[Tutorialsplanet.NET] Udemy - Financial Engineering and Artificial Intelligence in Python

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[Tutorialsplanet.NET] Udemy - Financial Engineering and Artificial Intelligence in Python

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收录时间：2022-03-20
最近下载：2024-11-11

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文件列表

  • 12. Setting Up Your Environment FAQ/1. Anaconda Environment Setup.mp4 189.6 MB
  • 12. Setting Up Your Environment FAQ/2. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.mp4 157.9 MB
  • 3. Time Series Analysis/18. ARIMA in Code (pt 1).mp4 141.8 MB
  • 3. Time Series Analysis/28. ARIMA in Code (pt 3).mp4 117.4 MB
  • 3. Time Series Analysis/27. ARIMA in Code (pt 2).mp4 115.2 MB
  • 14. Effective Learning Strategies for Machine Learning FAQ/4. Machine Learning and AI Prerequisite Roadmap (pt 2).mp4 113.4 MB
  • 14. Effective Learning Strategies for Machine Learning FAQ/2. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.mp4 110.7 MB
  • 6. VIP The Basics of Reinforcement Learning/2. Elements of a Reinforcement Learning Problem.mp4 110.3 MB
  • 7. VIP Reinforcement Learning for Algorithmic Trading/5. Q-Learning for Algorithmic Trading in Code.mp4 108.0 MB
  • 9. VIP Regime Detection and Sequence Modeling with Hidden Markov Models/5. HMM for Modeling Volatility Clustering in Code.mp4 106.9 MB
  • 8. VIP Statistical Factor Models and Unsupervised Machine Learning/4. Statistical Factor Models (Code).mp4 105.9 MB
  • 4. Portfolio Optimization and CAPM/8. Visualizing Random Portfolios and Monte Carlo Simulation (pt 2).mp4 93.0 MB
  • 14. Effective Learning Strategies for Machine Learning FAQ/3. Machine Learning and AI Prerequisite Roadmap (pt 1).mp4 83.5 MB
  • 2. Financial Basics/5. Understanding Financial Data (Code).mp4 79.2 MB
  • 4. Portfolio Optimization and CAPM/7. Visualizing Random Portfolios and Monte Carlo Simulation (pt 1).mp4 77.0 MB
  • 8. VIP Statistical Factor Models and Unsupervised Machine Learning/3. Statistical Factor Models (Advanced).mp4 76.6 MB
  • 13. Extra Help With Python Coding for Beginners FAQ/1. How to Code by Yourself (part 1).mp4 75.3 MB
  • 3. Time Series Analysis/3. Random Walk Hypothesis.mp4 74.9 MB
  • 5. VIP Algorithmic Trading/6. Machine Learning-Based Trading Strategy in Code.mp4 72.9 MB
  • 13. Extra Help With Python Coding for Beginners FAQ/3. Proof that using Jupyter Notebook is the same as not using it.mp4 72.8 MB
  • 5. VIP Algorithmic Trading/4. Trend-Following Strategy in Code (pt 2).mp4 72.4 MB
  • 6. VIP The Basics of Reinforcement Learning/11. Q-Learning.mp4 70.2 MB
  • 9. VIP Regime Detection and Sequence Modeling with Hidden Markov Models/4. HMM Tasks and the Viterbi Algorithm.mp4 68.2 MB
  • 3. Time Series Analysis/20. Stationarity Code.mp4 67.7 MB
  • 5. VIP Algorithmic Trading/3. Trend-Following Strategy in Code (pt 1).mp4 66.9 MB
  • 8. VIP Statistical Factor Models and Unsupervised Machine Learning/1. Statistical Factor Models (Beginner).mp4 66.5 MB
