[] Udemy - Financial Engineering and Artificial Intelligence in Python
- 收录时间:2021-12-24 19:23:12
- 文件大小:6GB
- 下载次数:1
- 最近下载:2021-12-24 19:23:12
- 磁力链接:
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文件列表
- 12. Setting Up Your Environment FAQ/1. Anaconda Environment Setup.mp4 181MB
- 12. Setting Up Your Environment FAQ/2. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.mp4 151MB
- 3. Time Series Analysis/18. ARIMA in Code (pt 1).mp4 135MB
- 3. Time Series Analysis/28. ARIMA in Code (pt 3).mp4 112MB
- 3. Time Series Analysis/27. ARIMA in Code (pt 2).mp4 110MB
- 14. Effective Learning Strategies for Machine Learning FAQ/4. Machine Learning and AI Prerequisite Roadmap (pt 2).mp4 108MB
- 14. Effective Learning Strategies for Machine Learning FAQ/2. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.mp4 106MB
- 6. VIP The Basics of Reinforcement Learning/2. Elements of a Reinforcement Learning Problem.mp4 105MB
- 7. VIP Reinforcement Learning for Algorithmic Trading/5. Q-Learning for Algorithmic Trading in Code.mp4 103MB
- 9. VIP Regime Detection and Sequence Modeling with Hidden Markov Models/5. HMM for Modeling Volatility Clustering in Code.mp4 102MB
- 8. VIP Statistical Factor Models and Unsupervised Machine Learning/4. Statistical Factor Models (Code).mp4 101MB
- 4. Portfolio Optimization and CAPM/8. Visualizing Random Portfolios and Monte Carlo Simulation (pt 2).mp4 89MB
- 14. Effective Learning Strategies for Machine Learning FAQ/3. Machine Learning and AI Prerequisite Roadmap (pt 1).mp4 80MB
- 2. Financial Basics/5. Understanding Financial Data (Code).mp4 76MB
- 4. Portfolio Optimization and CAPM/7. Visualizing Random Portfolios and Monte Carlo Simulation (pt 1).mp4 73MB
- 8. VIP Statistical Factor Models and Unsupervised Machine Learning/3. Statistical Factor Models (Advanced).mp4 73MB
- 13. Extra Help With Python Coding for Beginners FAQ/1. How to Code by Yourself (part 1).mp4 72MB
- 3. Time Series Analysis/3. Random Walk Hypothesis.mp4 71MB
- 5. VIP Algorithmic Trading/6. Machine Learning-Based Trading Strategy in Code.mp4 70MB
- 13. Extra Help With Python Coding for Beginners FAQ/3. Proof that using Jupyter Notebook is the same as not using it.mp4 69MB
- 5. VIP Algorithmic Trading/4. Trend-Following Strategy in Code (pt 2).mp4 69MB
- 6. VIP The Basics of Reinforcement Learning/11. Q-Learning.mp4 67MB
- 9. VIP Regime Detection and Sequence Modeling with Hidden Markov Models/4. HMM Tasks and the Viterbi Algorithm.mp4 65MB
- 3. Time Series Analysis/20. Stationarity Code.mp4 65MB
- 5. VIP Algorithmic Trading/3. Trend-Following Strategy in Code (pt 1).mp4 64MB
- 8. VIP Statistical Factor Models and Unsupervised Machine Learning/1. Statistical Factor Models (Beginner).mp4 63MB
- 2. Financial Basics/3. Getting Financial Data (Code).mp4 63MB
- 2. Financial Basics/19. Statistical Testing.mp4 61MB
- 3. Time Series Analysis/10. Simple Exponential Smoothing for Forecasting (Code).mp4 59MB
- 6. VIP The Basics of Reinforcement Learning/9. Solving the Bellman Equation with Reinforcement Learning (pt 2).mp4 57MB
- 5. VIP Algorithmic Trading/2. Trend-Following Strategy.mp4 56MB
