[Tutorialsplanet.NET] Udemy - Python for Finance Investment Fundamentals & Data Analytics

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[Tutorialsplanet.NET] Udemy - Python for Finance Investment Fundamentals & Data Analytics

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种子哈希：3946ed1b5c459e6f2400fc3cd18e9504649975bd
文件大小： 1.48G
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收录时间：2021-03-15
最近下载：2025-12-21

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文件列表

  • 10. Advanced Python tools/17. Importing and Organizing Data in Python – part II.A.mp4 69.8 MB
  • 3. Python Variables and Data Types/5. Strings.mp4 60.4 MB
  • 2. Introduction to programming with Python/7. Installing Python and Jupyter.mp4 56.4 MB
  • 6. Conditional Statements/4. Else if, for Brief – ELIF.mp4 55.8 MB
  • 8. Python Sequences/7. Dictionaries.mp4 43.8 MB
  • 10. Advanced Python tools/14. Sources of Financial Data.mp4 40.7 MB
  • 7. Python Functions/2. Creating a Function with a Parameter.mp4 40.0 MB
  • 8. Python Sequences/1. Lists.mp4 39.6 MB
  • 8. Python Sequences/3. Using Methods.mp4 39.4 MB
  • 10. Advanced Python tools/18. Importing and Organizing Data in Python – part II.B.mp4 38.6 MB
  • 9. Using Iterations in Python/8. Iterating over Dictionaries.mp4 31.1 MB
  • 8. Python Sequences/6. Tuples.mp4 30.9 MB
  • 9. Using Iterations in Python/3. While Loops and Incrementing.mp4 29.9 MB
  • 9. Using Iterations in Python/6. Use Conditional Statements and Loops Together.mp4 29.1 MB
  • 3. Python Variables and Data Types/1. Variables.mp4 27.9 MB
  • 10. Advanced Python tools/8. Importing Modules - Quiz.html 27.1 MB
  • 9. Using Iterations in Python/4. Create Lists with the range() Function.mp4 27.0 MB
  • 7. Python Functions/3. Another Way to Define a Function.mp4 26.5 MB
  • 10. Advanced Python tools/16. Importing and Organizing Data in Python – part I.mp4 25.2 MB
  • 9. Using Iterations in Python/1. For Loops.mp4 24.7 MB
  • 6. Conditional Statements/3. Add an ELSE statement.mp4 24.4 MB
  • 6. Conditional Statements/1. Introduction to the IF statement.mp4 24.4 MB
  • 11/4. Calculating a security's rate of return.mp4 22.5 MB
  • 6. Conditional Statements/5. A Note on Boolean values.mp4 20.9 MB
  • 10. Advanced Python tools/13. A Note on Using Financial Data in Python.mp4 19.7 MB
  • 2. Introduction to programming with Python/3. Why Python.mp4 16.4 MB
  • 11/12. Popular stock indices that can help us understand financial markets.mp4 16.4 MB
  • 16/3. Running a multivariate regression in Python.mp4 16.1 MB
  • 11/11. Calculating a Portfolio of Securities' Rate of Return.mp4 15.9 MB
  • 2. Introduction to programming with Python/1. Programming Explained in 5 Minutes.mp4 15.6 MB
  • 7. Python Functions/1. Defining a Function in Python.mp4 15.5 MB
  • 7. Python Functions/7. Creating Functions Containing a Few Arguments.mp4 15.4 MB
  • 2. Introduction to programming with Python/11. Python 2 vs Python 3 What's the Difference.mp4 14.2 MB
  • 4. Basic Python Syntax/12. Structure Your Code with Indentation.mp4 13.7 MB
  • 1. Welcome! Course Introduction/1. What Does the Course Cover.mp4 13.7 MB
  • 17/5. Monte Carlo Predicting Gross Profit – Part I.mp4 13.7 MB
  • 2. Introduction to programming with Python/9. Jupyter’s Interface – Prerequisites for Coding.mp4 12.9 MB
  • 14. PART II Finance - Markowitz Portfolio Optimization/4. Obtaining the Efficient Frontier in Python – Part II.mp4 12.2 MB
  • 4. Basic Python Syntax/7. Add Comments.mp4 11.7 MB
  • 14. PART II Finance - Markowitz Portfolio Optimization/1. Markowitz Portfolio Theory - One of the main pillars of modern Finance.mp4 11.4 MB
  • 17/17. Monte Carlo Euler Discretization - Part I.mp4 11.4 MB
