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[Tutorialsplanet.NET].url |
128B |
[Tutorialsplanet.NET].url |
128B |
[Tutorialsplanet.NET].url |
128B |
1. Algorithmic Trading Section Introduction.mp4 |
14.03MB |
1. Algorithmic Trading Section Introduction.srt |
3.60KB |
1. Anaconda Environment Setup.mp4 |
180.77MB |
1. Anaconda Environment Setup.srt |
19.70KB |
1. Colab Notebooks.html |
256B |
1. Financial Basics Section Introduction.mp4 |
28.96MB |
1. Financial Basics Section Introduction.srt |
7.41KB |
1. How to Code by Yourself (part 1).mp4 |
71.84MB |
1. How to Code by Yourself (part 1).srt |
22.65KB |
1. How to Succeed in this Course (Long Version).mp4 |
35.21MB |
1. How to Succeed in this Course (Long Version).srt |
14.71KB |
1. Introduction and Outline.mp4 |
46.84MB |
1. Introduction and Outline.srt |
9.58KB |
1. Portfolio Optimization Section Introduction.mp4 |
24.36MB |
1. Portfolio Optimization Section Introduction.srt |
4.83KB |
1. Reinforcement Learning Section Introduction.mp4 |
40.88MB |
1. Reinforcement Learning Section Introduction.srt |
8.67KB |
1. Statistical Factor Models (Beginner).mp4 |
63.37MB |
1. Statistical Factor Models (Beginner).srt |
21.18KB |
1. Time Series Analysis Section Introduction.mp4 |
31.84MB |
1. Time Series Analysis Section Introduction.srt |
9.33KB |
1. Trading APIs and Deploying Your Strategy in the Real World.mp4 |
31.89MB |
1. Trading APIs and Deploying Your Strategy in the Real World.srt |
7.62KB |
1. Trend-Following Strategy with Reinforcement Learning API.mp4 |
49.61MB |
1. Trend-Following Strategy with Reinforcement Learning API.srt |
15.72KB |
1. What is the Appendix.mp4 |
16.38MB |
1. What is the Appendix.srt |
3.77KB |
1. Why Sequence Models (pt 1).mp4 |
49.40MB |
1. Why Sequence Models (pt 1).srt |
18.72KB |
10. Adjusted Close (Code).mp4 |
20.95MB |
10. Adjusted Close (Code).srt |
4.59KB |
10. Epsilon-Greedy.mp4 |
41.63MB |
10. Epsilon-Greedy.srt |
7.44KB |
10. Maximum and Minimum Portfolio Return in Code.mp4 |
28.00MB |
10. Maximum and Minimum Portfolio Return in Code.srt |
5.80KB |
10. Simple Exponential Smoothing for Forecasting (Code).mp4 |
59.17MB |
10. Simple Exponential Smoothing for Forecasting (Code).srt |
12.63KB |
11. Back to Returns (Code).mp4 |
45.65MB |
11. Back to Returns (Code).srt |
9.07KB |
11. Holt's Linear Trend Model (Theory).mp4 |
32.96MB |
11. Holt's Linear Trend Model (Theory).srt |
10.08KB |
11. Mean-Variance Optimization.mp4 |
31.62MB |
11. Mean-Variance Optimization.srt |
10.01KB |
11. Q-Learning.mp4 |
66.91MB |
11. Q-Learning.srt |
18.04KB |
12. Holt's Linear Trend Model (Code).mp4 |
18.66MB |
12. Holt's Linear Trend Model (Code).srt |
3.45KB |
12. How to Learn Reinforcement Learning.mp4 |
40.39MB |
12. How to Learn Reinforcement Learning.srt |
7.56KB |
12. QQ-Plots.mp4 |
20.70MB |
12. QQ-Plots.srt |
7.19KB |
12. The Efficient Frontier.mp4 |
30.70MB |
