# Geocoding & Proximity Analysis with PostGIS

In the previous post I demonstrated how to web scrape data from a website with the intention of using the data as part of a geographic information system (GIS) data analysis pipeline. The data that we scraped are the addresses of all CVS pharmacies in the US. Now that we have the data we need … Continue reading Geocoding & Proximity Analysis with PostGIS

# Talk on Real Options using LSM

Today I presented on the topic of real options analysis using an approximate dynamic programming technique called the Least Squares Monte Carlo algorithm. The method was applied to real estate development. The model can be downloaded here (Update the talk is on YouTube here): Real Options Talk FinalDownload The default inputs and parameters of the … Continue reading Talk on Real Options using LSM

# Real Estate Real Options Analysis

Introduction One of the questions that arises in analyzing real estate development projects is how to phase the project to minimize the project's risks over construction periods that can last months if not years. Properly phasing, that is subdividing a project into separate self-contained stages, is an effective risk strategy as it allows the developer … Continue reading Real Estate Real Options Analysis

# Modeling Construction Cost Uncertainty

Introduction In previous posts I have demonstrated how to use Monte Carlo simulation to handle absorption risk, vacancy and occupancy dynamics, and sale price (or rental rate) risks for real estate developments and investments. In addition to those risks, real estate construction projects are notorious for being over budget and behind schedule. Therefore in this … Continue reading Modeling Construction Cost Uncertainty

# Modeling Real Estate Price/Rent Uncertainty

Introduction Real estate prices, whether they are housing prices, land prices, rental rates, or construction costs, evolve continuously through time. Traditionally real estate analysts have not directly modeled this dynamic process of price evolution. Instead they have relied on simple heuristics to handle future uncertainty, such as assuming a constant growth rate for the variable … Continue reading Modeling Real Estate Price/Rent Uncertainty

# The Real Estate Joint Venture Waterfall

Introduction   The Joint Venture distribution structure, aka the Waterfall, determines the allocation of profits among the equity investors and managers in a real estate project or transaction.  Typically as a project achieves different return requirements, called hurdles, this allocation of profits between the parties changes.  For this reason the Waterfall is often considered the most complex … Continue reading The Real Estate Joint Venture Waterfall

# Adding Rent to the Vacancy Model

Introduction The previous post reviewed two of the fundamental problems with the typical approach to modeling future real estate leases, namely a failure to address the uncertainties and nonlinearities embedded in the analysis. The proposed solution for these issues is to use simulation based methods.  The example model presented in the last post simulated the … Continue reading Adding Rent to the Vacancy Model

# Modeling Vacancy – A Monte Carlo Approach

Introduction This post is part of a series of posts that will demonstrate the benefits of adopting simulation as the mode of analysis for real estate investment valuation.  The focus of this post is how to conduct a lease analysis without relying on simplistic averages and blended rates that fail to properly account for uncertainty … Continue reading Modeling Vacancy – A Monte Carlo Approach

# Multifamily Lease-Up Module

(Note: This post uses Analytica by Lumina Decision Systems.  The free version is here.  Also here is a nice and easy introduction to the language.  You can download the model presented here at 2017-5-25 Lease Up Model ) Introduction This post will present one method for handling the absorption phase risk for a real estate development. … Continue reading Multifamily Lease-Up Module