  • 12. PART II Finance Measuring Investment Risk/3. Calculating a Security’s Risk in Python.mp4 11.3 MB
  • 11/6. Calculating a Security’s Rate of Return in Python – Simple Returns – Part I.mp4 11.1 MB
  • 17/15. Monte Carlo Black-Scholes-Merton.mp4 10.7 MB
  • 10. Advanced Python tools/20. Changing the Index of Your Time-Series Data.mp4 10.7 MB
  • 13/6. Computing Alpha, Beta, and R Squared in Python.mp4 10.5 MB
  • 13/3. Running a Regression in Python.mp4 10.5 MB
  • 10. Advanced Python tools/15. Accessing the Notebook Files.mp4 10.4 MB
  • 2. Introduction to programming with Python/5. Why Jupyter.mp4 10.3 MB
  • 17/12. An Introduction to Derivative Contracts.mp4 9.8 MB
  • 11/14. Calculating the Indices' Rate of Return.mp4 9.8 MB
  • 12. PART II Finance Measuring Investment Risk/1. How do we measure a security's risk.mp4 9.8 MB
  • 16/1. Multivariate regression analysis - a valuable tool for finance practitioners.mp4 9.7 MB
  • 14. PART II Finance - Markowitz Portfolio Optimization/3. Obtaining the Efficient Frontier in Python – Part I.mp4 9.2 MB
  • 10. Advanced Python tools/21. Restarting the Jupyter Kernel.mp4 9.2 MB
  • 10. Advanced Python tools/9. Must-have packages for Finance and Data Science.mp4 9.1 MB
  • 12. PART II Finance Measuring Investment Risk/10. Calculating Covariance and Correlation.mp4 8.8 MB
  • 1. Welcome! Course Introduction/2. Download Useful Resources - Exercises and Solutions.mp4 8.6 MB
  • 10. Advanced Python tools/19. Importing and Organizing Data in Python – part III.mp4 8.4 MB
  • 17/10. Monte Carlo Forecasting Stock Prices - Part II.mp4 8.4 MB
  • 10. Advanced Python tools/11. Working with arrays.mp4 8.3 MB
  • 5. Python Operators Continued/3. Logical and Identity Operators.mp4 8.3 MB
  • 12. PART II Finance Measuring Investment Risk/11. Considering the risk of multiple securities in a portfolio.mp4 8.1 MB
  • 13/4. Are all regressions created equal Learning how to distinguish good regressions.mp4 8.0 MB
  • 15/1. The intuition behind the Capital Asset Pricing Model (CAPM).mp4 7.9 MB
  • 8. Python Sequences/5. List Slicing.mp4 7.7 MB
  • 17/11. Monte Carlo Forecasting Stock Prices - Part III.mp4 7.4 MB
  • 17/14. The Black Scholes Formula for Option Pricing.mp4 7.4 MB
  • 12. PART II Finance Measuring Investment Risk/15. Calculating Diversifiable and Non-Diversifiable Risk of a Portfolio.mp4 7.4 MB
  • 10. Advanced Python tools/1. Object Oriented Programming.mp4 7.2 MB
  • 15/12. Measuring alpha and verifying how good (or bad) a portfolio manager is doing.mp4 6.8 MB
  • 17/7. Forecasting Stock Prices with a Monte Carlo Simulation.mp4 6.7 MB
  • 11/8. Calculating a Security’s Return in Python – Logarithmic Returns.mp4 6.7 MB
  • 15/5. Calculating the Beta of a Stock.mp4 6.6 MB
  • 15/3. Understanding and calculating a security's Beta.mp4 6.6 MB
  • 11/1. Considering both risk and return.mp4 6.5 MB
  • 15/6. The CAPM formula.mp4 6.4 MB
  • 17/9. Monte Carlo Forecasting Stock Prices - Part I.mp4 6.2 MB
  • 10. Advanced Python tools/7. Importing Modules.mp4 6.2 MB
  • 12. PART II Finance Measuring Investment Risk/6. Calculating the covariance between securities.mp4 6.2 MB
  • 7. Python Functions/8. Notable Built-in Functions in Python.mp4 6.1 MB
  • 12. PART II Finance Measuring Investment Risk/4. The benefits of portfolio diversification.mp4 6.0 MB
  • 12. PART II Finance Measuring Investment Risk/8. Measuring the correlation between stocks.mp4 6.0 MB
  • 13/1. The fundamentals of simple regression analysis.mp4 5.9 MB
  • 11/7. Calculating a Security’s Rate of Return in Python – Simple Returns – Part II.mp4 5.7 MB
  • 4. Basic Python Syntax/1. Arithmetic Operators.mp4 5.3 MB
