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خانه » فروشگاه » Python for Finance: Investment Fundamentals & Data Analytics

Python for Finance: Investment Fundamentals & Data Analytics

سرفصل های دوره

Learn Python Programming and Conduct Real-World Financial Analysis in Python - Complete Python Training


01 - Welcome! Course Introduction
  • 001 What Does the Course Cover
  • 002 Download Useful Resources - Exercises and Solutions
  • 002 Python-for-Finance-FAQ.pdf
  • external-links.txt

    • 02 - Introduction to programming with Python
  • 001 Programming Explained in 5 Minutes
  • 001 Python-for-Finance-Course-Notes-Part-I.pdf
  • 002 Why Python
  • 003 Why Jupyter
  • 004 Installing Python and Jupyter
  • 005 Jupyters Interface the Dashboard
  • 006 Jupyters Interface Prerequisites for Coding
  • 006 Jupyter-Shortcuts.pdf
  • 007 Python 2 vs Python 3 Whats the Difference
  • 007 Python-for-Finance-Course-Notes-Part-I.pdf

    • 03 - Python Variables and Data Types
  • 001 Variables
  • 002 Numbers and Boolean Values
  • 003 Strings
  • external-links.txt

    • 04 - Basic Python Syntax
  • 001 Arithmetic Operators
  • 002 The Double Equality Sign
  • 003 Reassign Values
  • 004 Add Comments
  • 005 Line Continuation
  • 006 Indexing Elements
  • 007 Structure Your Code with Indentation
  • external-links.txt

    • 05 - Python Operators Continued
  • 001 Comparison Operators
  • 002 Logical and Identity Operators
  • external-links.txt

    • 06 - Conditional Statements
  • 001 Introduction to the IF statement
  • 002 Add an ELSE statement
  • 003 Else if, for Brief ELIF
  • 004 A Note on Boolean Values
  • external-links.txt

    • 07 - Python Functions
  • 001 Defining a Function in Python
  • 002 Creating a Function with a Parameter
  • 003 Another Way to Define a Function
  • 004 Using a Function in another Function
  • 005 Combining Conditional Statements and Functions
  • 006 Creating Functions Containing a Few Arguments
  • 007 Notable Built-in Functions in Python
  • external-links.txt

    • 08 - Python Sequences
  • 001 Lists
  • 002 Using Methods
  • 003 List Slicing
  • 004 Tuples
  • 005 Dictionaries
  • external-links.txt

    • 09 - Using Iterations in Python
  • 001 For Loops
  • 002 While Loops and Incrementing
  • 003 Create Lists with the range() Function
  • 004 Use Conditional Statements and Loops Together
  • 005 All In Conditional Statements, Functions, and Loops
  • 006 Iterating over Dictionaries
  • external-links.txt

    • 10 - Advanced Python tools
  • 001 Object Oriented Programming
  • 002 Modules and Packages
  • 003 The Standard Library
  • 004 Importing Modules
  • 005 47-Packages-Exercise.pdf
  • 005 Must-have packages for Finance and Data Science
  • 006 Working with arrays
  • 007 Generating Random Numbers
  • 008 A Note on Using Financial Data in Python
  • 009 Sources of Financial Data
  • 010 Accessing the Notebook Files
  • 011 Importing and Organizing Data in Python part I
  • 012 Importing and Organizing Data in Python part II.A
  • 013 Importing and Organizing Data in Python part II.B
  • 014 Importing and Organizing Data in Python part III
  • 015 Changing the Index of Your Time-Series Data
  • 016 Restarting the Jupyter Kernel
  • external-links.txt

    • 11 - PART II FINANCE Calculating and Comparing Rates of Return in Python
  • 001 Considering both risk and return
  • 001 Python-for-Finance-Course-Notes-Part-II.pdf
  • 002 Python-for-Finance-Course-Notes-Part-II.pdf
  • 002 What are we going to see next
  • 003 Calculating a securitys rate of return
  • 003 Python-for-Finance-Course-Notes-Part-II.pdf
  • 004 Calculating a Securitys Rate of Return in Python - Simple Returns - Part I
  • 005 Calculating a Securitys Rate of Return in Python - Simple Returns - Part II
  • 006 Calculating a Securitys Return in Python - Logarithmic Returns
  • 007 Python-for-Finance-Course-Notes-Part-II.pdf
  • 007 What is a portfolio of securities and how to calculate its rate of return
  • 008 Calculating a Portfolio of Securities Rate of Return
  • 009 Popular stock indices that can help us understand financial markets
  • 009 Python-for-Finance-Course-Notes-Part-II.pdf
  • 010 Calculating the Indices Rate of Return
  • 010 Indices-Data-1.csv
  • 010 Indices-Data-2.csv
  • external-links.txt

