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

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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

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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

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05 - Python Operators Continued

001 Comparison Operators

002 Logical and Identity Operators

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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

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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

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08 - Python Sequences

001 Lists

002 Using Methods

003 List Slicing

004 Tuples

005 Dictionaries

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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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