  • 17/6. Monte Carlo Predicting Gross Profit – Part II.mp4 5.1 MB
  • 12. PART II Finance Measuring Investment Risk/13. Understanding Systematic vs. Idiosyncratic risk.mp4 5.1 MB
  • 3. Python Variables and Data Types/3. Numbers and Boolean Values.mp4 4.7 MB
  • 12. PART II Finance Measuring Investment Risk/12. Calculating Portfolio Risk.mp4 4.6 MB
  • 7. Python Functions/6. Combining Conditional Statements and Functions.mp4 4.6 MB
  • 11/9. What is a portfolio of securities and how to calculate its rate of return.mp4 4.5 MB
  • 2. Introduction to programming with Python/8. Jupyter’s Interface – the Dashboard.mp4 4.5 MB
  • 17/3. Monte Carlo applied in a Corporate Finance context.mp4 4.3 MB
  • 17/1. The essence of Monte Carlo simulations.mp4 4.3 MB
  • 11/3. What are we going to see next.mp4 4.3 MB
  • 10. Advanced Python tools/5. The Standard Library.mp4 4.2 MB
  • 15/8. Calculating the Expected Return of a Stock (CAPM).mp4 4.2 MB
  • 10. Advanced Python tools/12. Generating Random Numbers.mp4 4.0 MB
  • 14. PART II Finance - Markowitz Portfolio Optimization/5. Obtaining the Efficient Frontier in Python – Part III.mp4 3.9 MB
  • 15/9. Introducing the Sharpe ratio and how to put it into practice.mp4 3.8 MB
  • 17/18. Monte Carlo Euler Discretization - Part II.mp4 3.7 MB
  • 5. Python Operators Continued/1. Comparison Operators.mp4 3.0 MB
  • 9. Using Iterations in Python/7. All In – Conditional Statements, Functions, and Loops.mp4 3.0 MB
  • 7. Python Functions/5. Using a Function in another Function.mp4 2.4 MB
  • 15/11. Obtaining the Sharpe ratio in Python.mp4 2.2 MB
  • 2. Introduction to programming with Python/1.1 Python for Finance - Course Notes - Part I.pdf 2.1 MB
  • 2. Introduction to programming with Python/11.1 Python for Finance - Course Notes - Part I.pdf 2.1 MB
  • 4. Basic Python Syntax/3. The Double Equality Sign.mp4 2.0 MB
  • 4. Basic Python Syntax/10. Indexing Elements.mp4 1.9 MB
  • 10. Advanced Python tools/3. Modules and Packages.mp4 1.7 MB
  • 4. Basic Python Syntax/5. Reassign Values.mp4 1.5 MB
  • 14. PART II Finance - Markowitz Portfolio Optimization/1.2 Python for Finance Course Notes - Part II.pdf 1.4 MB
  • 11/9.1 Python for Finance Course Notes - Part II.pdf 1.1 MB
  • 11/1.1 Python for Finance Course Notes - Part II.pdf 1.1 MB
  • 11/12.1 Python for Finance Course Notes - Part II.pdf 1.1 MB
  • 11/3.1 Python for Finance Course Notes - Part II.pdf 1.1 MB
  • 11/4.1 Python for Finance Course Notes - Part II.pdf 1.1 MB
  • 12. PART II Finance Measuring Investment Risk/1.1 Python for Finance Course Notes - Part II.pdf 1.1 MB
  • 12. PART II Finance Measuring Investment Risk/11.1 Python for Finance Course Notes - Part II.pdf 1.1 MB
  • 12. PART II Finance Measuring Investment Risk/13.1 Python for Finance Course Notes - Part II.pdf 1.1 MB
  • 12. PART II Finance Measuring Investment Risk/4.1 Python for Finance Course Notes - Part II.pdf 1.1 MB
  • 12. PART II Finance Measuring Investment Risk/6.1 Python for Finance Course Notes - Part II.pdf 1.1 MB
  • 12. PART II Finance Measuring Investment Risk/8.1 Python for Finance Course Notes - Part II.pdf 1.1 MB
  • 13/1.1 Python for Finance Course Notes - Part II.pdf 1.1 MB
  • 13/4.1 Python for Finance Course Notes - Part II.pdf 1.1 MB
  • 15/1.1 Python for Finance Course Notes - Part II.pdf 1.1 MB
  • 15/12.1 Python for Finance Course Notes - Part II.pdf 1.1 MB
  • 15/3.1 Python for Finance Course Notes - Part II.pdf 1.1 MB
  • 15/6.1 Python for Finance Course Notes - Part II.pdf 1.1 MB
  • 15/9.1 Python for Finance Course Notes - Part II.pdf 1.1 MB
  • 16/1.1 Python for Finance Course Notes - Part II.pdf 1.1 MB
