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[] Udemy - Financial Engineering and Artificial Intelligence in Python

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  • 文件大小:6GB
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文件列表

  1. 12. Setting Up Your Environment FAQ/1. Anaconda Environment Setup.mp4 181MB
  2. 12. Setting Up Your Environment FAQ/2. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.mp4 151MB
  3. 3. Time Series Analysis/18. ARIMA in Code (pt 1).mp4 135MB
  4. 3. Time Series Analysis/28. ARIMA in Code (pt 3).mp4 112MB
  5. 3. Time Series Analysis/27. ARIMA in Code (pt 2).mp4 110MB
  6. 14. Effective Learning Strategies for Machine Learning FAQ/4. Machine Learning and AI Prerequisite Roadmap (pt 2).mp4 108MB
  7. 14. Effective Learning Strategies for Machine Learning FAQ/2. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.mp4 106MB
  8. 6. VIP The Basics of Reinforcement Learning/2. Elements of a Reinforcement Learning Problem.mp4 105MB
  9. 7. VIP Reinforcement Learning for Algorithmic Trading/5. Q-Learning for Algorithmic Trading in Code.mp4 103MB
  10. 9. VIP Regime Detection and Sequence Modeling with Hidden Markov Models/5. HMM for Modeling Volatility Clustering in Code.mp4 102MB
  11. 8. VIP Statistical Factor Models and Unsupervised Machine Learning/4. Statistical Factor Models (Code).mp4 101MB
  12. 4. Portfolio Optimization and CAPM/8. Visualizing Random Portfolios and Monte Carlo Simulation (pt 2).mp4 89MB
  13. 14. Effective Learning Strategies for Machine Learning FAQ/3. Machine Learning and AI Prerequisite Roadmap (pt 1).mp4 80MB
  14. 2. Financial Basics/5. Understanding Financial Data (Code).mp4 76MB
  15. 4. Portfolio Optimization and CAPM/7. Visualizing Random Portfolios and Monte Carlo Simulation (pt 1).mp4 73MB
  16. 8. VIP Statistical Factor Models and Unsupervised Machine Learning/3. Statistical Factor Models (Advanced).mp4 73MB
  17. 13. Extra Help With Python Coding for Beginners FAQ/1. How to Code by Yourself (part 1).mp4 72MB
  18. 3. Time Series Analysis/3. Random Walk Hypothesis.mp4 71MB
  19. 5. VIP Algorithmic Trading/6. Machine Learning-Based Trading Strategy in Code.mp4 70MB
  20. 13. Extra Help With Python Coding for Beginners FAQ/3. Proof that using Jupyter Notebook is the same as not using it.mp4 69MB
  21. 5. VIP Algorithmic Trading/4. Trend-Following Strategy in Code (pt 2).mp4 69MB
  22. 6. VIP The Basics of Reinforcement Learning/11. Q-Learning.mp4 67MB
  23. 9. VIP Regime Detection and Sequence Modeling with Hidden Markov Models/4. HMM Tasks and the Viterbi Algorithm.mp4 65MB
  24. 3. Time Series Analysis/20. Stationarity Code.mp4 65MB
  25. 5. VIP Algorithmic Trading/3. Trend-Following Strategy in Code (pt 1).mp4 64MB
  26. 8. VIP Statistical Factor Models and Unsupervised Machine Learning/1. Statistical Factor Models (Beginner).mp4 63MB
  27. 2. Financial Basics/3. Getting Financial Data (Code).mp4 63MB
  28. 2. Financial Basics/19. Statistical Testing.mp4 61MB
  29. 3. Time Series Analysis/10. Simple Exponential Smoothing for Forecasting (Code).mp4 59MB
  30. 6. VIP The Basics of Reinforcement Learning/9. Solving the Bellman Equation with Reinforcement Learning (pt 2).mp4 57MB
  31. 5. VIP Algorithmic Trading/2. Trend-Following Strategy.mp4 56MB
  32. 7. VIP Reinforcement Learning for Algorithmic Trading/2. Trend-Following Strategy Revisited (Code).mp4 56MB
