autodcf 0.1.0

Getting Started

You can clone the repo from GitHub using

git clone https://github.com/jackmoody11/autodcf

Setup the project by navigating to the project root directory and running

python setup.py

Basic Usage

There are a few important classes which will help you build your DCF. The Company class encapsulates three classes: BalanceSheet, CashFlows, and IncomeStatement. Once a Company object is created using the 3 financial statements, this can be passed to one of the DCF models (currently either SimpleDCF or DCF).

from autodcf.company import BalanceSheet, CashFlows, Company, IncomeStatement
from autodcf.models import SimpleDCF

balance_sheet = BalanceSheet(assets=100, liabilities=50)
cash_flows = CashFlows(capex=3)
income_statement = IncomeStatement(sales=100,
                                   cogs=50,
                                   sga=25,
                                   rd=0,
                                   depreciation=4,
                                   amortization=2,
                                   interest=0,
                                   nonrecurring_cost=3,
                                   tax=4)
company = Company(balance_sheet=balance_sheet,
                  cash_flows=cash_flows,
                  income_statement=income_statement,
                  price_per_share=2.00,
                  fully_diluted_shares=100)
simple_dcf = SimpleDCF(change_in_nwc_to_change_in_sales=0.1,
                       company=company,
                       discount_rate=0.14,
                       sales_growth=0.03,
                       tax_rate=0.21,
                       terminal_growth_rate=0.03,
                       window=5)
forecast = simple_dcf.forecast()

The code above will provide a filled out pandas DataFrame with estimated growth of different line items from the income statement.

TODO

• Add docs and deploy using doctr to GitHub Pages site (automate deployment with Travis CI)

• Publish package to PyPi

Future Enhancements

• io: Allow for DCF model to be exported to Excel

• data: Allow users to specify what company and data source to use and fetch necessary data for B/S, CF, and I/S behind the scenes

• company: Allow for integration with financial data APIs

• models: Add different types of models (with/without synergies)