  • 2. Financial Basics/3. Getting Financial Data (Code).mp4 65.6 MB
  • 2. Financial Basics/19. Statistical Testing.mp4 63.7 MB
  • 3. Time Series Analysis/10. Simple Exponential Smoothing for Forecasting (Code).mp4 62.0 MB
  • 6. VIP The Basics of Reinforcement Learning/9. Solving the Bellman Equation with Reinforcement Learning (pt 2).mp4 60.0 MB
  • 5. VIP Algorithmic Trading/2. Trend-Following Strategy.mp4 58.6 MB
  • 7. VIP Reinforcement Learning for Algorithmic Trading/2. Trend-Following Strategy Revisited (Code).mp4 58.5 MB
  • 3. Time Series Analysis/6. Simple Moving Average (Code).mp4 58.5 MB
  • 3. Time Series Analysis/2. Efficient Market Hypothesis.mp4 57.5 MB
  • 3. Time Series Analysis/8. Exponentially-Weighted Moving Average (Code).mp4 57.0 MB
  • 3. Time Series Analysis/15. Autoregressive Models - AR(p).mp4 56.2 MB
  • 4. Portfolio Optimization and CAPM/13. Mean-Variance Optimization And The Efficient Frontier in Code.mp4 55.9 MB
  • 3. Time Series Analysis/14. Holt-Winters (Code).mp4 55.0 MB
  • 4. Portfolio Optimization and CAPM/20. Capital Asset Pricing Model (CAPM).mp4 54.8 MB
  • 2. Financial Basics/15. The t-Distribution (Code).mp4 53.2 MB
  • 6. VIP The Basics of Reinforcement Learning/4. Markov Decision Processes (MDPs).mp4 53.2 MB
  • 7. VIP Reinforcement Learning for Algorithmic Trading/1. Trend-Following Strategy with Reinforcement Learning API.mp4 52.0 MB
  • 3. Time Series Analysis/19. Stationarity.mp4 52.0 MB
  • 9. VIP Regime Detection and Sequence Modeling with Hidden Markov Models/1. Why Sequence Models (pt 1).mp4 51.8 MB
  • 13. Extra Help With Python Coding for Beginners FAQ/2. How to Code by Yourself (part 2).mp4 51.5 MB
  • 3. Time Series Analysis/29. ACF and PACF for Stock Returns.mp4 51.3 MB
  • 3. Time Series Analysis/13. Holt-Winters (Theory).mp4 51.2 MB
  • 4. Portfolio Optimization and CAPM/21. Problems with Markowitz Portfolio Theory and Robust Estimation.mp4 50.4 MB
  • 6. VIP The Basics of Reinforcement Learning/6. Value Functions and the Bellman Equation.mp4 50.2 MB
  • 2. Financial Basics/9. Adjusted Close, Stock Splits, and Dividends.mp4 49.7 MB
  • 3. Time Series Analysis/26. Model Selection, AIC and BIC.mp4 49.6 MB
  • 1. Welcome/1. Introduction and Outline.mp4 49.1 MB
  • 2. Financial Basics/24. Alpha and Beta (Code).mp4 48.0 MB
  • 2. Financial Basics/11. Back to Returns (Code).mp4 47.9 MB
  • 6. VIP The Basics of Reinforcement Learning/3. States, Actions, Rewards, Policies.mp4 46.4 MB
  • 1. Welcome/2. Where to get the code.mp4 46.4 MB
  • 4. Portfolio Optimization and CAPM/17. Maximum Sharpe Ratio in Code.mp4 45.8 MB
  • 6. VIP The Basics of Reinforcement Learning/8. Solving the Bellman Equation with Reinforcement Learning (pt 1).mp4 44.9 MB
  • 3. Time Series Analysis/17. ARIMA.mp4 44.8 MB
  • 3. Time Series Analysis/23. ACF and PACF in Code (pt 1).mp4 44.3 MB
  • 2. Financial Basics/20. Statistical Testing (Code).mp4 43.9 MB