  33. 3. Time Series Analysis/6. Simple Moving Average (Code).mp4 56MB
  34. 3. Time Series Analysis/2. Efficient Market Hypothesis.mp4 55MB
  35. 3. Time Series Analysis/8. Exponentially-Weighted Moving Average (Code).mp4 54MB
  36. 3. Time Series Analysis/15. Autoregressive Models - AR(p).mp4 54MB
  37. 4. Portfolio Optimization and CAPM/13. Mean-Variance Optimization And The Efficient Frontier in Code.mp4 53MB
  38. 3. Time Series Analysis/14. Holt-Winters (Code).mp4 52MB
  39. 4. Portfolio Optimization and CAPM/20. Capital Asset Pricing Model (CAPM).mp4 52MB
  40. 2. Financial Basics/15. The t-Distribution (Code).mp4 51MB
  41. 6. VIP The Basics of Reinforcement Learning/4. Markov Decision Processes (MDPs).mp4 51MB
  42. 7. VIP Reinforcement Learning for Algorithmic Trading/1. Trend-Following Strategy with Reinforcement Learning API.mp4 50MB
  43. 3. Time Series Analysis/19. Stationarity.mp4 50MB
  44. 9. VIP Regime Detection and Sequence Modeling with Hidden Markov Models/1. Why Sequence Models (pt 1).mp4 49MB
  45. 13. Extra Help With Python Coding for Beginners FAQ/2. How to Code by Yourself (part 2).mp4 49MB
  46. 3. Time Series Analysis/29. ACF and PACF for Stock Returns.mp4 49MB
  47. 3. Time Series Analysis/13. Holt-Winters (Theory).mp4 49MB
  48. 4. Portfolio Optimization and CAPM/21. Problems with Markowitz Portfolio Theory and Robust Estimation.mp4 48MB
  49. 6. VIP The Basics of Reinforcement Learning/6. Value Functions and the Bellman Equation.mp4 48MB
  50. 2. Financial Basics/9. Adjusted Close, Stock Splits, and Dividends.mp4 47MB
  51. 3. Time Series Analysis/26. Model Selection, AIC and BIC.mp4 47MB
  52. 1. Welcome/1. Introduction and Outline.mp4 47MB
  53. 2. Financial Basics/24. Alpha and Beta (Code).mp4 46MB
  54. 2. Financial Basics/11. Back to Returns (Code).mp4 46MB
  55. 6. VIP The Basics of Reinforcement Learning/3. States, Actions, Rewards, Policies.mp4 44MB
  56. 1. Welcome/2. Where to get the code.mp4 44MB
  57. 4. Portfolio Optimization and CAPM/17. Maximum Sharpe Ratio in Code.mp4 44MB
  58. 6. VIP The Basics of Reinforcement Learning/8. Solving the Bellman Equation with Reinforcement Learning (pt 1).mp4 43MB
  59. 3. Time Series Analysis/17. ARIMA.mp4 43MB
  60. 3. Time Series Analysis/23. ACF and PACF in Code (pt 1).mp4 42MB
  61. 2. Financial Basics/20. Statistical Testing (Code).mp4 42MB
  62. 2. Financial Basics/2. Getting Financial Data.mp4 42MB
  63. 6. VIP The Basics of Reinforcement Learning/10. Epsilon-Greedy.mp4 42MB
  64. 9. VIP Regime Detection and Sequence Modeling with Hidden Markov Models/2. Why Sequence Models (pt 2).mp4 41MB
  65. 6. VIP The Basics of Reinforcement Learning/1. Reinforcement Learning Section Introduction.mp4 41MB
  66. 3. Time Series Analysis/25. Auto ARIMA and SARIMAX.mp4 41MB
  67. 8. VIP Statistical Factor Models and Unsupervised Machine Learning/2. Statistical Factor Models (Intermediate).mp4 40MB
  68. 6. VIP The Basics of Reinforcement Learning/12. How to Learn Reinforcement Learning.mp4 40MB
  69. 3. Time Series Analysis/30. Forecasting.mp4 39MB
  70. 2. Financial Basics/22. Covariance and Correlation (Code).mp4 39MB
  71. 2. Financial Basics/17. Confidence Intervals.mp4 39MB
  72. 4. Portfolio Optimization and CAPM/18. Portfolio with a Risk-Free Asset and Tangency Portfolio.mp4 38MB