- 7. VIP Reinforcement Learning for Algorithmic Trading/2. Trend-Following Strategy Revisited (Code).mp4 56MB
- 3. Time Series Analysis/6. Simple Moving Average (Code).mp4 56MB
- 3. Time Series Analysis/2. Efficient Market Hypothesis.mp4 55MB
- 3. Time Series Analysis/8. Exponentially-Weighted Moving Average (Code).mp4 54MB
- 3. Time Series Analysis/15. Autoregressive Models - AR(p).mp4 54MB
- 4. Portfolio Optimization and CAPM/13. Mean-Variance Optimization And The Efficient Frontier in Code.mp4 53MB
- 3. Time Series Analysis/14. Holt-Winters (Code).mp4 52MB
- 4. Portfolio Optimization and CAPM/20. Capital Asset Pricing Model (CAPM).mp4 52MB
- 2. Financial Basics/15. The t-Distribution (Code).mp4 51MB
- 6. VIP The Basics of Reinforcement Learning/4. Markov Decision Processes (MDPs).mp4 51MB
- 7. VIP Reinforcement Learning for Algorithmic Trading/1. Trend-Following Strategy with Reinforcement Learning API.mp4 50MB
- 3. Time Series Analysis/19. Stationarity.mp4 50MB
- 9. VIP Regime Detection and Sequence Modeling with Hidden Markov Models/1. Why Sequence Models (pt 1).mp4 49MB
- 13. Extra Help With Python Coding for Beginners FAQ/2. How to Code by Yourself (part 2).mp4 49MB
- 3. Time Series Analysis/29. ACF and PACF for Stock Returns.mp4 49MB
- 3. Time Series Analysis/13. Holt-Winters (Theory).mp4 49MB
- 4. Portfolio Optimization and CAPM/21. Problems with Markowitz Portfolio Theory and Robust Estimation.mp4 48MB
- 6. VIP The Basics of Reinforcement Learning/6. Value Functions and the Bellman Equation.mp4 48MB
- 2. Financial Basics/9. Adjusted Close, Stock Splits, and Dividends.mp4 47MB
- 3. Time Series Analysis/26. Model Selection, AIC and BIC.mp4 47MB
- 1. Welcome/1. Introduction and Outline.mp4 47MB
- 2. Financial Basics/24. Alpha and Beta (Code).mp4 46MB
- 2. Financial Basics/11. Back to Returns (Code).mp4 46MB
- 6. VIP The Basics of Reinforcement Learning/3. States, Actions, Rewards, Policies.mp4 44MB
- 1. Welcome/2. Where to get the code.mp4 44MB
- 4. Portfolio Optimization and CAPM/17. Maximum Sharpe Ratio in Code.mp4 44MB
- 6. VIP The Basics of Reinforcement Learning/8. Solving the Bellman Equation with Reinforcement Learning (pt 1).mp4 43MB
- 3. Time Series Analysis/17. ARIMA.mp4 43MB
- 3. Time Series Analysis/23. ACF and PACF in Code (pt 1).mp4 42MB
- 2. Financial Basics/20. Statistical Testing (Code).mp4 42MB
- 2. Financial Basics/2. Getting Financial Data.mp4 42MB
- 6. VIP The Basics of Reinforcement Learning/10. Epsilon-Greedy.mp4 42MB
- 9. VIP Regime Detection and Sequence Modeling with Hidden Markov Models/2. Why Sequence Models (pt 2).mp4 41MB
- 6. VIP The Basics of Reinforcement Learning/1. Reinforcement Learning Section Introduction.mp4 41MB
- 3. Time Series Analysis/25. Auto ARIMA and SARIMAX.mp4 41MB
- 8. VIP Statistical Factor Models and Unsupervised Machine Learning/2. Statistical Factor Models (Intermediate).mp4 40MB
- 6. VIP The Basics of Reinforcement Learning/12. How to Learn Reinforcement Learning.mp4 40MB
- 3. Time Series Analysis/30. Forecasting.mp4 39MB
- 2. Financial Basics/22. Covariance and Correlation (Code).mp4 39MB
- 2. Financial Basics/17. Confidence Intervals.mp4 39MB
- 4. Portfolio Optimization and CAPM/18. Portfolio with a Risk-Free Asset and Tangency Portfolio.mp4 38MB