12. The Efficient Frontier.srt |
9.54KB |
13. Holt-Winters (Theory).mp4 |
48.84MB |
13. Holt-Winters (Theory).srt |
15.00KB |
13. Mean-Variance Optimization And The Efficient Frontier in Code.mp4 |
53.29MB |
13. Mean-Variance Optimization And The Efficient Frontier in Code.srt |
11.23KB |
13. QQ-Plots (Code).mp4 |
35.34MB |
13. QQ-Plots (Code).srt |
9.94KB |
14. Global Minimum Variance (GMV) Portfolio.mp4 |
8.58MB |
14. Global Minimum Variance (GMV) Portfolio.srt |
2.35KB |
14. Holt-Winters (Code).mp4 |
52.48MB |
14. Holt-Winters (Code).srt |
9.82KB |
14. The t-Distribution.mp4 |
19.71MB |
14. The t-Distribution.srt |
5.07KB |
15. Autoregressive Models - AR(p).mp4 |
53.63MB |
15. Autoregressive Models - AR(p).srt |
16.67KB |
15. Global Minimum Variance (GMV) Portfolio in Code.mp4 |
13.64MB |
15. Global Minimum Variance (GMV) Portfolio in Code.srt |
2.47KB |
15. The t-Distribution (Code).mp4 |
50.74MB |
15. The t-Distribution (Code).srt |
10.46KB |
16. Moving Average Models - MA(q).mp4 |
10.93MB |
16. Moving Average Models - MA(q).srt |
4.16KB |
16. Sharpe Ratio.mp4 |
37.59MB |
16. Sharpe Ratio.srt |
9.97KB |
16. Skewness and Kurtosis.mp4 |
34.64MB |
16. Skewness and Kurtosis.srt |
10.36KB |
17. ARIMA.mp4 |
42.69MB |
17. ARIMA.srt |
13.80KB |
17. Confidence Intervals.mp4 |
38.76MB |
17. Confidence Intervals.srt |
13.70KB |
17. Maximum Sharpe Ratio in Code.mp4 |
43.71MB |
17. Maximum Sharpe Ratio in Code.srt |
8.26KB |
18. ARIMA in Code (pt 1).mp4 |
135.23MB |
18. ARIMA in Code (pt 1).srt |
24.49KB |
18. Confidence Intervals (Code).mp4 |
12.32MB |
18. Confidence Intervals (Code).srt |
2.82KB |
18. Portfolio with a Risk-Free Asset and Tangency Portfolio.mp4 |
37.84MB |
18. Portfolio with a Risk-Free Asset and Tangency Portfolio.srt |
12.40KB |
19. Risk-Free Asset and Tangency Portfolio in Code.mp4 |
13.58MB |
19. Risk-Free Asset and Tangency Portfolio in Code.srt |
2.57KB |
19. Stationarity.mp4 |
49.59MB |
19. Stationarity.srt |
16.29KB |
19. Statistical Testing.mp4 |
60.71MB |
19. Statistical Testing.srt |
20.82KB |
2.1 Github Link.html |
116B |
2. BONUS Lecture.mp4 |
37.79MB |
2. BONUS Lecture.srt |
7.83KB |
2. Efficient Market Hypothesis.mp4 |
54.80MB |
2. Efficient Market Hypothesis.srt |
16.08KB |
2. Elements of a Reinforcement Learning Problem.mp4 |
105.15MB |
2. Elements of a Reinforcement Learning Problem.srt |
25.92KB |
2. Getting Financial Data.mp4 |
41.85MB |
2. Getting Financial Data.srt |
9.95KB |
2. High Frequency Trading (HFT).mp4 |
22.04MB |
2. High Frequency Trading (HFT).srt |
5.27KB |
2. How to Code by Yourself (part 2).mp4 |
49.16MB |
2. How to Code by Yourself (part 2).srt |
13.18KB |
2. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.mp4 |
150.56MB |
2. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.srt |
14.15KB |
2. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.mp4 |
105.57MB |
2. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.srt |