  73. 15. Appendix FAQ Finale/2. BONUS Lecture.mp4 38MB
  74. 3. Time Series Analysis/7. Exponentially-Weighted Moving Average (Theory).mp4 38MB
  75. 2. Financial Basics/7. Dealing with Missing Data (Code).mp4 38MB
  76. 4. Portfolio Optimization and CAPM/16. Sharpe Ratio.mp4 38MB
  77. 9. VIP Regime Detection and Sequence Modeling with Hidden Markov Models/3. HMM Parameters.mp4 37MB
  78. 3. Time Series Analysis/21. ACF (Autocorrelation Function).mp4 37MB
  79. 4. Portfolio Optimization and CAPM/5. Describing a Portfolio (pt 1).mp4 37MB
  80. 3. Time Series Analysis/9. Simple Exponential Smoothing for Forecasting (Theory).mp4 36MB
  81. 3. Time Series Analysis/24. ACF and PACF in Code (pt 2).mp4 35MB
  82. 2. Financial Basics/13. QQ-Plots (Code).mp4 35MB
  83. 14. Effective Learning Strategies for Machine Learning FAQ/1. How to Succeed in this Course (Long Version).mp4 35MB
  84. 2. Financial Basics/16. Skewness and Kurtosis.mp4 35MB
  85. 2. Financial Basics/26. Mixture of Gaussians (Code).mp4 34MB
  86. 5. VIP Algorithmic Trading/5. Machine Learning-Based Trading Strategy.mp4 33MB
  87. 4. Portfolio Optimization and CAPM/4. Why Diversify.mp4 33MB
  88. 5. VIP Algorithmic Trading/8. Using a Random Forest Classifier for Machine Learning-Based Trading.mp4 33MB
  89. 3. Time Series Analysis/11. Holt's Linear Trend Model (Theory).mp4 33MB
  90. 2. Financial Basics/21. Covariance and Correlation.mp4 33MB
  91. 4. Portfolio Optimization and CAPM/9. Maximum and Minimum Portfolio Return.mp4 33MB
  92. 7. VIP Reinforcement Learning for Algorithmic Trading/4. Representing States.mp4 33MB
  93. 10. Course Summary and Common Questions/1. Trading APIs and Deploying Your Strategy in the Real World.mp4 32MB
  94. 3. Time Series Analysis/1. Time Series Analysis Section Introduction.mp4 32MB
  95. 6. VIP The Basics of Reinforcement Learning/7. What does it mean to “learn”.mp4 32MB
  96. 4. Portfolio Optimization and CAPM/11. Mean-Variance Optimization.mp4 32MB
  97. 3. Time Series Analysis/4. The Naive Forecast.mp4 31MB
  98. 4. Portfolio Optimization and CAPM/12. The Efficient Frontier.mp4 31MB
  99. 4. Portfolio Optimization and CAPM/3. What is Risk.mp4 31MB
  100. 5. VIP Algorithmic Trading/9. Algorithmic Trading Section Summary.mp4 30MB
  101. 7. VIP Reinforcement Learning for Algorithmic Trading/3. Q-Learning in an Algorithmic Trading Context.mp4 30MB
  102. 2. Financial Basics/25. Mixture of Gaussians.mp4 29MB
  103. 2. Financial Basics/8. Returns.mp4 29MB
  104. 2. Financial Basics/1. Financial Basics Section Introduction.mp4 29MB
  105. 2. Financial Basics/23. Alpha and Beta.mp4 29MB
  106. 2. Financial Basics/4. Understanding Financial Data.mp4 29MB
  107. 2. Financial Basics/6. Dealing with Missing Data.mp4 28MB
  108. 4. Portfolio Optimization and CAPM/10. Maximum and Minimum Portfolio Return in Code.mp4 28MB
  109. 3. Time Series Analysis/22. PACF (Partial Autocorrelation Funtion).mp4 26MB
  110. 5. VIP Algorithmic Trading/7. Classification-Based Trading Strategy in Code.mp4 25MB
  111. 1. Welcome/4. How to Practice.mp4 25MB
  112. 1. Welcome/3. Scope of the course.mp4 24MB
  113. 4. Portfolio Optimization and CAPM/1. Portfolio Optimization Section Introduction.mp4 24MB
  114. 6. VIP The Basics of Reinforcement Learning/5. The Return.mp4 24MB
  115. 1. Welcome/5. Warmup (Optional).mp4 23MB