- 15. Appendix FAQ Finale/2. BONUS Lecture.mp4 38MB
- 3. Time Series Analysis/7. Exponentially-Weighted Moving Average (Theory).mp4 38MB
- 2. Financial Basics/7. Dealing with Missing Data (Code).mp4 38MB
- 4. Portfolio Optimization and CAPM/16. Sharpe Ratio.mp4 38MB
- 9. VIP Regime Detection and Sequence Modeling with Hidden Markov Models/3. HMM Parameters.mp4 37MB
- 3. Time Series Analysis/21. ACF (Autocorrelation Function).mp4 37MB
- 4. Portfolio Optimization and CAPM/5. Describing a Portfolio (pt 1).mp4 37MB
- 3. Time Series Analysis/9. Simple Exponential Smoothing for Forecasting (Theory).mp4 36MB
- 3. Time Series Analysis/24. ACF and PACF in Code (pt 2).mp4 35MB
- 2. Financial Basics/13. QQ-Plots (Code).mp4 35MB
- 14. Effective Learning Strategies for Machine Learning FAQ/1. How to Succeed in this Course (Long Version).mp4 35MB
- 2. Financial Basics/16. Skewness and Kurtosis.mp4 35MB
- 2. Financial Basics/26. Mixture of Gaussians (Code).mp4 34MB
- 5. VIP Algorithmic Trading/5. Machine Learning-Based Trading Strategy.mp4 33MB
- 4. Portfolio Optimization and CAPM/4. Why Diversify.mp4 33MB
- 5. VIP Algorithmic Trading/8. Using a Random Forest Classifier for Machine Learning-Based Trading.mp4 33MB
- 3. Time Series Analysis/11. Holt's Linear Trend Model (Theory).mp4 33MB
- 2. Financial Basics/21. Covariance and Correlation.mp4 33MB
- 4. Portfolio Optimization and CAPM/9. Maximum and Minimum Portfolio Return.mp4 33MB
- 7. VIP Reinforcement Learning for Algorithmic Trading/4. Representing States.mp4 33MB
- 10. Course Summary and Common Questions/1. Trading APIs and Deploying Your Strategy in the Real World.mp4 32MB
- 3. Time Series Analysis/1. Time Series Analysis Section Introduction.mp4 32MB
- 6. VIP The Basics of Reinforcement Learning/7. What does it mean to “learn”.mp4 32MB
- 4. Portfolio Optimization and CAPM/11. Mean-Variance Optimization.mp4 32MB
- 3. Time Series Analysis/4. The Naive Forecast.mp4 31MB
- 4. Portfolio Optimization and CAPM/12. The Efficient Frontier.mp4 31MB
- 4. Portfolio Optimization and CAPM/3. What is Risk.mp4 31MB
- 5. VIP Algorithmic Trading/9. Algorithmic Trading Section Summary.mp4 30MB
- 7. VIP Reinforcement Learning for Algorithmic Trading/3. Q-Learning in an Algorithmic Trading Context.mp4 30MB
- 2. Financial Basics/25. Mixture of Gaussians.mp4 29MB
- 2. Financial Basics/8. Returns.mp4 29MB
- 2. Financial Basics/1. Financial Basics Section Introduction.mp4 29MB
- 2. Financial Basics/23. Alpha and Beta.mp4 29MB
- 2. Financial Basics/4. Understanding Financial Data.mp4 29MB
- 2. Financial Basics/6. Dealing with Missing Data.mp4 28MB
- 4. Portfolio Optimization and CAPM/10. Maximum and Minimum Portfolio Return in Code.mp4 28MB
- 3. Time Series Analysis/22. PACF (Partial Autocorrelation Funtion).mp4 26MB
- 5. VIP Algorithmic Trading/7. Classification-Based Trading Strategy in Code.mp4 25MB
- 1. Welcome/4. How to Practice.mp4 25MB
- 1. Welcome/3. Scope of the course.mp4 24MB
- 4. Portfolio Optimization and CAPM/1. Portfolio Optimization Section Introduction.mp4 24MB
- 6. VIP The Basics of Reinforcement Learning/5. The Return.mp4 24MB
