Financial Modelling with Python & Excel : DCF Valuation

Examine how free cash flow after debt splits into the value of equity, contrasting fcfe with the dividend discount model and its growth-driven dividends.

Compare fcfe and ddm valuations in excel by modeling growth, reinvestment, and dividends, then discount future cash flows to present value using cost of equity.

Learn how to set up inputs for FCFE and DDM calculations in Python, including net income, debt obligations, miscellaneous reinvestment rate, growth rate, cost of equity, and perpetual growth rate.

Learn to implement a Python discounted cash flow model by recreating autofill with temp, calc, and lists, applying growth and discounting to net income, debt obligations, miscellaneous cash, and dividends.

Learn to build a python-based FCFE valuation by calculating free cash flow, forming an FCF list, and discounting equity with the cost of equity and a terminal growth rate.

Explore fcfe and the dividend discount model in Python by discounting free cash flow to equity and dividends with cost of equity, calculating terminal value, and deriving equity value.

Explore how return on capital and reinvestment shape growth, using earnings, obligations, and working capital to calculate the reinvestment rate in spreadsheet and Python models.

Explore calculating return on invested capital (ROIC) and reinvestment rate in a spreadsheet and Python lab, using EBIT, tax, capex, depreciation, and working capital to derive growth.

Analyze five-year growth estimation by averaging reinvestment rate and ROIC, while using the last ROE value for conservatism; assess impacts on discount rate and intrinsic value in the Python lab.

Recreate the financial model from spreadsheet in Python, calculating return on capital and reinvestment using tax, EBIT, debt and equity, capex, depreciation, and working capital.

Explore two-stage dividend discount model, applying ROE and payout ratios to project eps and dps in growth and stable periods, determining equity value via terminal price and cost of equity.

Derive eps growth from roe and payout, set growth and stable cost of equity, compute stable payout ratio, and value via terminal price and dividends in excel.

Apply the dividend discount model in Python and Excel to compute cost of equity for growth and stable periods, derive EPS and payouts, and determine terminal and present values.

Explore the free cash flow to equity model by deriving fcfe from net income, capex, and depreciation using reinvestment rate and ROE to project growth and value large firms.

Model free cash flow to equity in excel by forecasting net income and reinvestment using growth rates, then discount with the cost of equity to derive intrinsic equity value.

Compute inputs and cost of equity, forecast net income and FCF, discount cash flows, and derive the equity value with a Python-based discounted cash flow model.

Explain the free cash flow to firm and equity models, including two-stage growth with varying weighted average cost of capital, operating income, capex, and debt, guiding intrinsic value.

Learn to build excel fcff valuation by deriving inputs from financial statements and choosing fcff or fcfe based on leverage, then compute ebit, reinvestment rate, and return on capital.

Compute free cash flow to the firm from EBIT, apply reinvestment and tax, forecast growth, and discount projected FCF at the weighted average cost of capital.

Calculate intrinsic value by building a DCF model in Excel, derive values and terminal value from net income, growth, tax, reinvestment rates, then discount cash flows at cost of capital.

Use Python to input FCFF assumptions, convert currency to crore INR for an India-based firm, and compute growth, cost of equity, cost of debt, and WACC to derive intrinsic value.

Build a fully functional FCFF model in Python to compute terminal value and intrinsic value within a DCF framework, using tax rate, reinvestment rate, and cost of capital.

Calculate the cost of equity via the beta approach by deriving unlevered beta from industry data and converting to a levered total beta, using the risk-free rate and risk premium.

learn how to estimate cost of equity using two methods—the equal exposure and beta scaled approaches—by deriving levered beta from unlevered beta, debt-to-equity, taxes, and country and historical risk premiums.

Calculate the cost of equity using unlevered and levered beta with inputs like debt-to-equity, tax rate, risk-free rate, and risk premiums; compare equal exposure and beta-scaled approaches.

Explore valuing Sun TV, a Sun Group media firm in India, via dcf valuation using 2021 data, with corporate, ownership details, and sources like Wikipedia and stock prices.

Analyze the balance sheet to determine leverage and select the free cash flow to equity (fcfe) method for intrinsic valuation.

Analyze the profit and loss statement by examining revenue from operations, expenses balance across expenses, employee benefits, and depreciation. Understand how after-tax profit flows into cash flow for financial modeling.

Analyze the cash flow statement by examining operating, investing, and financing activities, linking profit before tax, working capital, capital expenditure, depreciation, and reinvestment rate to cash flow and growth.

Extract total income, EBIT, and equity capital from financial statements; input reinvested cash, dividend income, and expenditures to forecast five years, compute reinvestment and growth rates, then intrinsic value.