  • 2. Financial Basics/2. Getting Financial Data.mp4 43.9 MB
  • 6. VIP The Basics of Reinforcement Learning/10. Epsilon-Greedy.mp4 43.7 MB
  • 9. VIP Regime Detection and Sequence Modeling with Hidden Markov Models/2. Why Sequence Models (pt 2).mp4 43.2 MB
  • 6. VIP The Basics of Reinforcement Learning/1. Reinforcement Learning Section Introduction.mp4 42.9 MB
  • 3. Time Series Analysis/25. Auto ARIMA and SARIMAX.mp4 42.6 MB
  • 8. VIP Statistical Factor Models and Unsupervised Machine Learning/2. Statistical Factor Models (Intermediate).mp4 42.5 MB
  • 6. VIP The Basics of Reinforcement Learning/12. How to Learn Reinforcement Learning.mp4 42.4 MB
  • 3. Time Series Analysis/30. Forecasting.mp4 41.2 MB
  • 2. Financial Basics/22. Covariance and Correlation (Code).mp4 40.8 MB
  • 2. Financial Basics/17. Confidence Intervals.mp4 40.6 MB
  • 4. Portfolio Optimization and CAPM/18. Portfolio with a Risk-Free Asset and Tangency Portfolio.mp4 39.7 MB
  • 15. Appendix FAQ Finale/2. BONUS Lecture.mp4 39.6 MB
  • 3. Time Series Analysis/7. Exponentially-Weighted Moving Average (Theory).mp4 39.6 MB
  • 2. Financial Basics/7. Dealing with Missing Data (Code).mp4 39.5 MB
  • 4. Portfolio Optimization and CAPM/16. Sharpe Ratio.mp4 39.4 MB
  • 9. VIP Regime Detection and Sequence Modeling with Hidden Markov Models/3. HMM Parameters.mp4 39.2 MB
  • 3. Time Series Analysis/21. ACF (Autocorrelation Function).mp4 39.1 MB
  • 4. Portfolio Optimization and CAPM/5. Describing a Portfolio (pt 1).mp4 38.3 MB
  • 3. Time Series Analysis/9. Simple Exponential Smoothing for Forecasting (Theory).mp4 38.1 MB
  • 3. Time Series Analysis/24. ACF and PACF in Code (pt 2).mp4 37.1 MB
  • 2. Financial Basics/13. QQ-Plots (Code).mp4 37.1 MB
  • 14. Effective Learning Strategies for Machine Learning FAQ/1. How to Succeed in this Course (Long Version).mp4 36.9 MB
  • 2. Financial Basics/16. Skewness and Kurtosis.mp4 36.3 MB
  • 2. Financial Basics/26. Mixture of Gaussians (Code).mp4 35.1 MB
  • 5. VIP Algorithmic Trading/5. Machine Learning-Based Trading Strategy.mp4 34.9 MB
  • 4. Portfolio Optimization and CAPM/4. Why Diversify.mp4 34.9 MB
  • 5. VIP Algorithmic Trading/8. Using a Random Forest Classifier for Machine Learning-Based Trading.mp4 34.6 MB
  • 3. Time Series Analysis/11. Holt's Linear Trend Model (Theory).mp4 34.6 MB
  • 2. Financial Basics/21. Covariance and Correlation.mp4 34.5 MB
  • 4. Portfolio Optimization and CAPM/9. Maximum and Minimum Portfolio Return.mp4 34.2 MB
  • 7. VIP Reinforcement Learning for Algorithmic Trading/4. Representing States.mp4 34.1 MB
  • 10. Course Summary and Common Questions/1. Trading APIs and Deploying Your Strategy in the Real World.mp4 33.4 MB
  • 3. Time Series Analysis/1. Time Series Analysis Section Introduction.mp4 33.4 MB
  • 6. VIP The Basics of Reinforcement Learning/7. What does it mean to “learn”.mp4 33.3 MB
  • 4. Portfolio Optimization and CAPM/11. Mean-Variance Optimization.mp4 33.2 MB