31.94KB |
2. Statistical Factor Models (Intermediate).mp4 |
40.50MB |
2. Statistical Factor Models (Intermediate).srt |
13.09KB |
2. The S&P500.mp4 |
11.70MB |
2. The S&P500.srt |
3.34KB |
2. Trend-Following Strategy.mp4 |
55.86MB |
2. Trend-Following Strategy.srt |
17.95KB |
2. Trend-Following Strategy Revisited (Code).mp4 |
55.76MB |
2. Trend-Following Strategy Revisited (Code).srt |
10.53KB |
2. VIP Finance Enthusiasts, Beware of Marketers!.mp4 |
13.51MB |
2. VIP Finance Enthusiasts, Beware of Marketers!.srt |
2.81KB |
2. Where to get the code.mp4 |
44.23MB |
2. Where to get the code.srt |
12.37KB |
2. Why Sequence Models (pt 2).mp4 |
41.20MB |
2. Why Sequence Models (pt 2).srt |
16.04KB |
20. Capital Asset Pricing Model (CAPM).mp4 |
52.23MB |
20. Capital Asset Pricing Model (CAPM).srt |
16.02KB |
20. Stationarity Code.mp4 |
64.55MB |
20. Stationarity Code.srt |
10.76KB |
20. Statistical Testing (Code).mp4 |
41.89MB |
20. Statistical Testing (Code).srt |
9.06KB |
21. ACF (Autocorrelation Function).mp4 |
37.28MB |
21. ACF (Autocorrelation Function).srt |
12.98KB |
21. Covariance and Correlation.mp4 |
32.87MB |
21. Covariance and Correlation.srt |
10.81KB |
21. Problems with Markowitz Portfolio Theory and Robust Estimation.mp4 |
48.06MB |
21. Problems with Markowitz Portfolio Theory and Robust Estimation.srt |
12.18KB |
22. Covariance and Correlation (Code).mp4 |
38.93MB |
22. Covariance and Correlation (Code).srt |
7.14KB |
22. PACF (Partial Autocorrelation Funtion).mp4 |
26.18MB |
22. PACF (Partial Autocorrelation Funtion).srt |
7.97KB |
22. Portfolio Optimization Section Conclusion.mp4 |
17.49MB |
22. Portfolio Optimization Section Conclusion.srt |
2.89KB |
23. ACF and PACF in Code (pt 1).mp4 |
42.27MB |
23. ACF and PACF in Code (pt 1).srt |
9.34KB |
23. Alpha and Beta.mp4 |
28.75MB |
23. Alpha and Beta.srt |
9.26KB |
24. ACF and PACF in Code (pt 2).mp4 |
35.39MB |
24. ACF and PACF in Code (pt 2).srt |
8.02KB |
24. Alpha and Beta (Code).mp4 |
45.80MB |
24. Alpha and Beta (Code).srt |
10.39KB |
25. Auto ARIMA and SARIMAX.mp4 |
40.64MB |
25. Auto ARIMA and SARIMAX.srt |
12.28KB |
25. Mixture of Gaussians.mp4 |
29.33MB |
25. Mixture of Gaussians.srt |
9.17KB |
26. Mixture of Gaussians (Code).mp4 |
33.51MB |
26. Mixture of Gaussians (Code).srt |
8.22KB |
26. Model Selection, AIC and BIC.mp4 |
47.28MB |
26. Model Selection, AIC and BIC.srt |
13.46KB |
27. ARIMA in Code (pt 2).mp4 |
109.85MB |
27. ARIMA in Code (pt 2).srt |
16.66KB |
27. Volatility Clustering.mp4 |
18.52MB |
27. Volatility Clustering.srt |
3.88KB |
28. ARIMA in Code (pt 3).mp4 |
111.97MB |
28. ARIMA in Code (pt 3).srt |
18.05KB |
28. Price Simulation.mp4 |
11.99MB |
28. Price Simulation.srt |
4.02KB |
29. ACF and PACF for Stock Returns.mp4 |
48.93MB |
29. ACF and PACF for Stock Returns.srt |
8.45KB |
29. Price Simulation (Code).mp4 |
12.24MB |
29. Price Simulation (Code).srt |