Learn to input capex, change in working capital, and reinvested cash in valuation models, using capex 454 crore INR, change in working capital 202 crore INR, and 25% tax rate.

Forecast free cash flows by calculating EBIT after tax, subtracting capital expenditure and delta working capital, estimating reinvestment, and forecasting growth to derive robust intrinsic value.

Compute the discount rate from cost of capital or cost of equity, discount forecast free cash flows, and derive the firm’s present value and intrinsic value.

Learn how basic free cash flow and dividend inputs affect equity value, intrinsic value, compare with price-to-book, and identify pitfalls in forecasting and financial statement reading.

Unpack the five fundamental elements of a program—syntax, semantics, a command or statement, objects and expressions, and variables—through Python basics with literals, operators, and simple examples like area and print.

Discover the elements of Python programming, including syntax, commands, and print statements. Practice with variables and expressions, compute area with pi r squared, string handling, and understand syntax errors.

Explore branching programs and conditionals, mastering if-else logic, nested conditions, and indentation in Python-style pseudocode, with examples for even/odd checks using modulo.

Master branching programs and conditional logic through practical examples of nested if statements, modulo operations, and divisibility by two and three.

Explore core string concepts in Python, including indexing, slicing, length, and concatenation, and practice input handling and type errors, with emphasis on string operations and Python 3 input.

Explore string operations and input handling in Python through hands-on lab exercises, including string multiplication, concatenation, indexing, slicing, length checks, and type checking.

Master iterations and loops, using while, do while, and for loops driven by tests; learn how initial, final values and increments control execution, with examples like squaring integers.

Explore iteration fundamentals through a hands-on lab, using while loops to perform repeated addition, simulate multiplication, and print results while comparing loop types like for and do-while.

Explore exhaustive enumeration and the decrement function within loops, using a program that tests if a number is a perfect cube by incremental cube root checks and handling negatives.

Explore exhaustive enumeration and for loops to determine if a number is a perfect cube, comparing while loop and for loop approaches, with practical cube root calculations.

Explore how functions are defined and executed, including formal and actual parameters, returns, and indentation. Understand scoping and how variables bind within and outside a function, with examples.

Explore defining functions, formal and actual parameters, and function scope. Learn to implement max, min, and square as examples, and distinguish inside versus outside the function scope.

Explore recursion, where a function calls itself within its body, forming a parent function with implications for factorial, Fibonacci, and numerical series in finance.

Explore recursion by implementing factorial both iteratively and recursively, including base case, return statements, and self-referential calls, demonstrated with four yielding 24.

Learn recursion theory through factorial and Fibonacci examples, comparing iterative and recursive implementations. Explore defining recursive functions like fact and fib, with base cases and recursive calls.

Define a fibonacci function and use recursion to compute numbers as the sum of the two previous values, with Python demonstrations and base-case notes.

Master tuples and lists as Python data types. Declare tuples with parentheses, mix data types, and create empty tuples; declare lists with square brackets, index from zero, and print lists.

Explore tuples and lists in Python, learn their declaration, basic manipulations, and printing, including empty tuples and lists. Compare mutability and memory implications while practicing with loops and indexing.

Master mutability in lists by distinguishing value versus object identity, and note that combining by names differs from combining by actual content; a Python variable is just a name.

Demonstrate mutability in lists and tuples by distinguishing value equality from object identity with id(), and explain that variables are just names.

Demonstrate cloning to avoid mutating lists during iteration and use list comprehension to remove duplicates and generate squares, including handling mixed types with integer filtering.

Explore how functions act as objects by treating a function as a data type within another function, and replace each list element with the function's output, converting to integers.

Explore treating functions as objects in Python, using apply-to-each to mutate lists and apply built-in functions like abs and int, with factorial and Fibonacci examples.

This lecture covers testing and debugging theory, distinguishes overt and covert bugs, explains intermittent and persistent errors, and promotes learning by analyzing intermediate outputs with print statements.

Learn practical testing and debugging techniques for python code, including identifying bugs in palindrome checks, using copied inputs, step-by-step tracing, and targeted prints to validate functions.

Explore object oriented programming concepts in Python, including classes, methods, instantiation, and objects, then examine inheritance and recursion to see how classes and objects interact.

Learn object oriented programming in python by building an int set class with methods for insert, remove, and member, exploring instance creation, exception handling, and inheritance.

Build a capstone loan payment calculator in python, comparing two payment types with credit-point adjustments using the monthly formula, and implement functions to define, process, and compare payments.

Apply Python to compare fixed-rate loans with and without points, using a mortgage class and payments calculation to reveal total payments and impact of credit points.

Discover the final course highlights and key takeaways from mastering financial modelling with Python and Excel for DCF valuation.