  • 3. Time Series Analysis/4. The Naive Forecast.mp4 32.5 MB
  • 4. Portfolio Optimization and CAPM/12. The Efficient Frontier.mp4 32.2 MB
  • 4. Portfolio Optimization and CAPM/3. What is Risk.mp4 32.0 MB
  • 5. VIP Algorithmic Trading/9. Algorithmic Trading Section Summary.mp4 31.4 MB
  • 7. VIP Reinforcement Learning for Algorithmic Trading/3. Q-Learning in an Algorithmic Trading Context.mp4 31.1 MB
  • 2. Financial Basics/25. Mixture of Gaussians.mp4 30.8 MB
  • 2. Financial Basics/8. Returns.mp4 30.6 MB
  • 2. Financial Basics/1. Financial Basics Section Introduction.mp4 30.4 MB
  • 2. Financial Basics/23. Alpha and Beta.mp4 30.2 MB
  • 2. Financial Basics/4. Understanding Financial Data.mp4 29.9 MB
  • 2. Financial Basics/6. Dealing with Missing Data.mp4 29.6 MB
  • 4. Portfolio Optimization and CAPM/10. Maximum and Minimum Portfolio Return in Code.mp4 29.4 MB
  • 3. Time Series Analysis/22. PACF (Partial Autocorrelation Funtion).mp4 27.5 MB
  • 5. VIP Algorithmic Trading/7. Classification-Based Trading Strategy in Code.mp4 26.3 MB
  • 1. Welcome/4. How to Practice.mp4 25.7 MB
  • 1. Welcome/3. Scope of the course.mp4 25.5 MB
  • 4. Portfolio Optimization and CAPM/1. Portfolio Optimization Section Introduction.mp4 25.5 MB
  • 6. VIP The Basics of Reinforcement Learning/5. The Return.mp4 24.7 MB
  • 1. Welcome/5. Warmup (Optional).mp4 24.3 MB
  • 4. Portfolio Optimization and CAPM/6. Describing a Portfolio (pt 2).mp4 23.9 MB
  • 10. Course Summary and Common Questions/2. High Frequency Trading (HFT).mp4 23.1 MB
  • 2. Financial Basics/10. Adjusted Close (Code).mp4 22.0 MB
  • 2. Financial Basics/12. QQ-Plots.mp4 21.7 MB
  • 3. Time Series Analysis/5. Simple Moving Average (Theory).mp4 20.9 MB
  • 2. Financial Basics/14. The t-Distribution.mp4 20.7 MB
  • 3. Time Series Analysis/12. Holt's Linear Trend Model (Code).mp4 19.6 MB
  • 2. Financial Basics/27. Volatility Clustering.mp4 19.4 MB
  • 3. Time Series Analysis/31. Time Series Analysis Section Conclusion.mp4 19.0 MB
  • 4. Portfolio Optimization and CAPM/22. Portfolio Optimization Section Conclusion.mp4 18.3 MB
  • 15. Appendix FAQ Finale/1. What is the Appendix.mp4 17.2 MB
  • 2. Financial Basics/31. Suggestion Box.mp4 16.9 MB
  • 5. VIP Algorithmic Trading/1. Algorithmic Trading Section Introduction.mp4 14.7 MB
  • 4. Portfolio Optimization and CAPM/15. Global Minimum Variance (GMV) Portfolio in Code.mp4 14.3 MB
  • 4. Portfolio Optimization and CAPM/19. Risk-Free Asset and Tangency Portfolio in Code.mp4 14.2 MB
  • 11. Extras/2. VIP Finance Enthusiasts, Beware of Marketers!.mp4 14.2 MB
  • 2. Financial Basics/18. Confidence Intervals (Code).mp4 12.9 MB
  • 2. Financial Basics/29. Price Simulation (Code).mp4 12.8 MB
  • 2. Financial Basics/28. Price Simulation.mp4 12.6 MB
  • 4. Portfolio Optimization and CAPM/2. The S&P500.mp4 12.3 MB
  • 3. Time Series Analysis/16. Moving Average Models - MA(q).mp4 11.5 MB
  • 2. Financial Basics/30. Financial Basics Section Summary.mp4 10.5 MB