    • 12 - PART II Finance Measuring Investment Risk
  • 001 How do we measure a securitys risk
  • 001 Python-for-Finance-Course-Notes-Part-II.pdf
  • 002 Calculating a Securitys Risk in Python
  • 003 Python-for-Finance-Course-Notes-Part-II.pdf
  • 003 The benefits of portfolio diversification
  • 004 Calculating the covariance between securities
  • 004 Python-for-Finance-Course-Notes-Part-II.pdf
  • 005 Measuring the correlation between stocks
  • 005 Python-for-Finance-Course-Notes-Part-II.pdf
  • 006 Calculating Covariance and Correlation
  • 007 Considering the risk of multiple securities in a portfolio
  • 007 Python-for-Finance-Course-Notes-Part-II.pdf
  • 008 Calculating Portfolio Risk
  • 009 Python-for-Finance-Course-Notes-Part-II.pdf
  • 009 Understanding Systematic vs. Idiosyncratic risk
  • 010 Calculating Diversifiable and Non-Diversifiable Risk of a Portfolio
  • external-links.txt

    • 13 - PART II Finance - Using Regressions for Financial Analysis
  • 001 Housing-Data.xlsx
  • 001 Python-for-Finance-Course-Notes-Part-II.pdf
  • 001 The fundamentals of simple regression analysis
  • 002 Housing.xlsx
  • 002 Running a Regression in Python
  • 003 Are all regressions created equal Learning how to distinguish good regressions
  • 003 Python-for-Finance-Course-Notes-Part-II.pdf
  • 004 Computing Alpha, Beta, and R Squared in Python
  • 004 Housing.xlsx
  • external-links.txt

    • 14 - PART II Finance - Markowitz Portfolio Optimization
  • 001 14.Markowitz-Efficient-frontier.xlsx
  • 001 Markowitz Portfolio Theory - One of the main pillars of modern Finance
  • 001 Python-for-Finance-Course-Notes-Part-II.pdf
  • 002 Markowitz-Data.csv
  • 002 Obtaining the Efficient Frontier in Python Part I
  • 003 Markowitz-Data.csv
  • 003 Obtaining the Efficient Frontier in Python Part II
  • 004 Markowitz-Data.csv
  • 004 Obtaining the Efficient Frontier in Python Part III
  • external-links.txt

    • 15 - Part II Finance - The Capital Asset Pricing Model
  • 001 Python-for-Finance-Course-Notes-Part-II.pdf
  • 001 The intuition behind the Capital Asset Pricing Model (CAPM)
  • 002 Python-for-Finance-Course-Notes-Part-II.pdf
  • 002 Understanding and calculating a securitys Beta
  • 003 CAPM-Data.csv
  • 003 Calculating the Beta of a Stock
  • 004 Python-for-Finance-Course-Notes-Part-II.pdf
  • 004 The CAPM formula
  • 005 CAPM-Data.csv
  • 005 Calculating the Expected Return of a Stock (CAPM)
  • 006 Introducing the Sharpe ratio and how to put it into practice
  • 006 Python-for-Finance-Course-Notes-Part-II.pdf
  • 007 CAPM-Data.csv
  • 007 Obtaining the Sharpe ratio in Python
  • 008 Measuring alpha and verifying how good (or bad) a portfolio manager is doing
  • 008 Python-for-Finance-Course-Notes-Part-II.pdf
  • external-links.txt

    • 16 - Part II Finance Multivariate regression analysis
  • 001 Multivariate regression analysis - a valuable tool for finance practitioners
  • 001 Python-for-Finance-Course-Notes-Part-II.pdf
  • 002 Housing.xlsx
  • 002 Running a multivariate regression in Python
  • external-links.txt