- 1. Welcome/5. Warmup (Optional).mp4 23MB
- 4. Portfolio Optimization and CAPM/6. Describing a Portfolio (pt 2).mp4 23MB
- 10. Course Summary and Common Questions/2. High Frequency Trading (HFT).mp4 22MB
- 2. Financial Basics/10. Adjusted Close (Code).mp4 21MB
- 2. Financial Basics/12. QQ-Plots.mp4 21MB
- 3. Time Series Analysis/5. Simple Moving Average (Theory).mp4 20MB
- 2. Financial Basics/14. The t-Distribution.mp4 20MB
- 3. Time Series Analysis/12. Holt's Linear Trend Model (Code).mp4 19MB
- 2. Financial Basics/27. Volatility Clustering.mp4 19MB
- 3. Time Series Analysis/31. Time Series Analysis Section Conclusion.mp4 18MB
- 4. Portfolio Optimization and CAPM/22. Portfolio Optimization Section Conclusion.mp4 17MB
- 15. Appendix FAQ Finale/1. What is the Appendix.mp4 16MB
- 2. Financial Basics/31. Suggestion Box.mp4 16MB
- 5. VIP Algorithmic Trading/1. Algorithmic Trading Section Introduction.mp4 14MB
- 4. Portfolio Optimization and CAPM/15. Global Minimum Variance (GMV) Portfolio in Code.mp4 14MB
- 4. Portfolio Optimization and CAPM/19. Risk-Free Asset and Tangency Portfolio in Code.mp4 14MB
- 11. Extras/2. VIP Finance Enthusiasts, Beware of Marketers!.mp4 14MB
- 2. Financial Basics/18. Confidence Intervals (Code).mp4 12MB
- 2. Financial Basics/29. Price Simulation (Code).mp4 12MB
- 2. Financial Basics/28. Price Simulation.mp4 12MB
- 4. Portfolio Optimization and CAPM/2. The S&P500.mp4 12MB
- 3. Time Series Analysis/16. Moving Average Models - MA(q).mp4 11MB
- 2. Financial Basics/30. Financial Basics Section Summary.mp4 10MB
- 4. Portfolio Optimization and CAPM/14. Global Minimum Variance (GMV) Portfolio.mp4 9MB
- 14. Effective Learning Strategies for Machine Learning FAQ/2. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.srt 32KB
- 6. VIP The Basics of Reinforcement Learning/2. Elements of a Reinforcement Learning Problem.srt 26KB
- 8. VIP Statistical Factor Models and Unsupervised Machine Learning/3. Statistical Factor Models (Advanced).srt 25KB
- 3. Time Series Analysis/18. ARIMA in Code (pt 1).srt 24KB
- 9. VIP Regime Detection and Sequence Modeling with Hidden Markov Models/5. HMM for Modeling Volatility Clustering in Code.srt 24KB
- 14. Effective Learning Strategies for Machine Learning FAQ/4. Machine Learning and AI Prerequisite Roadmap (pt 2).srt 24KB
- 13. Extra Help With Python Coding for Beginners FAQ/1. How to Code by Yourself (part 1).srt 23KB
- 8. VIP Statistical Factor Models and Unsupervised Machine Learning/1. Statistical Factor Models (Beginner).srt 21KB
- 2. Financial Basics/19. Statistical Testing.srt 21KB
- 12. Setting Up Your Environment FAQ/1. Anaconda Environment Setup.srt 20KB
- 9. VIP Regime Detection and Sequence Modeling with Hidden Markov Models/4. HMM Tasks and the Viterbi Algorithm.srt 19KB
- 3. Time Series Analysis/3. Random Walk Hypothesis.srt 19KB
- 9. VIP Regime Detection and Sequence Modeling with Hidden Markov Models/1. Why Sequence Models (pt 1).srt 19KB
- 8. VIP Statistical Factor Models and Unsupervised Machine Learning/4. Statistical Factor Models (Code).srt 19KB
- 7. VIP Reinforcement Learning for Algorithmic Trading/5. Q-Learning for Algorithmic Trading in Code.srt 18KB