  • 4. Portfolio Optimization and CAPM/14. Global Minimum Variance (GMV) Portfolio.mp4 9.0 MB
  • 14. Effective Learning Strategies for Machine Learning FAQ/2. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.srt 32.7 kB
  • 6. VIP The Basics of Reinforcement Learning/2. Elements of a Reinforcement Learning Problem.srt 26.5 kB
  • 8. VIP Statistical Factor Models and Unsupervised Machine Learning/3. Statistical Factor Models (Advanced).srt 26.0 kB
  • 3. Time Series Analysis/18. ARIMA in Code (pt 1).srt 25.1 kB
  • 9. VIP Regime Detection and Sequence Modeling with Hidden Markov Models/5. HMM for Modeling Volatility Clustering in Code.srt 24.7 kB
  • 14. Effective Learning Strategies for Machine Learning FAQ/4. Machine Learning and AI Prerequisite Roadmap (pt 2).srt 24.1 kB
  • 13. Extra Help With Python Coding for Beginners FAQ/1. How to Code by Yourself (part 1).srt 23.2 kB
  • 8. VIP Statistical Factor Models and Unsupervised Machine Learning/1. Statistical Factor Models (Beginner).srt 21.7 kB
  • 2. Financial Basics/19. Statistical Testing.srt 21.3 kB
  • 12. Setting Up Your Environment FAQ/1. Anaconda Environment Setup.srt 20.2 kB
  • 9. VIP Regime Detection and Sequence Modeling with Hidden Markov Models/4. HMM Tasks and the Viterbi Algorithm.srt 19.7 kB
  • 3. Time Series Analysis/3. Random Walk Hypothesis.srt 19.6 kB
  • 9. VIP Regime Detection and Sequence Modeling with Hidden Markov Models/1. Why Sequence Models (pt 1).srt 19.2 kB
  • 8. VIP Statistical Factor Models and Unsupervised Machine Learning/4. Statistical Factor Models (Code).srt 19.0 kB
  • 7. VIP Reinforcement Learning for Algorithmic Trading/5. Q-Learning for Algorithmic Trading in Code.srt 18.9 kB
  • 4. Portfolio Optimization and CAPM/8. Visualizing Random Portfolios and Monte Carlo Simulation (pt 2).srt 18.8 kB
  • 3. Time Series Analysis/28. ARIMA in Code (pt 3).srt 18.5 kB
  • 6. VIP The Basics of Reinforcement Learning/11. Q-Learning.srt 18.5 kB
  • 5. VIP Algorithmic Trading/2. Trend-Following Strategy.srt 18.4 kB
  • 14. Effective Learning Strategies for Machine Learning FAQ/3. Machine Learning and AI Prerequisite Roadmap (pt 1).srt 17.2 kB
  • 3. Time Series Analysis/15. Autoregressive Models - AR(p).srt 17.1 kB
  • 3. Time Series Analysis/27. ARIMA in Code (pt 2).srt 17.1 kB
  • 3. Time Series Analysis/19. Stationarity.srt 16.7 kB
  • 4. Portfolio Optimization and CAPM/7. Visualizing Random Portfolios and Monte Carlo Simulation (pt 1).srt 16.6 kB
  • 2. Financial Basics/9. Adjusted Close, Stock Splits, and Dividends.srt 16.6 kB
  • 3. Time Series Analysis/2. Efficient Market Hypothesis.srt 16.5 kB
  • 9. VIP Regime Detection and Sequence Modeling with Hidden Markov Models/2. Why Sequence Models (pt 2).srt 16.4 kB
  • 4. Portfolio Optimization and CAPM/20. Capital Asset Pricing Model (CAPM).srt 16.4 kB
  • 7. VIP Reinforcement Learning for Algorithmic Trading/1. Trend-Following Strategy with Reinforcement Learning API.srt 16.1 kB
