Discounting Cash Flows Developer’s Guide

This is the official guide for anyone interested in creating or editing valuation models within the Model Code Editor on discountingcashflows.com.

Note

The website is under active development. If you encounter outdated content or have any questions, please let us know here.

Discounting Cash Flows (discountingcashflows.com) is dedicated to fundamental stock analysis and valuation. We automate the process of retrieving financial data from various sources (such as SEC.gov, Yahoo Finance, etc.) and importing this data into financial valuation models, enabling investors to focus more on analyzing companies’ fundamentals.

Our financial data is provided by financialmodelingprep.com. We use fully transparent and editable models written in JavaScript, processed directly in the user’s web browser (Chrome, Firefox, Opera, etc.), to calculate the intrinsic value of companies.

Advantages

• Interactive valuation models

  Users can adjust model assumptions with their own future estimations for companies. Changing these values automatically recalculates the models.

• Shareable valuation models

  Once users finalize their assumptions, they can easily copy and share the model’s URL with others.

• Editable valuation models

  Users can fully customize the models using our built-in JavaScript code editor.

• Price watches and alerts

  Users can set up price alerts and receive notifications via email when their valuation models reach specific thresholds.

Warning

Our website does not replace the Due Diligence required before making investment decisions, nor do we offer financial advice. We strongly recommend users thoroughly research each company, understand its business model, and develop their own projections before investing.

Model Code Editor

This guide explains every function available within the Model Code Editor. Additionally, you can access the source code and detailed explanations for all valuation models, including how they are calculated, on our GitHub documentation page.

Contents

Contents:

• Introduction
  • Good to know
• Reported Data Map
  • Preview of the Reported Data Map
• The data object
  • data.compute()
  • Key Types
  • Forecasting Values
  • Available Functions in data.compute()
  • Available Operations in data.compute()
  • data.set()
  • data.get()
  • data.min()
  • data.max()
  • data.average()
  • data.sum()
  • data.count()
• The assumptions object
  • assumptions.init()
  • assumptions.get()
  • assumptions.set()
  • assumptions.set_description()
• The model object
  • model.render_results()
  • model.render_chart()
  • model.render_table()
  • model.set_final_value()
  • model.render_description()