  • 17/1.2 Python for Finance Course Notes - Part II.pdf 1.1 MB
  • 17/12.1 Python for Finance Course Notes - Part II.pdf 1.1 MB
  • 17/14.1 Python for Finance Course Notes - Part II.pdf 1.1 MB
  • 17/3.1 Python for Finance Course Notes - Part II.pdf 1.1 MB
  • 1. Welcome! Course Introduction/2.1 Python for Finance - FAQ.pdf 1.0 MB
  • 4. Basic Python Syntax/9. Line Continuation.mp4 1.0 MB
  • 2. Introduction to programming with Python/9.1 Jupyter_Shortcuts.pdf 603.7 kB
  • 10. Advanced Python tools/9.2 47 Packages Exercise.pdf 262.3 kB
  • 11/14.1 Indices_Data_1.csv 238.5 kB
  • 11/14.2 Indices_Data_2.csv 114.9 kB
  • 14. PART II Finance - Markowitz Portfolio Optimization/3.2 Markowitz_Data.csv 60.0 kB
  • 14. PART II Finance - Markowitz Portfolio Optimization/4.1 Markowitz_Data.csv 60.0 kB
  • 14. PART II Finance - Markowitz Portfolio Optimization/5.2 Markowitz_Data.csv 60.0 kB
  • 15/11.2 CAPM_Data.csv 41.7 kB
  • 15/5.1 CAPM_Data.csv 41.7 kB
  • 15/8.1 CAPM_Data.csv 41.7 kB
  • 3. Python Variables and Data Types/5. Strings.srt 16.2 kB
  • 14. PART II Finance - Markowitz Portfolio Optimization/1.1 14. Markowitz Efficient frontier.xlsx 15.9 kB
  • 13/1.2 Housing Data.xlsx 14.8 kB
  • 6. Conditional Statements/4. Else if, for Brief – ELIF.srt 13.5 kB
  • 13/3.2 Housing.xlsx 10.3 kB
  • 13/6.2 Housing.xlsx 10.3 kB
  • 16/3.2 Housing.xlsx 10.3 kB
  • 8. Python Sequences/1. Lists.srt 10.1 kB
  • 11/11. Calculating a Portfolio of Securities' Rate of Return.srt 9.9 kB
  • 2. Introduction to programming with Python/7. Installing Python and Jupyter.srt 9.6 kB
  • 7. Python Functions/2. Creating a Function with a Parameter.srt 9.2 kB
  • 8. Python Sequences/7. Dictionaries.srt 8.6 kB
  • 8. Python Sequences/3. Using Methods.srt 8.6 kB
  • 10. Advanced Python tools/14. Sources of Financial Data.srt 8.5 kB
  • 17/12. An Introduction to Derivative Contracts.srt 8.3 kB
  • 10. Advanced Python tools/17. Importing and Organizing Data in Python – part II.A.srt 8.2 kB
  • 17/17. Monte Carlo Euler Discretization - Part I.srt 8.2 kB
  • 9. Using Iterations in Python/8. Iterating over Dictionaries.srt 8.1 kB
  • 2. Introduction to programming with Python/9. Jupyter’s Interface – Prerequisites for Coding.srt 7.9 kB
  • 16/3. Running a multivariate regression in Python.srt 7.9 kB
  • 9. Using Iterations in Python/4. Create Lists with the range() Function.srt 7.8 kB
  • 14. PART II Finance - Markowitz Portfolio Optimization/1. Markowitz Portfolio Theory - One of the main pillars of modern Finance.srt 7.8 kB
  • 6. Conditional Statements/1. Introduction to the IF statement.srt 7.8 kB
  • 13/3. Running a Regression in Python.srt 7.8 kB
  • 17/15. Monte Carlo Black-Scholes-Merton.srt 7.7 kB
  • 9. Using Iterations in Python/6. Use Conditional Statements and Loops Together.srt 7.6 kB
  • 12. PART II Finance Measuring Investment Risk/1. How do we measure a security's risk.srt 7.6 kB
  • 1. Welcome! Course Introduction/1. What Does the Course Cover.srt 7.4 kB
  • 11/4. Calculating a security's rate of return.srt 7.3 kB
  • 12. PART II Finance Measuring Investment Risk/3. Calculating a Security’s Risk in Python.srt 7.2 kB
  • 2. Introduction to programming with Python/3. Why Python.srt 7.1 kB
  • 17/5. Monte Carlo Predicting Gross Profit – Part I.srt 7.1 kB
  • 10. Advanced Python tools/11. Working with arrays.srt 7.1 kB
  • 8. Python Sequences/6. Tuples.srt 7.1 kB
  • 2. Introduction to programming with Python/1. Programming Explained in 5 Minutes.srt 7.1 kB
  • 16/1. Multivariate regression analysis - a valuable tool for finance practitioners.srt 7.0 kB
  • 13/6. Computing Alpha, Beta, and R Squared in Python.srt 6.9 kB