  • 2. Financial Basics/5. Understanding Financial Data (Code).srt 15.5 kB
  • 3. Time Series Analysis/13. Holt-Winters (Theory).srt 15.4 kB
  • 6. VIP The Basics of Reinforcement Learning/9. Solving the Bellman Equation with Reinforcement Learning (pt 2).srt 15.1 kB
  • 14. Effective Learning Strategies for Machine Learning FAQ/1. How to Succeed in this Course (Long Version).srt 15.1 kB
  • 3. Time Series Analysis/8. Exponentially-Weighted Moving Average (Code).srt 15.0 kB
  • 3. Time Series Analysis/7. Exponentially-Weighted Moving Average (Theory).srt 14.9 kB
  • 12. Setting Up Your Environment FAQ/2. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.srt 14.5 kB
  • 13. Extra Help With Python Coding for Beginners FAQ/3. Proof that using Jupyter Notebook is the same as not using it.srt 14.4 kB
  • 3. Time Series Analysis/9. Simple Exponential Smoothing for Forecasting (Theory).srt 14.2 kB
  • 3. Time Series Analysis/17. ARIMA.srt 14.1 kB
  • 2. Financial Basics/17. Confidence Intervals.srt 14.0 kB
  • 3. Time Series Analysis/26. Model Selection, AIC and BIC.srt 13.8 kB
  • 13. Extra Help With Python Coding for Beginners FAQ/2. How to Code by Yourself (part 2).srt 13.5 kB
  • 8. VIP Statistical Factor Models and Unsupervised Machine Learning/2. Statistical Factor Models (Intermediate).srt 13.4 kB
  • 3. Time Series Analysis/21. ACF (Autocorrelation Function).srt 13.3 kB
  • 6. VIP The Basics of Reinforcement Learning/4. Markov Decision Processes (MDPs).srt 13.0 kB
  • 3. Time Series Analysis/10. Simple Exponential Smoothing for Forecasting (Code).srt 12.9 kB
  • 6. VIP The Basics of Reinforcement Learning/6. Value Functions and the Bellman Equation.srt 12.9 kB
  • 4. Portfolio Optimization and CAPM/9. Maximum and Minimum Portfolio Return.srt 12.8 kB
  • 6. VIP The Basics of Reinforcement Learning/8. Solving the Bellman Equation with Reinforcement Learning (pt 1).srt 12.7 kB
  • 4. Portfolio Optimization and CAPM/18. Portfolio with a Risk-Free Asset and Tangency Portfolio.srt 12.7 kB
  • 1. Welcome/2. Where to get the code.srt 12.7 kB
  • 9. VIP Regime Detection and Sequence Modeling with Hidden Markov Models/3. HMM Parameters.srt 12.6 kB
  • 4. Portfolio Optimization and CAPM/5. Describing a Portfolio (pt 1).srt 12.6 kB
  • 3. Time Series Analysis/25. Auto ARIMA and SARIMAX.srt 12.6 kB
  • 4. Portfolio Optimization and CAPM/21. Problems with Markowitz Portfolio Theory and Robust Estimation.srt 12.5 kB
  • 3. Time Series Analysis/30. Forecasting.srt 12.4 kB
  • 5. VIP Algorithmic Trading/4. Trend-Following Strategy in Code (pt 2).srt 12.3 kB
  • 2. Financial Basics/8. Returns.srt 12.0 kB
  • 6. VIP The Basics of Reinforcement Learning/3. States, Actions, Rewards, Policies.srt 11.9 kB
  • 4. Portfolio Optimization and CAPM/13. Mean-Variance Optimization And The Efficient Frontier in Code.srt 11.5 kB
  • 2. Financial Basics/21. Covariance and Correlation.srt 11.1 kB
  • 3. Time Series Analysis/20. Stationarity Code.srt 11.0 kB