  116. 4. Portfolio Optimization and CAPM/6. Describing a Portfolio (pt 2).mp4 23MB
  117. 10. Course Summary and Common Questions/2. High Frequency Trading (HFT).mp4 22MB
  118. 2. Financial Basics/10. Adjusted Close (Code).mp4 21MB
  119. 2. Financial Basics/12. QQ-Plots.mp4 21MB
  120. 3. Time Series Analysis/5. Simple Moving Average (Theory).mp4 20MB
  121. 2. Financial Basics/14. The t-Distribution.mp4 20MB
  122. 3. Time Series Analysis/12. Holt's Linear Trend Model (Code).mp4 19MB
  123. 2. Financial Basics/27. Volatility Clustering.mp4 19MB
  124. 3. Time Series Analysis/31. Time Series Analysis Section Conclusion.mp4 18MB
  125. 4. Portfolio Optimization and CAPM/22. Portfolio Optimization Section Conclusion.mp4 17MB
  126. 15. Appendix FAQ Finale/1. What is the Appendix.mp4 16MB
  127. 2. Financial Basics/31. Suggestion Box.mp4 16MB
  128. 5. VIP Algorithmic Trading/1. Algorithmic Trading Section Introduction.mp4 14MB
  129. 4. Portfolio Optimization and CAPM/15. Global Minimum Variance (GMV) Portfolio in Code.mp4 14MB
  130. 4. Portfolio Optimization and CAPM/19. Risk-Free Asset and Tangency Portfolio in Code.mp4 14MB
  131. 11. Extras/2. VIP Finance Enthusiasts, Beware of Marketers!.mp4 14MB
  132. 2. Financial Basics/18. Confidence Intervals (Code).mp4 12MB
  133. 2. Financial Basics/29. Price Simulation (Code).mp4 12MB
  134. 2. Financial Basics/28. Price Simulation.mp4 12MB
  135. 4. Portfolio Optimization and CAPM/2. The S&P500.mp4 12MB
  136. 3. Time Series Analysis/16. Moving Average Models - MA(q).mp4 11MB
  137. 2. Financial Basics/30. Financial Basics Section Summary.mp4 10MB
  138. 4. Portfolio Optimization and CAPM/14. Global Minimum Variance (GMV) Portfolio.mp4 9MB
  139. 14. Effective Learning Strategies for Machine Learning FAQ/2. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.srt 32KB
  140. 6. VIP The Basics of Reinforcement Learning/2. Elements of a Reinforcement Learning Problem.srt 26KB
  141. 8. VIP Statistical Factor Models and Unsupervised Machine Learning/3. Statistical Factor Models (Advanced).srt 25KB
  142. 3. Time Series Analysis/18. ARIMA in Code (pt 1).srt 24KB
  143. 9. VIP Regime Detection and Sequence Modeling with Hidden Markov Models/5. HMM for Modeling Volatility Clustering in Code.srt 24KB
  144. 14. Effective Learning Strategies for Machine Learning FAQ/4. Machine Learning and AI Prerequisite Roadmap (pt 2).srt 24KB
  145. 13. Extra Help With Python Coding for Beginners FAQ/1. How to Code by Yourself (part 1).srt 23KB
  146. 8. VIP Statistical Factor Models and Unsupervised Machine Learning/1. Statistical Factor Models (Beginner).srt 21KB
  147. 2. Financial Basics/19. Statistical Testing.srt 21KB
  148. 12. Setting Up Your Environment FAQ/1. Anaconda Environment Setup.srt 20KB
  149. 9. VIP Regime Detection and Sequence Modeling with Hidden Markov Models/4. HMM Tasks and the Viterbi Algorithm.srt 19KB
  150. 3. Time Series Analysis/3. Random Walk Hypothesis.srt 19KB
  151. 9. VIP Regime Detection and Sequence Modeling with Hidden Markov Models/1. Why Sequence Models (pt 1).srt 19KB
  152. 8. VIP Statistical Factor Models and Unsupervised Machine Learning/4. Statistical Factor Models (Code).srt 19KB
  153. 7. VIP Reinforcement Learning for Algorithmic Trading/5. Q-Learning for Algorithmic Trading in Code.srt 18KB
  154. 4. Portfolio Optimization and CAPM/8. Visualizing Random Portfolios and Monte Carlo Simulation (pt 2).srt 18KB
