor model), Multi-Factor Linear Regression, Principal Component Analysis and Time series analysis to forecast stock prices . Generated trading signals using strategies such as Bollinger bands, Double crossover with evaluating risk and Sharpe ratio

语言:Jupyter Notebook · GitHub 星标:19 · Fork:7

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