  • 9. Using Iterations in Python/1. For Loops.srt 6.7 kB
  • 7. Python Functions/3. Another Way to Define a Function.srt 6.6 kB
  • 11/6. Calculating a Security’s Rate of Return in Python – Simple Returns – Part I.srt 6.5 kB
  • 6. Conditional Statements/3. Add an ELSE statement.srt 6.4 kB
  • 6. Conditional Statements/5. A Note on Boolean values.srt 6.4 kB
  • 3. Python Variables and Data Types/1. Variables.srt 6.3 kB
  • 15/1. The intuition behind the Capital Asset Pricing Model (CAPM).srt 6.3 kB
  • 10. Advanced Python tools/1. Object Oriented Programming.srt 6.2 kB
  • 13/4. Are all regressions created equal Learning how to distinguish good regressions.srt 6.2 kB
  • 14. PART II Finance - Markowitz Portfolio Optimization/3. Obtaining the Efficient Frontier in Python – Part I.srt 6.2 kB
  • 11/14. Calculating the Indices' Rate of Return.srt 6.2 kB
  • 17/14. The Black Scholes Formula for Option Pricing.srt 6.1 kB
  • 14. PART II Finance - Markowitz Portfolio Optimization/4. Obtaining the Efficient Frontier in Python – Part II.srt 6.1 kB
  • 9. Using Iterations in Python/3. While Loops and Incrementing.srt 6.0 kB
  • 12. PART II Finance Measuring Investment Risk/10. Calculating Covariance and Correlation.srt 5.9 kB
  • 10. Advanced Python tools/9. Must-have packages for Finance and Data Science.srt 5.9 kB
  • 5. Python Operators Continued/3. Logical and Identity Operators.srt 5.8 kB
  • 8. Python Sequences/5. List Slicing.srt 5.6 kB
  • 17/10. Monte Carlo Forecasting Stock Prices - Part II.srt 5.6 kB
  • 17/7. Forecasting Stock Prices with a Monte Carlo Simulation.srt 5.6 kB
  • 15/6. The CAPM formula.srt 5.6 kB
  • 7. Python Functions/1. Defining a Function in Python.srt 5.4 kB
  • 15/12. Measuring alpha and verifying how good (or bad) a portfolio manager is doing.srt 5.4 kB
  • 15/3. Understanding and calculating a security's Beta.srt 5.4 kB
  • 17/11. Monte Carlo Forecasting Stock Prices - Part III.srt 5.3 kB
  • 10. Advanced Python tools/7. Importing Modules.srt 5.2 kB
  • 10. Advanced Python tools/18. Importing and Organizing Data in Python – part II.B.srt 5.2 kB
  • 12. PART II Finance Measuring Investment Risk/15. Calculating Diversifiable and Non-Diversifiable Risk of a Portfolio.srt 5.0 kB
  • 12. PART II Finance Measuring Investment Risk/8. Measuring the correlation between stocks.srt 4.9 kB
  • 4. Basic Python Syntax/12. Structure Your Code with Indentation.srt 4.8 kB
  • 13/1. The fundamentals of simple regression analysis.srt 4.8 kB
  • 12. PART II Finance Measuring Investment Risk/4. The benefits of portfolio diversification.srt 4.8 kB
  • 2. Introduction to programming with Python/5. Why Jupyter.srt 4.7 kB
  • 10. Advanced Python tools/19. Importing and Organizing Data in Python – part III.srt 4.6 kB
  • 11/8. Calculating a Security’s Return in Python – Logarithmic Returns.srt 4.5 kB
  • 12. PART II Finance Measuring Investment Risk/6. Calculating the covariance between securities.srt 4.4 kB
  • 11/7. Calculating a Security’s Rate of Return in Python – Simple Returns – Part II.srt 4.4 kB
  • 15/5. Calculating the Beta of a Stock.srt 4.4 kB
  • 17/9. Monte Carlo Forecasting Stock Prices - Part I.srt 4.3 kB
  • 11/12. Popular stock indices that can help us understand financial markets.srt 4.3 kB
  • 7. Python Functions/8. Notable Built-in Functions in Python.srt 4.3 kB
  • 4. Basic Python Syntax/1. Arithmetic Operators.srt 4.2 kB
  • 10. Advanced Python tools/16. Importing and Organizing Data in Python – part I.srt 4.2 kB
  • 12. PART II Finance Measuring Investment Risk/11. Considering the risk of multiple securities in a portfolio.srt 4.1 kB
  • 4. Basic Python Syntax/7. Add Comments.srt 4.0 kB