  155. 3. Time Series Analysis/28. ARIMA in Code (pt 3).srt 18KB
  156. 6. VIP The Basics of Reinforcement Learning/11. Q-Learning.srt 18KB
  157. 5. VIP Algorithmic Trading/2. Trend-Following Strategy.srt 18KB
  158. 14. Effective Learning Strategies for Machine Learning FAQ/3. Machine Learning and AI Prerequisite Roadmap (pt 1).srt 17KB
  159. 3. Time Series Analysis/15. Autoregressive Models - AR(p).srt 17KB
  160. 3. Time Series Analysis/27. ARIMA in Code (pt 2).srt 17KB
  161. 3. Time Series Analysis/19. Stationarity.srt 16KB
  162. 4. Portfolio Optimization and CAPM/7. Visualizing Random Portfolios and Monte Carlo Simulation (pt 1).srt 16KB
  163. 2. Financial Basics/9. Adjusted Close, Stock Splits, and Dividends.srt 16KB
  164. 3. Time Series Analysis/2. Efficient Market Hypothesis.srt 16KB
  165. 9. VIP Regime Detection and Sequence Modeling with Hidden Markov Models/2. Why Sequence Models (pt 2).srt 16KB
  166. 4. Portfolio Optimization and CAPM/20. Capital Asset Pricing Model (CAPM).srt 16KB
  167. 7. VIP Reinforcement Learning for Algorithmic Trading/1. Trend-Following Strategy with Reinforcement Learning API.srt 16KB
  168. 2. Financial Basics/5. Understanding Financial Data (Code).srt 15KB
  169. 3. Time Series Analysis/13. Holt-Winters (Theory).srt 15KB
  170. 6. VIP The Basics of Reinforcement Learning/9. Solving the Bellman Equation with Reinforcement Learning (pt 2).srt 15KB
  171. 14. Effective Learning Strategies for Machine Learning FAQ/1. How to Succeed in this Course (Long Version).srt 15KB
  172. 3. Time Series Analysis/8. Exponentially-Weighted Moving Average (Code).srt 15KB
  173. 3. Time Series Analysis/7. Exponentially-Weighted Moving Average (Theory).srt 15KB
  174. 12. Setting Up Your Environment FAQ/2. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.srt 14KB
  175. 13. Extra Help With Python Coding for Beginners FAQ/3. Proof that using Jupyter Notebook is the same as not using it.srt 14KB
  176. 3. Time Series Analysis/9. Simple Exponential Smoothing for Forecasting (Theory).srt 14KB
  177. 3. Time Series Analysis/17. ARIMA.srt 14KB
  178. 2. Financial Basics/17. Confidence Intervals.srt 14KB
  179. 3. Time Series Analysis/26. Model Selection, AIC and BIC.srt 13KB
  180. 13. Extra Help With Python Coding for Beginners FAQ/2. How to Code by Yourself (part 2).srt 13KB
  181. 8. VIP Statistical Factor Models and Unsupervised Machine Learning/2. Statistical Factor Models (Intermediate).srt 13KB
  182. 3. Time Series Analysis/21. ACF (Autocorrelation Function).srt 13KB
  183. 6. VIP The Basics of Reinforcement Learning/4. Markov Decision Processes (MDPs).srt 13KB
  184. 3. Time Series Analysis/10. Simple Exponential Smoothing for Forecasting (Code).srt 13KB
  185. 6. VIP The Basics of Reinforcement Learning/6. Value Functions and the Bellman Equation.srt 13KB
  186. 4. Portfolio Optimization and CAPM/9. Maximum and Minimum Portfolio Return.srt 12KB
  187. 6. VIP The Basics of Reinforcement Learning/8. Solving the Bellman Equation with Reinforcement Learning (pt 1).srt 12KB
  188. 4. Portfolio Optimization and CAPM/18. Portfolio with a Risk-Free Asset and Tangency Portfolio.srt 12KB
  189. 1. Welcome/2. Where to get the code.srt 12KB
  190. 9. VIP Regime Detection and Sequence Modeling with Hidden Markov Models/3. HMM Parameters.srt 12KB
