STOCK-RETURN-PREDICTION-USING-KNN-SVM-GUASSIAN-PROCESS-ADABO
Unverified Grid strategy on Indices by kennedyCzar. BotFinder score 18 out of 100.
Forecast stock prices using machine learning approach. A time series analysis. Employ the Use of Predictive Modeling in Machine Learning to Forecast Stock Return. Approach Used by
Source: github
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STOCK-RETURN-PREDICTION-USING-KNN-SVM-GUASSIAN-PROCESS-ADABO
STOCK-RETURN-PREDICTION-USING-KNN-SVM-GUASSIAN-PROCESS-ADABOOST-TREE-REGRESSION-AND-QDA Forecasts stock prices using classical machine learning techniques- A time series analysis & modeling. Employ the Use of Predictive Modeling in Machine Learning to Forecast Stock Return. Approach Used by Hedge Funds to Select Tradeable Stocks Objective: Predict stock stock price using Technical Indicators as predictors (features). Use Supervised Machine Learning Approach to predict stock prices. Employ the use of pipeline and GridSearch to select the best model Use Final Model to Predict Stock Returns. Show plots of stock Return Write Deployable script. Note: That Every stock has different behaviour and so at every point we may have different best performing algorithm. For instance, after much testing Ranform Forest Algorithm perform better for predicting Apple Stocks than any other algo. Guassian process classifier performed better than every other algo at predicting IBM stocks etc. Indicators/Predictors Used: Moving Averages(Also called Rolling mean) Commodity Channel Index Momentum Stochastic O
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