3.10KB |
3. Getting Financial Data (Code).mp4 |
62.59MB |
3. Getting Financial Data (Code).srt |
9.46KB |
3. HMM Parameters.mp4 |
37.43MB |
3. HMM Parameters.srt |
12.35KB |
3. Machine Learning and AI Prerequisite Roadmap (pt 1).mp4 |
79.64MB |
3. Machine Learning and AI Prerequisite Roadmap (pt 1).srt |
16.77KB |
3. Proof that using Jupyter Notebook is the same as not using it.mp4 |
69.45MB |
3. Proof that using Jupyter Notebook is the same as not using it.srt |
14.05KB |
3. Q-Learning in an Algorithmic Trading Context.mp4 |
29.67MB |
3. Q-Learning in an Algorithmic Trading Context.srt |
9.29KB |
3. Random Walk Hypothesis.mp4 |
71.46MB |
3. Random Walk Hypothesis.srt |
19.10KB |
3. Scope of the course.mp4 |
24.37MB |
3. Scope of the course.srt |
5.16KB |
3. States, Actions, Rewards, Policies.mp4 |
44.24MB |
3. States, Actions, Rewards, Policies.srt |
11.67KB |
3. Statistical Factor Models (Advanced).mp4 |
73.07MB |
3. Statistical Factor Models (Advanced).srt |
25.40KB |
3. Trend-Following Strategy in Code (pt 1).mp4 |
63.78MB |
3. Trend-Following Strategy in Code (pt 1).srt |
9.38KB |
3. What is Risk.mp4 |
30.51MB |
3. What is Risk.srt |
9.35KB |
30. Financial Basics Section Summary.mp4 |
9.98MB |
30. Financial Basics Section Summary.srt |
3.07KB |
30. Forecasting.mp4 |
39.29MB |
30. Forecasting.srt |
12.14KB |
31. Suggestion Box.mp4 |
16.10MB |
31. Suggestion Box.srt |
4.66KB |
31. Time Series Analysis Section Conclusion.mp4 |
18.14MB |
31. Time Series Analysis Section Conclusion.srt |
5.29KB |
4. HMM Tasks and the Viterbi Algorithm.mp4 |
65.01MB |
4. HMM Tasks and the Viterbi Algorithm.srt |
19.23KB |
4. How to Practice.mp4 |
24.52MB |
4. How to Practice.srt |
5.20KB |
4. Machine Learning and AI Prerequisite Roadmap (pt 2).mp4 |
108.17MB |
4. Machine Learning and AI Prerequisite Roadmap (pt 2).srt |
23.55KB |
4. Markov Decision Processes (MDPs).mp4 |
50.71MB |
4. Markov Decision Processes (MDPs).srt |
12.70KB |
4. Representing States.mp4 |
32.55MB |
4. Representing States.srt |
9.56KB |
4. Statistical Factor Models (Code).mp4 |
101.03MB |
4. Statistical Factor Models (Code).srt |
18.59KB |
4. The Naive Forecast.mp4 |
30.95MB |
4. The Naive Forecast.srt |
9.23KB |
4. Trend-Following Strategy in Code (pt 2).mp4 |
69.09MB |
4. Trend-Following Strategy in Code (pt 2).srt |
12.00KB |
4. Understanding Financial Data.mp4 |
28.53MB |
4. Understanding Financial Data.srt |
6.61KB |
4. Why Diversify.mp4 |
33.24MB |
4. Why Diversify.srt |
10.50KB |
5. Describing a Portfolio (pt 1).mp4 |
36.52MB |
5. Describing a Portfolio (pt 1).srt |
12.35KB |
5. HMM for Modeling Volatility Clustering in Code.mp4 |
101.96MB |
5. HMM for Modeling Volatility Clustering in Code.srt |
24.11KB |
5. Machine Learning-Based Trading Strategy.mp4 |
33.32MB |
5. Machine Learning-Based Trading Strategy.srt |
10.30KB |
5. Q-Learning for Algorithmic Trading in Code.mp4 |
103.04MB |