  191. 4. Portfolio Optimization and CAPM/5. Describing a Portfolio (pt 1).srt 12KB
  192. 3. Time Series Analysis/25. Auto ARIMA and SARIMAX.srt 12KB
  193. 4. Portfolio Optimization and CAPM/21. Problems with Markowitz Portfolio Theory and Robust Estimation.srt 12KB
  194. 3. Time Series Analysis/30. Forecasting.srt 12KB
  195. 5. VIP Algorithmic Trading/4. Trend-Following Strategy in Code (pt 2).srt 12KB
  196. 2. Financial Basics/8. Returns.srt 12KB
  197. 6. VIP The Basics of Reinforcement Learning/3. States, Actions, Rewards, Policies.srt 12KB
  198. 4. Portfolio Optimization and CAPM/13. Mean-Variance Optimization And The Efficient Frontier in Code.srt 11KB
  199. 2. Financial Basics/21. Covariance and Correlation.srt 11KB
  200. 3. Time Series Analysis/20. Stationarity Code.srt 11KB
  201. 7. VIP Reinforcement Learning for Algorithmic Trading/2. Trend-Following Strategy Revisited (Code).srt 11KB
  202. 4. Portfolio Optimization and CAPM/4. Why Diversify.srt 11KB
  203. 2. Financial Basics/15. The t-Distribution (Code).srt 10KB
  204. 2. Financial Basics/24. Alpha and Beta (Code).srt 10KB
  205. 5. VIP Algorithmic Trading/6. Machine Learning-Based Trading Strategy in Code.srt 10KB
  206. 2. Financial Basics/16. Skewness and Kurtosis.srt 10KB
  207. 5. VIP Algorithmic Trading/5. Machine Learning-Based Trading Strategy.srt 10KB
  208. 3. Time Series Analysis/11. Holt's Linear Trend Model (Theory).srt 10KB
  209. 4. Portfolio Optimization and CAPM/11. Mean-Variance Optimization.srt 10KB
  210. 4. Portfolio Optimization and CAPM/16. Sharpe Ratio.srt 10KB
  211. 2. Financial Basics/2. Getting Financial Data.srt 10KB
  212. 2. Financial Basics/13. QQ-Plots (Code).srt 10KB
  213. 3. Time Series Analysis/14. Holt-Winters (Code).srt 10KB
  214. 1. Welcome/1. Introduction and Outline.srt 10KB
  215. 7. VIP Reinforcement Learning for Algorithmic Trading/4. Representing States.srt 10KB
  216. 4. Portfolio Optimization and CAPM/12. The Efficient Frontier.srt 10KB
  217. 2. Financial Basics/3. Getting Financial Data (Code).srt 9KB
  218. 3. Time Series Analysis/6. Simple Moving Average (Code).srt 9KB
  219. 5. VIP Algorithmic Trading/3. Trend-Following Strategy in Code (pt 1).srt 9KB
  220. 4. Portfolio Optimization and CAPM/3. What is Risk.srt 9KB
  221. 3. Time Series Analysis/23. ACF and PACF in Code (pt 1).srt 9KB
  222. 3. Time Series Analysis/1. Time Series Analysis Section Introduction.srt 9KB
  223. 7. VIP Reinforcement Learning for Algorithmic Trading/3. Q-Learning in an Algorithmic Trading Context.srt 9KB
  224. 2. Financial Basics/23. Alpha and Beta.srt 9KB
  225. 3. Time Series Analysis/4. The Naive Forecast.srt 9KB
  226. 2. Financial Basics/25. Mixture of Gaussians.srt 9KB
  227. 2. Financial Basics/11. Back to Returns (Code).srt 9KB
  228. 2. Financial Basics/20. Statistical Testing (Code).srt 9KB
  229. 2. Financial Basics/7. Dealing with Missing Data (Code).srt 9KB
  230. 6. VIP The Basics of Reinforcement Learning/7. What does it mean to “learn”.srt 9KB
  231. 6. VIP The Basics of Reinforcement Learning/1. Reinforcement Learning Section Introduction.srt 9KB
  232. 3. Time Series Analysis/29. ACF and PACF for Stock Returns.srt 8KB
  233. 4. Portfolio Optimization and CAPM/17. Maximum Sharpe Ratio in Code.srt 8KB
  234. 2. Financial Basics/26. Mixture of Gaussians (Code).srt 8KB