    • 17 - PART II Finance - Monte Carlo simulations as a decision-making tool
  • 001 Python-for-Finance-Course-Notes-Part-II.pdf
  • 001 The essence of Monte Carlo simulations
  • 002 Monte Carlo applied in a Corporate Finance context
  • 002 Python-for-Finance-Course-Notes-Part-II.pdf
  • 003 Monte Carlo Predicting Gross Profit Part I
  • 004 Monte Carlo Predicting Gross Profit Part II
  • 005 Forecasting Stock Prices with a Monte Carlo Simulation
  • 006 Monte Carlo Forecasting Stock Prices - Part I
  • 007 Monte Carlo Forecasting Stock Prices - Part II
  • 008 Monte Carlo Forecasting Stock Prices - Part III
  • 009 An Introduction to Derivative Contracts
  • 009 Python-for-Finance-Course-Notes-Part-II.pdf
  • 010 Python-for-Finance-Course-Notes-Part-II.pdf
  • 010 The Black Scholes Formula for Option Pricing
  • 011 Monte Carlo Black-Scholes-Merton
  • 012 Monte Carlo Euler Discretization - Part I
  • 013 Monte Carlo Euler Discretization - Part II
  • external-links.txt

    • 18 - APPENDIX - pandas Fundamentals
  • 001 pandas Series - Introduction
  • 001 pandas-dataframes-introduction-exercise.zip
  • 001 pandas-dataframes-introduction-lecture.zip
  • 001 pandas-dataframes-introduction-solution.zip
  • 002 pandas - Working with Methods - Part I
  • 002 pandas-working-with-methods-part-i-lecture.zip
  • 003 pandas - Working with Methods - Part II
  • 003 pandas-working-with-methods-exercise.zip
  • 003 pandas-working-with-methods-part-ii-lecture.zip
  • 003 pandas-working-with-methods-solution.zip
  • 004 pandas - Using Parameters and Arguments
  • 004 using-parameters-and-arguments-exercise.zip
  • 004 using-parameters-and-arguments-lecture.zip
  • 004 using-parameters-and-arguments-solution.zip
  • 005 Location.csv
  • 005 Region.csv
  • 005 pandas Series - .unique() and .nunique()
  • 005 pandas-series.unique-and.nunique-exercise.zip
  • 005 pandas-series.unique-and.nunique-lecture.zip
  • 005 pandas-series.unique-and.nunique-solution.zip
  • 006 Location.csv
  • 006 Region.csv
  • 006 pandas Series - .sort values()
  • 006 pandas-series.sort-values-exercise.zip
  • 006 pandas-series.sort-values-lecture.zip
  • 006 pandas-series.sort-values-solution.zip
  • 007 pandas DataFrames - Introduction - Part I
  • 008 Lending-company.csv
  • 008 Sales-products.csv
  • 008 pandas DataFrames - Introduction - Part II
  • 008 pandas-series-introduction-exercise.zip
  • 008 pandas-series-introduction-lecture.zip
  • 008 pandas-series-introduction-solution.zip
  • 009 Lending-company.csv
  • 009 Sales-products.csv
  • 009 pandas DataFrames - Common Attributes
  • 009 pandas-dataframes-common-attributes-exercise.zip
  • 009 pandas-dataframes-common-attributes-lecture.zip
  • 009 pandas-dataframes-common-attributes-solution.zip
  • 010 Lending-company.csv
  • 010 Sales-products.csv
  • 010 pandas DataFrames - Data Selection
  • 010 pandas-dataframes-data-selection-exercise.zip
  • 010 pandas-dataframes-data-selection-lecture.zip
  • 010 pandas-dataframes-data-selection-solution.zip
  • 011 Lending-company.csv
  • 011 Sales-products.csv
  • 011 pandas DataFrames - Data Selection with .iloc[]
  • 011 pandas-dataframes-data-selection.iloc-exercise.zip
  • 011 pandas-dataframes-data-selection.iloc-lecture.zip
  • 011 pandas-dataframes-data-selection.iloc-solution.zip
  • 012 Lending-company.csv
  • 012 Sales-products.csv
  • 012 pandas DataFrames - Data Selection with .loc[]
  • 012 pandas-dataframes-data-selection.loc-exercise.zip
  • 012 pandas-dataframes-data-selection.loc-lecture.zip
  • 012 pandas-dataframes-data-selection.loc-solution.zip

    • 19 - APPENDIX - Technical Analysis
  • 001 Technical Analysis - Principles, Applications, Assumptions
  • 002 Charts Used in Technical Analysis
  • 003 Other Tools Used in Technical Analysis
  • 004 Trend, Support and Resistance Lines
  • 005 Common Chart Patterns
  • 006 Price Indicators
  • 007 Momentum Oscillators
  • 008 Non-price Based Indicators
  • 009 Technical Analysis - Cycles
  • 010 Intermarket Analysis

    • 20 - BONUS LECTURE
  • 001 Bonus Lecture Next Steps.html
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