Welcome to Nick DeRobertis’ Financial Modeling Course!¶
This is the website for Nick DeRobertis’ Financial Modeling courses. Currently there are two courses: Financial Modeling with Python and Excel and Advanced Financial Modeling with Python.
Financial Modeling with Python and Excel is targeted at students who want to learn financial modeling and have basic finance, accounting, and Excel knowledge, but no knowledge of Python.
Advanced Financial Modeling with Python is meant for those who are comfortable with financial modeling in Python but want to learn more advanced topics. Completion of the Financial Modeling with Python and Excel course would be good preparation for this course.
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- Financial Modeling with Python and Excel
- Getting Started with Python and Excel
- The Depth of a Financial Model
- Going Beyond an Initial Python Script
- The Depth of a Financial Model, Continued
- Understanding Complex Results
- Exploring the Parameter Space
- Resources
- Introduction to Parameter Exploration
- Introduction to Sensitivity Analysis
- Sensitivity Analysis in Excel
- Using Python Dictionaries
- Python List Comprehensions - Convenient List Building
- Python Imports and Installing Packages
- Introduction to Sensitivity Analysis in Python
- Sensitivity Analysis in Python Example
- Lab Exercise - Adding Sensitivity Analysis to Project 1 - Python
- Probabilistic Modeling
- Resources
- Introduction to Probabilistic Modeling
- Math Review for Probabilistic Modeling
- Introduction to Scenario Analysis
- Scenario Analysis in Excel
- Lab Exercise - Adding Scenario Analysis to Project 1 - Excel
- Scenario Analysis in Python
- Introduction to Internal Randomness
- Intro to Randomness in Excel
- Intro to Randomness in Python
- Lab Exercise - Generating Continuous Random Numbers in Excel and Python
- Discrete Randomness
- Adding Internal Randomness to an Excel Model
- Adding Internal Randomness to a Python Model
- Internal Randomness Lab Exercises Overview
- Combining Excel and Python
- Monte Carlo Simulation
- Resources
- Introduction to Monte Carlo Simulations
- Monte Carlo Investment Returns
- Monte Carlo Dividend Discount Model (DDM) Lab Exercise
- Formal Introduction to Monte Carlo Simulations
- Analyzing Relationships with Monte Carlo Simulations
- Applying Monte Carlo Simulation to a Python Model
- Applying Monte Carlo Simulation to an Excel Model
- Relationship of Inputs and Outputs in Excel Monte Carlo Simulation
- Introduction to DCF Valuation and Cost of Capital Estimation
- Resources
- Introduction to Discounted Cash Flow (DCF) Valuation
- Enterprise Value and Equity Value
- Introduction to Cost of Equity
- Cost of Equity in Python
- Cost of Equity in Excel
- Market Value of Equity
- Cost of Debt
- Introduction to Market Value of Debt
- Calculating the Market Value of Debt in Python
- Calculating the Weighted Average Cost of Capital (WACC)
- Free Cash Flow Estimation and Forecasting
- Resources
- Introduction to Free Cash Flows
- Introduction to Calculating Historical Free Cash Flows
- Historical Free Cash Flows in Python Using Pandas and finstmt
- Historical Free Cash Flows Lab Exercise Overview
- Introduction to Forecasting
- Simple Time-Series Forecasting Models
- Simple Time-Series Forecasting in Excel
- Simple Time-Series Forecasting in Python
- Simple Time-Series Forecasting Lab Overview
- Forecasting Simple Financial Statements in Python with finstmt
- Complex Time-Series Forecasting
- Complex Time-Series Forecasting in Python - Manual Method
- Complex Time-Series Forecasting in Python - finstmt Method
- Complex Time-Series Forecasting Lab Overview
- Applying Forecasting to Free Cash Flows
- Calculating a Terminal Value
- Q&A
- Projects
- Lab Exercise Solutions
- Extending a Simple Retirement Model
- Determining Desired Cash in the Dynamic Salary Retirement Excel Model
- Python Basics - Conditionals
- Python Basics - Lists
- Python Basics - Functions
- Python Basics - Data Types
- Python Basics - Classes
- Determining Desired Cash in the Dynamic Salary Retirement Python Model
- Getting Started with Pandas
- Styling Pandas DataFrames
- Introduction to Graphing with Pandas
- Adding Sensitivity Analysis to Project 1 - Excel
- Learning How to Use Dictionaries
- Learning How to Use List Comprehensions
- Adding Sensitivity Analysis to Project 1 - Python
- Adding Scenario Analysis to Project 1 - Excel
- Adding Scenario Analysis to Project 1 - Python
- Generating and Visualizing Random Numbers - Excel
- Generating and Visualizing Random Numbers - Python
- Building a Simple Model of Stock Returns
- Extending the Project 1 Model with Internal Randomness
- Reading and Writing to Excel with Pandas
- Reading and Writing to Excel with xlwings
- Monte Carlo Simulation of DDM
- Monte Carlo Simulation of Python Models
- Monte Carlo Simulation of Excel Models
- Finding Enterprise and Equity Value Given FCF and WACC
- Finding Cost of Equity Given Historical Prices
- Finding Cost of Debt Given Financial and Market Info
- Free Cash Flow Calculation
- Forecasting Simple Time-Series
- Forecasting Complex Time-Series
- DCF Stock Price using Terminal Values
- Advanced Financial Modeling
- Resources
- Introduction to Advanced Financial Modeling
- Additional Types of Financial Models
- Data Pipelines for Financial Modeling
- Advanced Mathematical Tools for Financial Modeling
- Better Presentation of Python Financial Models
- Programming Skills for Advanced Financial Models
- Extra Resources for Python Financial Modeling
- Data Pipelines