  • 7. VIP Reinforcement Learning for Algorithmic Trading/2. Trend-Following Strategy Revisited (Code).srt 10.8 kB
  • 4. Portfolio Optimization and CAPM/4. Why Diversify.srt 10.8 kB
  • 2. Financial Basics/15. The t-Distribution (Code).srt 10.7 kB
  • 2. Financial Basics/24. Alpha and Beta (Code).srt 10.6 kB
  • 5. VIP Algorithmic Trading/6. Machine Learning-Based Trading Strategy in Code.srt 10.6 kB
  • 2. Financial Basics/16. Skewness and Kurtosis.srt 10.6 kB
  • 5. VIP Algorithmic Trading/5. Machine Learning-Based Trading Strategy.srt 10.5 kB
  • 3. Time Series Analysis/11. Holt's Linear Trend Model (Theory).srt 10.3 kB
  • 4. Portfolio Optimization and CAPM/11. Mean-Variance Optimization.srt 10.3 kB
  • 4. Portfolio Optimization and CAPM/16. Sharpe Ratio.srt 10.2 kB
  • 2. Financial Basics/2. Getting Financial Data.srt 10.2 kB
  • 2. Financial Basics/13. QQ-Plots (Code).srt 10.2 kB
  • 3. Time Series Analysis/14. Holt-Winters (Code).srt 10.1 kB
  • 1. Welcome/1. Introduction and Outline.srt 9.8 kB
  • 7. VIP Reinforcement Learning for Algorithmic Trading/4. Representing States.srt 9.8 kB
  • 4. Portfolio Optimization and CAPM/12. The Efficient Frontier.srt 9.8 kB
  • 2. Financial Basics/3. Getting Financial Data (Code).srt 9.7 kB
  • 3. Time Series Analysis/6. Simple Moving Average (Code).srt 9.7 kB
  • 5. VIP Algorithmic Trading/3. Trend-Following Strategy in Code (pt 1).srt 9.6 kB
  • 4. Portfolio Optimization and CAPM/3. What is Risk.srt 9.6 kB
  • 3. Time Series Analysis/23. ACF and PACF in Code (pt 1).srt 9.6 kB
  • 3. Time Series Analysis/1. Time Series Analysis Section Introduction.srt 9.6 kB
  • 7. VIP Reinforcement Learning for Algorithmic Trading/3. Q-Learning in an Algorithmic Trading Context.srt 9.5 kB
  • 2. Financial Basics/23. Alpha and Beta.srt 9.5 kB
  • 3. Time Series Analysis/4. The Naive Forecast.srt 9.4 kB
  • 2. Financial Basics/25. Mixture of Gaussians.srt 9.4 kB
  • 2. Financial Basics/11. Back to Returns (Code).srt 9.3 kB
  • 2. Financial Basics/20. Statistical Testing (Code).srt 9.3 kB
  • 2. Financial Basics/7. Dealing with Missing Data (Code).srt 9.2 kB
  • 6. VIP The Basics of Reinforcement Learning/7. What does it mean to “learn”.srt 9.1 kB
  • 6. VIP The Basics of Reinforcement Learning/1. Reinforcement Learning Section Introduction.srt 8.9 kB
  • 3. Time Series Analysis/29. ACF and PACF for Stock Returns.srt 8.7 kB
  • 4. Portfolio Optimization and CAPM/17. Maximum Sharpe Ratio in Code.srt 8.5 kB
  • 2. Financial Basics/26. Mixture of Gaussians (Code).srt 8.4 kB
  • 3. Time Series Analysis/24. ACF and PACF in Code (pt 2).srt 8.2 kB
  • 3. Time Series Analysis/22. PACF (Partial Autocorrelation Funtion).srt 8.2 kB
  • 4. Portfolio Optimization and CAPM/6. Describing a Portfolio (pt 2).srt 8.1 kB
  • 15. Appendix FAQ Finale/2. BONUS Lecture.srt 8.0 kB
  • 2. Financial Basics/6. Dealing with Missing Data.srt 8.0 kB
  • 10. Course Summary and Common Questions/1. Trading APIs and Deploying Your Strategy in the Real World.srt 7.8 kB