- 4. Portfolio Optimization and CAPM/8. Visualizing Random Portfolios and Monte Carlo Simulation (pt 2).srt 18KB
- 3. Time Series Analysis/28. ARIMA in Code (pt 3).srt 18KB
- 6. VIP The Basics of Reinforcement Learning/11. Q-Learning.srt 18KB
- 5. VIP Algorithmic Trading/2. Trend-Following Strategy.srt 18KB
- 14. Effective Learning Strategies for Machine Learning FAQ/3. Machine Learning and AI Prerequisite Roadmap (pt 1).srt 17KB
- 3. Time Series Analysis/15. Autoregressive Models - AR(p).srt 17KB
- 3. Time Series Analysis/27. ARIMA in Code (pt 2).srt 17KB
- 3. Time Series Analysis/19. Stationarity.srt 16KB
- 4. Portfolio Optimization and CAPM/7. Visualizing Random Portfolios and Monte Carlo Simulation (pt 1).srt 16KB
- 2. Financial Basics/9. Adjusted Close, Stock Splits, and Dividends.srt 16KB
- 3. Time Series Analysis/2. Efficient Market Hypothesis.srt 16KB
- 9. VIP Regime Detection and Sequence Modeling with Hidden Markov Models/2. Why Sequence Models (pt 2).srt 16KB
- 4. Portfolio Optimization and CAPM/20. Capital Asset Pricing Model (CAPM).srt 16KB
- 7. VIP Reinforcement Learning for Algorithmic Trading/1. Trend-Following Strategy with Reinforcement Learning API.srt 16KB
- 2. Financial Basics/5. Understanding Financial Data (Code).srt 15KB
- 3. Time Series Analysis/13. Holt-Winters (Theory).srt 15KB
- 6. VIP The Basics of Reinforcement Learning/9. Solving the Bellman Equation with Reinforcement Learning (pt 2).srt 15KB
- 14. Effective Learning Strategies for Machine Learning FAQ/1. How to Succeed in this Course (Long Version).srt 15KB
- 3. Time Series Analysis/8. Exponentially-Weighted Moving Average (Code).srt 15KB
- 3. Time Series Analysis/7. Exponentially-Weighted Moving Average (Theory).srt 15KB
- 12. Setting Up Your Environment FAQ/2. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.srt 14KB
- 13. Extra Help With Python Coding for Beginners FAQ/3. Proof that using Jupyter Notebook is the same as not using it.srt 14KB
- 3. Time Series Analysis/9. Simple Exponential Smoothing for Forecasting (Theory).srt 14KB
- 3. Time Series Analysis/17. ARIMA.srt 14KB
- 2. Financial Basics/17. Confidence Intervals.srt 14KB
- 3. Time Series Analysis/26. Model Selection, AIC and BIC.srt 13KB
- 13. Extra Help With Python Coding for Beginners FAQ/2. How to Code by Yourself (part 2).srt 13KB
- 8. VIP Statistical Factor Models and Unsupervised Machine Learning/2. Statistical Factor Models (Intermediate).srt 13KB
- 3. Time Series Analysis/21. ACF (Autocorrelation Function).srt 13KB
- 6. VIP The Basics of Reinforcement Learning/4. Markov Decision Processes (MDPs).srt 13KB
- 3. Time Series Analysis/10. Simple Exponential Smoothing for Forecasting (Code).srt 13KB
- 6. VIP The Basics of Reinforcement Learning/6. Value Functions and the Bellman Equation.srt 13KB
- 4. Portfolio Optimization and CAPM/9. Maximum and Minimum Portfolio Return.srt 12KB
- 6. VIP The Basics of Reinforcement Learning/8. Solving the Bellman Equation with Reinforcement Learning (pt 1).srt 12KB
- 4. Portfolio Optimization and CAPM/18. Portfolio with a Risk-Free Asset and Tangency Portfolio.srt 12KB
- 1. Welcome/2. Where to get the code.srt 12KB