5. Q-Learning for Algorithmic Trading in Code.srt |
18.50KB |
5. Simple Moving Average (Theory).mp4 |
19.90MB |
5. Simple Moving Average (Theory).srt |
5.73KB |
5. The Return.mp4 |
23.55MB |
5. The Return.srt |
6.32KB |
5. Understanding Financial Data (Code).mp4 |
75.54MB |
5. Understanding Financial Data (Code).srt |
15.10KB |
5. Warmup (Optional).mp4 |
23.17MB |
5. Warmup (Optional).srt |
6.05KB |
6. Dealing with Missing Data.mp4 |
28.20MB |
6. Dealing with Missing Data.srt |
7.76KB |
6. Describing a Portfolio (pt 2).mp4 |
22.75MB |
6. Describing a Portfolio (pt 2).srt |
7.88KB |
6. Machine Learning-Based Trading Strategy in Code.mp4 |
69.54MB |
6. Machine Learning-Based Trading Strategy in Code.srt |
10.38KB |
6. Simple Moving Average (Code).mp4 |
55.75MB |
6. Simple Moving Average (Code).srt |
9.45KB |
6. Value Functions and the Bellman Equation.mp4 |
47.86MB |
6. Value Functions and the Bellman Equation.srt |
12.63KB |
7. Classification-Based Trading Strategy in Code.mp4 |
25.11MB |
7. Classification-Based Trading Strategy in Code.srt |
4.25KB |
7. Dealing with Missing Data (Code).mp4 |
37.68MB |
7. Dealing with Missing Data (Code).srt |
8.95KB |
7. Exponentially-Weighted Moving Average (Theory).mp4 |
37.76MB |
7. Exponentially-Weighted Moving Average (Theory).srt |
14.60KB |
7. Visualizing Random Portfolios and Monte Carlo Simulation (pt 1).mp4 |
73.44MB |
7. Visualizing Random Portfolios and Monte Carlo Simulation (pt 1).srt |
16.22KB |
7. What does it mean to “learn”.mp4 |
31.77MB |
7. What does it mean to “learn”.srt |
8.91KB |
8. Exponentially-Weighted Moving Average (Code).mp4 |
54.34MB |
8. Exponentially-Weighted Moving Average (Code).srt |
14.66KB |
8. Returns.mp4 |
29.22MB |
8. Returns.srt |
11.72KB |
8. Solving the Bellman Equation with Reinforcement Learning (pt 1).mp4 |
42.79MB |
8. Solving the Bellman Equation with Reinforcement Learning (pt 1).srt |
12.41KB |
8. Using a Random Forest Classifier for Machine Learning-Based Trading.mp4 |
33.02MB |
8. Using a Random Forest Classifier for Machine Learning-Based Trading.srt |
5.54KB |
8. Visualizing Random Portfolios and Monte Carlo Simulation (pt 2).mp4 |
88.72MB |
8. Visualizing Random Portfolios and Monte Carlo Simulation (pt 2).srt |
18.36KB |
9. Adjusted Close, Stock Splits, and Dividends.mp4 |
47.36MB |
9. Adjusted Close, Stock Splits, and Dividends.srt |
16.21KB |
9. Algorithmic Trading Section Summary.mp4 |
29.94MB |
9. Algorithmic Trading Section Summary.srt |
7.56KB |
9. Maximum and Minimum Portfolio Return.mp4 |
32.65MB |
9. Maximum and Minimum Portfolio Return.srt |
12.46KB |
9. Simple Exponential Smoothing for Forecasting (Theory).mp4 |
36.31MB |
9. Simple Exponential Smoothing for Forecasting (Theory).srt |
13.89KB |
9. Solving the Bellman Equation with Reinforcement Learning (pt 2).mp4 |
57.19MB |
9. Solving the Bellman Equation with Reinforcement Learning (pt 2).srt |
14.78KB |