  235. 3. Time Series Analysis/24. ACF and PACF in Code (pt 2).srt 8KB
  236. 3. Time Series Analysis/22. PACF (Partial Autocorrelation Funtion).srt 8KB
  237. 4. Portfolio Optimization and CAPM/6. Describing a Portfolio (pt 2).srt 8KB
  238. 15. Appendix FAQ Finale/2. BONUS Lecture.srt 8KB
  239. 2. Financial Basics/6. Dealing with Missing Data.srt 8KB
  240. 10. Course Summary and Common Questions/1. Trading APIs and Deploying Your Strategy in the Real World.srt 8KB
  241. 6. VIP The Basics of Reinforcement Learning/12. How to Learn Reinforcement Learning.srt 8KB
  242. 5. VIP Algorithmic Trading/9. Algorithmic Trading Section Summary.srt 8KB
  243. 6. VIP The Basics of Reinforcement Learning/10. Epsilon-Greedy.srt 7KB
  244. 2. Financial Basics/1. Financial Basics Section Introduction.srt 7KB
  245. 2. Financial Basics/12. QQ-Plots.srt 7KB
  246. 2. Financial Basics/22. Covariance and Correlation (Code).srt 7KB
  247. 2. Financial Basics/4. Understanding Financial Data.srt 7KB
  248. 6. VIP The Basics of Reinforcement Learning/5. The Return.srt 6KB
  249. 1. Welcome/5. Warmup (Optional).srt 6KB
  250. 4. Portfolio Optimization and CAPM/10. Maximum and Minimum Portfolio Return in Code.srt 6KB
  251. 3. Time Series Analysis/5. Simple Moving Average (Theory).srt 6KB
  252. 5. VIP Algorithmic Trading/8. Using a Random Forest Classifier for Machine Learning-Based Trading.srt 6KB
  253. 3. Time Series Analysis/31. Time Series Analysis Section Conclusion.srt 5KB
  254. 10. Course Summary and Common Questions/2. High Frequency Trading (HFT).srt 5KB
  255. 1. Welcome/4. How to Practice.srt 5KB
  256. 1. Welcome/3. Scope of the course.srt 5KB
  257. 2. Financial Basics/14. The t-Distribution.srt 5KB
  258. 4. Portfolio Optimization and CAPM/1. Portfolio Optimization Section Introduction.srt 5KB
  259. 2. Financial Basics/31. Suggestion Box.srt 5KB
  260. 2. Financial Basics/10. Adjusted Close (Code).srt 5KB
  261. 5. VIP Algorithmic Trading/7. Classification-Based Trading Strategy in Code.srt 4KB
  262. 3. Time Series Analysis/16. Moving Average Models - MA(q).srt 4KB
  263. 2. Financial Basics/28. Price Simulation.srt 4KB
  264. 2. Financial Basics/27. Volatility Clustering.srt 4KB
  265. 15. Appendix FAQ Finale/1. What is the Appendix.srt 4KB
  266. 5. VIP Algorithmic Trading/1. Algorithmic Trading Section Introduction.srt 4KB
  267. 3. Time Series Analysis/12. Holt's Linear Trend Model (Code).srt 3KB
  268. 4. Portfolio Optimization and CAPM/2. The S&P500.srt 3KB
  269. 2. Financial Basics/29. Price Simulation (Code).srt 3KB
  270. 2. Financial Basics/30. Financial Basics Section Summary.srt 3KB
  271. 4. Portfolio Optimization and CAPM/22. Portfolio Optimization Section Conclusion.srt 3KB
  272. 2. Financial Basics/18. Confidence Intervals (Code).srt 3KB
  273. 11. Extras/2. VIP Finance Enthusiasts, Beware of Marketers!.srt 3KB
  274. 4. Portfolio Optimization and CAPM/19. Risk-Free Asset and Tangency Portfolio in Code.srt 3KB
  275. 4. Portfolio Optimization and CAPM/15. Global Minimum Variance (GMV) Portfolio in Code.srt 2KB
  276. 4. Portfolio Optimization and CAPM/14. Global Minimum Variance (GMV) Portfolio.srt 2KB
  277. 11. Extras/1. Colab Notebooks.html 256B
  278. 1. Welcome/[Tutorialsplanet.NET].url 128B
  279. 11. Extras/[Tutorialsplanet.NET].url 128B
  280. [Tutorialsplanet.NET].url 128B
  281. 1. Welcome/2.1 Github Link.html 116B