- 9. VIP Regime Detection and Sequence Modeling with Hidden Markov Models/3. HMM Parameters.srt 12KB
- 4. Portfolio Optimization and CAPM/5. Describing a Portfolio (pt 1).srt 12KB
- 3. Time Series Analysis/25. Auto ARIMA and SARIMAX.srt 12KB
- 4. Portfolio Optimization and CAPM/21. Problems with Markowitz Portfolio Theory and Robust Estimation.srt 12KB
- 3. Time Series Analysis/30. Forecasting.srt 12KB
- 5. VIP Algorithmic Trading/4. Trend-Following Strategy in Code (pt 2).srt 12KB
- 2. Financial Basics/8. Returns.srt 12KB
- 6. VIP The Basics of Reinforcement Learning/3. States, Actions, Rewards, Policies.srt 12KB
- 4. Portfolio Optimization and CAPM/13. Mean-Variance Optimization And The Efficient Frontier in Code.srt 11KB
- 2. Financial Basics/21. Covariance and Correlation.srt 11KB
- 3. Time Series Analysis/20. Stationarity Code.srt 11KB
- 7. VIP Reinforcement Learning for Algorithmic Trading/2. Trend-Following Strategy Revisited (Code).srt 11KB
- 4. Portfolio Optimization and CAPM/4. Why Diversify.srt 11KB
- 2. Financial Basics/15. The t-Distribution (Code).srt 10KB
- 2. Financial Basics/24. Alpha and Beta (Code).srt 10KB
- 5. VIP Algorithmic Trading/6. Machine Learning-Based Trading Strategy in Code.srt 10KB
- 2. Financial Basics/16. Skewness and Kurtosis.srt 10KB
- 5. VIP Algorithmic Trading/5. Machine Learning-Based Trading Strategy.srt 10KB
- 3. Time Series Analysis/11. Holt's Linear Trend Model (Theory).srt 10KB
- 4. Portfolio Optimization and CAPM/11. Mean-Variance Optimization.srt 10KB
- 4. Portfolio Optimization and CAPM/16. Sharpe Ratio.srt 10KB
- 2. Financial Basics/2. Getting Financial Data.srt 10KB
- 2. Financial Basics/13. QQ-Plots (Code).srt 10KB
- 3. Time Series Analysis/14. Holt-Winters (Code).srt 10KB
- 1. Welcome/1. Introduction and Outline.srt 10KB
- 7. VIP Reinforcement Learning for Algorithmic Trading/4. Representing States.srt 10KB
- 4. Portfolio Optimization and CAPM/12. The Efficient Frontier.srt 10KB
- 2. Financial Basics/3. Getting Financial Data (Code).srt 9KB
- 3. Time Series Analysis/6. Simple Moving Average (Code).srt 9KB
- 5. VIP Algorithmic Trading/3. Trend-Following Strategy in Code (pt 1).srt 9KB
- 4. Portfolio Optimization and CAPM/3. What is Risk.srt 9KB
- 3. Time Series Analysis/23. ACF and PACF in Code (pt 1).srt 9KB
- 3. Time Series Analysis/1. Time Series Analysis Section Introduction.srt 9KB
- 7. VIP Reinforcement Learning for Algorithmic Trading/3. Q-Learning in an Algorithmic Trading Context.srt 9KB
- 2. Financial Basics/23. Alpha and Beta.srt 9KB
- 3. Time Series Analysis/4. The Naive Forecast.srt 9KB
- 2. Financial Basics/25. Mixture of Gaussians.srt 9KB
- 2. Financial Basics/11. Back to Returns (Code).srt 9KB
- 2. Financial Basics/20. Statistical Testing (Code).srt 9KB
- 2. Financial Basics/7. Dealing with Missing Data (Code).srt 9KB
- 6. VIP The Basics of Reinforcement Learning/7. What does it mean to “learn”.srt 9KB
- 6. VIP The Basics of Reinforcement Learning/1. Reinforcement Learning Section Introduction.srt 9KB
- 3. Time Series Analysis/29. ACF and PACF for Stock Returns.srt 8KB
- 4. Portfolio Optimization and CAPM/17. Maximum Sharpe Ratio in Code.srt 8KB
- 2. Financial Basics/26. Mixture of Gaussians (Code).srt 8KB
