Data Analytics for Finance Using Python

Data Analytics for Finance Using Python

Untwal, Nitin Jaglal; Kose, Utku

Taylor & Francis Ltd

12/2024

121

Mole

9781032618234

Pré-lançamento - envio 15 a 20 dias após a sua edição

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1. Stock Investments Portfolio Management by Applying K-Means Clustering. 2. Predicting Stock Price Using the ARIMA Model. 3. Stock Investment Strategy Using a Logistic Regression Model. 4. Predicting Stock Buying and Selling Decisions by Applying the Gaussian Naive Bayes Model Using Python Programming. 5. The Random Forest Technique Is a Tool for Stock Trading Decisions. 6. Applying Decision Tree Classifier for Buying and Selling Strategy with Special Reference to MRF Stock. 7. Descriptive Statistics for Stock Risk Assessment. 8. Stock Investment Strategy Using a Regression Model. 9. Comparing Stock Risk Using F-Test. 10. Stock Risk Analysis Using t-Test. 11. Stock Investment Strategy Using a Z-Score. 12. Applying a Support Vector Machine Model Using Python Programming. 13. Data Visualization for Stock Risk Comparison and Analysis. 14. Applying Natural Language Processing for Stock Investors Sentiment Analysis. 15. Stock Prediction Applying LSTM.
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