  • 6. VIP The Basics of Reinforcement Learning/12. How to Learn Reinforcement Learning.srt 7.7 kB
  • 5. VIP Algorithmic Trading/9. Algorithmic Trading Section Summary.srt 7.7 kB
  • 6. VIP The Basics of Reinforcement Learning/10. Epsilon-Greedy.srt 7.6 kB
  • 2. Financial Basics/1. Financial Basics Section Introduction.srt 7.6 kB
  • 2. Financial Basics/12. QQ-Plots.srt 7.4 kB
  • 2. Financial Basics/22. Covariance and Correlation (Code).srt 7.3 kB
  • 2. Financial Basics/4. Understanding Financial Data.srt 6.8 kB
  • 6. VIP The Basics of Reinforcement Learning/5. The Return.srt 6.5 kB
  • 1. Welcome/5. Warmup (Optional).srt 6.2 kB
  • 4. Portfolio Optimization and CAPM/10. Maximum and Minimum Portfolio Return in Code.srt 5.9 kB
  • 3. Time Series Analysis/5. Simple Moving Average (Theory).srt 5.9 kB
  • 5. VIP Algorithmic Trading/8. Using a Random Forest Classifier for Machine Learning-Based Trading.srt 5.7 kB
  • 3. Time Series Analysis/31. Time Series Analysis Section Conclusion.srt 5.4 kB
  • 10. Course Summary and Common Questions/2. High Frequency Trading (HFT).srt 5.4 kB
  • 1. Welcome/4. How to Practice.srt 5.3 kB
  • 1. Welcome/3. Scope of the course.srt 5.3 kB
  • 2. Financial Basics/14. The t-Distribution.srt 5.2 kB
  • 4. Portfolio Optimization and CAPM/1. Portfolio Optimization Section Introduction.srt 4.9 kB
  • 2. Financial Basics/31. Suggestion Box.srt 4.8 kB
  • 2. Financial Basics/10. Adjusted Close (Code).srt 4.7 kB
  • 5. VIP Algorithmic Trading/7. Classification-Based Trading Strategy in Code.srt 4.3 kB
  • 3. Time Series Analysis/16. Moving Average Models - MA(q).srt 4.3 kB
  • 2. Financial Basics/28. Price Simulation.srt 4.1 kB
  • 2. Financial Basics/27. Volatility Clustering.srt 4.0 kB
  • 15. Appendix FAQ Finale/1. What is the Appendix.srt 3.9 kB
  • 5. VIP Algorithmic Trading/1. Algorithmic Trading Section Introduction.srt 3.7 kB
  • 3. Time Series Analysis/12. Holt's Linear Trend Model (Code).srt 3.5 kB
  • 4. Portfolio Optimization and CAPM/2. The S&P500.srt 3.4 kB
  • 2. Financial Basics/29. Price Simulation (Code).srt 3.2 kB
  • 2. Financial Basics/30. Financial Basics Section Summary.srt 3.1 kB
  • 4. Portfolio Optimization and CAPM/22. Portfolio Optimization Section Conclusion.srt 3.0 kB
  • 2. Financial Basics/18. Confidence Intervals (Code).srt 2.9 kB
  • 11. Extras/2. VIP Finance Enthusiasts, Beware of Marketers!.srt 2.9 kB
  • 4. Portfolio Optimization and CAPM/19. Risk-Free Asset and Tangency Portfolio in Code.srt 2.6 kB
  • 4. Portfolio Optimization and CAPM/15. Global Minimum Variance (GMV) Portfolio in Code.srt 2.5 kB
  • 4. Portfolio Optimization and CAPM/14. Global Minimum Variance (GMV) Portfolio.srt 2.4 kB
  • 11. Extras/1. Colab Notebooks.html 256 Bytes
  • 1. Welcome/[Tutorialsplanet.NET].url 128 Bytes
  • 11. Extras/[Tutorialsplanet.NET].url 128 Bytes
  • [Tutorialsplanet.NET].url 128 Bytes
  • 1. Welcome/2.1 Github Link.html 116 Bytes

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