- 3. Time Series Analysis/24. ACF and PACF in Code (pt 2).srt 8KB
- 3. Time Series Analysis/22. PACF (Partial Autocorrelation Funtion).srt 8KB
- 4. Portfolio Optimization and CAPM/6. Describing a Portfolio (pt 2).srt 8KB
- 15. Appendix FAQ Finale/2. BONUS Lecture.srt 8KB
- 2. Financial Basics/6. Dealing with Missing Data.srt 8KB
- 10. Course Summary and Common Questions/1. Trading APIs and Deploying Your Strategy in the Real World.srt 8KB
- 6. VIP The Basics of Reinforcement Learning/12. How to Learn Reinforcement Learning.srt 8KB
- 5. VIP Algorithmic Trading/9. Algorithmic Trading Section Summary.srt 8KB
- 6. VIP The Basics of Reinforcement Learning/10. Epsilon-Greedy.srt 7KB
- 2. Financial Basics/1. Financial Basics Section Introduction.srt 7KB
- 2. Financial Basics/12. QQ-Plots.srt 7KB
- 2. Financial Basics/22. Covariance and Correlation (Code).srt 7KB
- 2. Financial Basics/4. Understanding Financial Data.srt 7KB
- 6. VIP The Basics of Reinforcement Learning/5. The Return.srt 6KB
- 1. Welcome/5. Warmup (Optional).srt 6KB
- 4. Portfolio Optimization and CAPM/10. Maximum and Minimum Portfolio Return in Code.srt 6KB
- 3. Time Series Analysis/5. Simple Moving Average (Theory).srt 6KB
- 5. VIP Algorithmic Trading/8. Using a Random Forest Classifier for Machine Learning-Based Trading.srt 6KB
- 3. Time Series Analysis/31. Time Series Analysis Section Conclusion.srt 5KB
- 10. Course Summary and Common Questions/2. High Frequency Trading (HFT).srt 5KB
- 1. Welcome/4. How to Practice.srt 5KB
- 1. Welcome/3. Scope of the course.srt 5KB
- 2. Financial Basics/14. The t-Distribution.srt 5KB
- 4. Portfolio Optimization and CAPM/1. Portfolio Optimization Section Introduction.srt 5KB
- 2. Financial Basics/31. Suggestion Box.srt 5KB
- 2. Financial Basics/10. Adjusted Close (Code).srt 5KB
- 5. VIP Algorithmic Trading/7. Classification-Based Trading Strategy in Code.srt 4KB
- 3. Time Series Analysis/16. Moving Average Models - MA(q).srt 4KB
- 2. Financial Basics/28. Price Simulation.srt 4KB
- 2. Financial Basics/27. Volatility Clustering.srt 4KB
- 15. Appendix FAQ Finale/1. What is the Appendix.srt 4KB
- 5. VIP Algorithmic Trading/1. Algorithmic Trading Section Introduction.srt 4KB
- 3. Time Series Analysis/12. Holt's Linear Trend Model (Code).srt 3KB
- 4. Portfolio Optimization and CAPM/2. The S&P500.srt 3KB
- 2. Financial Basics/29. Price Simulation (Code).srt 3KB
- 2. Financial Basics/30. Financial Basics Section Summary.srt 3KB
- 4. Portfolio Optimization and CAPM/22. Portfolio Optimization Section Conclusion.srt 3KB
- 2. Financial Basics/18. Confidence Intervals (Code).srt 3KB
- 11. Extras/2. VIP Finance Enthusiasts, Beware of Marketers!.srt 3KB
- 4. Portfolio Optimization and CAPM/19. Risk-Free Asset and Tangency Portfolio in Code.srt 3KB
- 4. Portfolio Optimization and CAPM/15. Global Minimum Variance (GMV) Portfolio in Code.srt 2KB
- 4. Portfolio Optimization and CAPM/14. Global Minimum Variance (GMV) Portfolio.srt 2KB
- 11. Extras/1. Colab Notebooks.html 256B
- 1. Welcome/[Tutorialsplanet.NET].url 128B
- 11. Extras/[Tutorialsplanet.NET].url 128B
- [Tutorialsplanet.NET].url 128B
- 1. Welcome/2.1 Github Link.html 116B