  • 2. Introduction to programming with Python/8. Jupyter’s Interface – the Dashboard.srt 3.8 kB
  • 3. Python Variables and Data Types/3. Numbers and Boolean Values.srt 3.7 kB
  • 1. Welcome! Course Introduction/2. Download Useful Resources - Exercises and Solutions.srt 3.7 kB
  • 17/6. Monte Carlo Predicting Gross Profit – Part II.srt 3.7 kB
  • 10. Advanced Python tools/5. The Standard Library.srt 3.7 kB
  • 10. Advanced Python tools/13. A Note on Using Financial Data in Python.srt 3.7 kB
  • 12. PART II Finance Measuring Investment Risk/13. Understanding Systematic vs. Idiosyncratic risk.srt 3.7 kB
  • 7. Python Functions/6. Combining Conditional Statements and Functions.srt 3.6 kB
  • 2. Introduction to programming with Python/11. Python 2 vs Python 3 What's the Difference.srt 3.6 kB
  • 10. Advanced Python tools/20. Changing the Index of Your Time-Series Data.srt 3.6 kB
  • 11/3. What are we going to see next.srt 3.3 kB
  • 17/1. The essence of Monte Carlo simulations.srt 3.3 kB
  • 10. Advanced Python tools/12. Generating Random Numbers.srt 3.2 kB
  • 10. Advanced Python tools/15. Accessing the Notebook Files.srt 3.1 kB
  • 15/9. Introducing the Sharpe ratio and how to put it into practice.srt 3.1 kB
  • 7. Python Functions/7. Creating Functions Containing a Few Arguments.srt 3.1 kB
  • 11/9. What is a portfolio of securities and how to calculate its rate of return.srt 3.1 kB
  • 17/3. Monte Carlo applied in a Corporate Finance context.srt 3.0 kB
  • 12. PART II Finance Measuring Investment Risk/12. Calculating Portfolio Risk.srt 3.0 kB
  • 15/8. Calculating the Expected Return of a Stock (CAPM).srt 3.0 kB
  • 17/18. Monte Carlo Euler Discretization - Part II.srt 2.9 kB
  • 11/1. Considering both risk and return.srt 2.9 kB
  • 10. Advanced Python tools/21. Restarting the Jupyter Kernel.srt 2.8 kB
  • 14. PART II Finance - Markowitz Portfolio Optimization/5. Obtaining the Efficient Frontier in Python – Part III.srt 2.6 kB
  • 5. Python Operators Continued/1. Comparison Operators.srt 2.5 kB
  • 9. Using Iterations in Python/7. All In – Conditional Statements, Functions, and Loops.srt 2.4 kB
  • 7. Python Functions/5. Using a Function in another Function.srt 2.1 kB
  • 18. BONUS LECTURE/1. Bonus Lecture Next Steps.html 1.9 kB
  • 4. Basic Python Syntax/3. The Double Equality Sign.srt 1.9 kB
  • 4. Basic Python Syntax/10. Indexing Elements.srt 1.7 kB
  • 15/11. Obtaining the Sharpe ratio in Python.srt 1.7 kB
  • 10. Advanced Python tools/3. Modules and Packages.srt 1.4 kB
  • 4. Basic Python Syntax/5. Reassign Values.srt 1.3 kB
  • 4. Basic Python Syntax/9. Line Continuation.srt 1.1 kB
  • 7. Python Functions/4. Another Way to Define a Function.html 168 Bytes
  • 10. Advanced Python tools/10. Must-have packages - Quiz.html 167 Bytes
  • 10. Advanced Python tools/2. Object Oriented Programming - Quiz.html 167 Bytes
  • 10. Advanced Python tools/4. Modules - Quiz.html 167 Bytes
  • 10. Advanced Python tools/6. The Standard Library - Quiz.html 167 Bytes
  • 11/10. What is a portfolio of securities and how to calculate its rate of return - Quiz.html 167 Bytes
  • 11/13. Which of the following is not an index - Quiz.html 167 Bytes
  • 11/2. Risk and return - Quiz.html 167 Bytes
  • 11/5. Calculating a security's rate of return.html 167 Bytes
  • 12. PART II Finance Measuring Investment Risk/14. Diversifiable Risk - Quiz.html 167 Bytes
  • 12. PART II Finance Measuring Investment Risk/2. Which of the following sentences is true - Quiz.html 167 Bytes
  • 12. PART II Finance Measuring Investment Risk/5. Investing in stocks - Quiz.html 167 Bytes
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  • 13/5. Regressions - Quiz.html 167 Bytes
