Rangekeeper#
Rangekeeper is an open-source python-based code library for financial modelling in real estate asset & development planning, decision-making, cashflow forecasting, and scenario analysis.
Rangekeeper enables real estate valuation at all stages and resolutions of description — from early-stage ‘back-of-the-envelope’ models to detailed commercial assessments, and can be completely synchronised with 3D design, engineering, and logistics modelling.
It decomposes elements of the Discounted Cash Flow (DCF) Proforma modelling approach into recomposable code functions that can be wired together to form a full model.
Development of the library follows the rigorous methodology established by MIT Professors David Geltner and Richard de Neufville, in their book Flexibility and Real Estate Valuation under Uncertainty: A Practical Guide for Developers , and expands it into a more robust computational framework.
This walkthrough is intended to provide a brief introduction to the library, as well as examples of its use in practice. There are two sections to the walkthrough:
Real Estate Flexibility and Valuation under Uncertainty: a series of notebooks providing a walkthrough of the library in parallel with chapters of the book.
Using Rangekeeper in Examples: notebooks that showcase some of the library’s functionality in practice
This walkthrough is intended for use by practitioners who are both familiar with the book’s content, and well-versed in data-science-oriented programming.
For those interested, notebooks can be run interactively via Google Colab, by clicking the icon at the top of each notebook.
Note
Note: installation of the library via !pip install rangekeeper
is required
for use in Google Colab.
Table of Contents#
Acknowledgements#
For Andrea, who keeps reminding me it is possible.
Bibliography#
R. de Neufville and D. Geltner. Flexibility and Real Estate Valuation under Uncertainty: A Practical Guide for Developers. John Wiley & Sons, Ltd, 2018. ISBN 9781119106470. URL: https://onlinelibrary.wiley.com/doi/abs/10.1002/9781119106470, arXiv:https://onlinelibrary.wiley.com/doi/pdf/10.1002/9781119106470, doi:https://doi.org/10.1002/9781119106470.