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  • 17/2. Monte Carlo - Quiz.html 167 Bytes
  • 17/4. Monte Carlo in Corporate Finance - Quiz.html 167 Bytes
  • 17/8. Monte Carlo Simulations - Quiz.html 167 Bytes
  • 2. Introduction to programming with Python/10. Jupyter’s Interface.html 167 Bytes
  • 2. Introduction to programming with Python/2. Programming Explained in 5 Minutes.html 167 Bytes
  • 2. Introduction to programming with Python/4. Why Python.html 167 Bytes
  • 2. Introduction to programming with Python/6. Why Jupyter.html 167 Bytes
  • 3. Python Variables and Data Types/2. Variables.html 167 Bytes
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  • 5. Python Operators Continued/2. Comparison Operators.html 167 Bytes
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  • 6. Conditional Statements/2. Introduction to the IF statement.html 167 Bytes
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  • 9. Using Iterations in Python/2. For Loops.html 167 Bytes
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  • 1. Welcome! Course Introduction/2.2 Course Resources.html 134 Bytes
  • 10. Advanced Python tools/11.1 Working with arrays - Resources.html 134 Bytes
  • 10. Advanced Python tools/12.1 Generating Random Numbers - Resources.html 134 Bytes
  • 10. Advanced Python tools/16.1 Importing Data - Part I.html 134 Bytes
  • 10. Advanced Python tools/17.1 Importing and Organizing Data in Python – Resources.html 134 Bytes
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  • 10. Advanced Python tools/19.1 Importing and Organizing Data in Python – Resources.html 134 Bytes
  • 10. Advanced Python tools/20.1 Changing the Index of Your Time-Series - Resources.html 134 Bytes
  • 10. Advanced Python tools/21.1 Restarting the Jupyter Kernel - Resources.html 134 Bytes
  • 10. Advanced Python tools/7.1 Importing Modules - Resources.html 134 Bytes
  • 10. Advanced Python tools/9.1 Must have packages for Finance and Data Science.html 134 Bytes
  • 11/11.1 Calculating the Return of a Portfolio of Securities - Resources.html 134 Bytes
  • 11/14.3 Calculating the Return of Indices - Resources.html 134 Bytes
  • 11/6.1 Simple Returns - Part I - Resources.html 134 Bytes
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  • 11/8.1 Logarithmic Returns - Resources.html 134 Bytes
  • 12. PART II Finance Measuring Investment Risk/10.1 Calculating Covariance and Correlation - Resources.html 134 Bytes
  • 12. PART II Finance Measuring Investment Risk/12.1 Calculating Portfolio Risk - Resources.html 134 Bytes
  • 12. PART II Finance Measuring Investment Risk/15.1 Diversifiable and Non-Diversifiable Risk - Resources.html 134 Bytes
  • 12. PART II Finance Measuring Investment Risk/3.1 Calculating the Risk of a Security - Resources.html 134 Bytes
  • 13/3.1 Running a Regression in Python - Resources.html 134 Bytes
  • 13/6.1 Computing Alpha, Beta, and R Squared in Python - Resources.html 134 Bytes
  • 14. PART II Finance - Markowitz Portfolio Optimization/3.1 Obtaining the Efficient Frontier in Python - Part I - Resources.html 134 Bytes
  • 14. PART II Finance - Markowitz Portfolio Optimization/4.2 Obtaining the Efficient Frontier in Python - Part II - Resources.html 134 Bytes
  • 14. PART II Finance - Markowitz Portfolio Optimization/5.1 Obtaining the Efficient Frontier in Python - Part III - Resources.html 134 Bytes
  • 15/11.1 Estimating the Sharpe Ratio in Python - Resources.html 134 Bytes
  • 15/5.2 Calculating the Beta of a Stock - Resources.html 134 Bytes
  • 15/8.2 Calculating the Expected Return of a Stock (CAPM) - Resources.html 134 Bytes
  • 16/3.1 Running a Multivariate Regression in Python - Resources.html 134 Bytes
  • 17/1.1 The Essence of Monte Carlo Simulations - Resources.html 134 Bytes
  • 17/10.1 Predicting Stock Prices - Part II - Resources.html 134 Bytes
  • 17/11.1 Predicting Stock Prices - Part III - Resources.html 134 Bytes
  • 17/15.1 Monte Carlo Black-Scholes-Merton Resources.html 134 Bytes
  • 17/17.1 Monte Carlo - Euler Discretization - Part I - Resources.html 134 Bytes
  • 17/18.1 Monte Carlo - Euler Discretization - Part II - Resources.html 134 Bytes
  • 17/5.1 Monte Carlo - Predicting Gross Profit - Part I - Resources.html 134 Bytes
  • 17/6.1 Monte Carlo - Predicting Gross Profit - Part II - Resources.html 134 Bytes
  • 17/9.1 Monte Carlo - Predicting Stock Prices - Part I - Resources.html 134 Bytes
  • 3. Python Variables and Data Types/1.1 Variables - Resources.html 134 Bytes
  • 3. Python Variables and Data Types/3.1 Numbers and Boolean Values - Resources.html 134 Bytes
  • 3. Python Variables and Data Types/5.1 Strings - Resources.html 134 Bytes
  • 4. Basic Python Syntax/1.1 Arithmetic Operators - Resources.html 134 Bytes
  • 4. Basic Python Syntax/10.1 Indexing Elements - Resources.html 134 Bytes
  • 4. Basic Python Syntax/12.1 Structure Your Code with Indentation - Resources.html 134 Bytes
  • 4. Basic Python Syntax/3.1 The Double Equality Sign - Resources.html 134 Bytes
  • 4. Basic Python Syntax/5.1 Reassign Values - Resources.html 134 Bytes
  • 4. Basic Python Syntax/7.1 Add Comments - Resources.html 134 Bytes
  • 4. Basic Python Syntax/9.1 Line Continuation - Resources.html 134 Bytes
  • 5. Python Operators Continued/1.1 Comparison Operators - Resources.html 134 Bytes
  • 5. Python Operators Continued/3.1 Logical and Identity Operators - Resources.html 134 Bytes
  • 6. Conditional Statements/1.1 Introduction to the If Statement - Resources.html 134 Bytes
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  • 6. Conditional Statements/4.1 Else if, for Brief - Elif - Resources.html 134 Bytes
  • 6. Conditional Statements/5.1 A Note on Boolean Values - Resources.html 134 Bytes
  • 7. Python Functions/1.1 Defining a Function in Python - Resources.html 134 Bytes
  • 7. Python Functions/2.1 Creating a Function with a Parameter - Resources.html 134 Bytes
  • 7. Python Functions/3.1 Another Way to Define a Function - Resources.html 134 Bytes
  • 7. Python Functions/5.1 Using a Function in Another Function - Resources.html 134 Bytes
  • 7. Python Functions/6.1 Combining Conditional Statements and Functions - Resources.html 134 Bytes
  • 7. Python Functions/7.1 Creating Functions Containing a Few Arguments - Resources.html 134 Bytes
  • 7. Python Functions/8.1 Notable Built-In Functions in Python - Resources.html 134 Bytes
  • 8. Python Sequences/1.1 Lists - Resources.html 134 Bytes
  • 8. Python Sequences/3.1 Using Methods - Resources.html 134 Bytes
  • 8. Python Sequences/5.1 List Slicing - Resources.html 134 Bytes
  • 8. Python Sequences/6.1 Tuples - Resources.html 134 Bytes
  • 8. Python Sequences/7.1 Dictionaries - Resources.html 134 Bytes
  • 9. Using Iterations in Python/1.1 For Loops - Resources.html 134 Bytes
  • 9. Using Iterations in Python/3.1 While Loops and Incrementing - Resources.html 134 Bytes
  • 9. Using Iterations in Python/4.1 Create Lists with the range() Function - Resources.html 134 Bytes
  • 9. Using Iterations in Python/6.1 Use Conditional Statements and Loops Together - Resources.html 134 Bytes
  • 9. Using Iterations in Python/7.1 All In - Conditional Statements, Functions, and Loops - Resources.html 134 Bytes
  • 9. Using Iterations in Python/8.1 Iterating over Dictionaries - Resources.html 134 Bytes
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