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THE HIDDEN COSTS OF HOMEOWNERSHIP
| March 12, 2015
LNR is a commercial real estate company and one of the first companies to enter the CMBS industry in the early 1990's. LNR has created one of the nation's leading and most respected franchises in the CMBS market.
Article | March 8, 2020
Financial modeling is a technical application as old as finance itself. Traditionally performed through excel sheets and various DCF models, I wanted to set out and use Machine Learning to build a predictive model for the movement of an asset’s price. Within a two week project time period, I set out to analyze and build predictive SARIMAX (Seasonal Auto-Regressive Integrated Moving Average with Exogeneity) models to capture the movement of eight different Real Estate Investment Trusts (REITs). Before we get into the data, it is essential to first understand the nature of a REIT. REITs are just like any other financial asset in that ownership represents a “share” of a companies profit. These companies own and operate income-producing real estate and are usually centric to a particular sector of real estate type (data centers, retail properties, Senior/Assisted living communities, healthcare, etc…). There are two main types of REITS:
Article | March 4, 2020
Since we know machine learning is driving innovation across every industry, real estate included, I took the time to summarize my experience as an attendee of ICNY by highlighting key findings in this blog post. These insights are based on my personal interpretation of the sessions, booth visits, and conversations with industry players (real estate agents, proptech workers, investors, and other conference participants). It’s no longer news that the real estate industry experienced a major revolution over the last few years with the involvement of iBuyers. In short, iBuyers digitize as many housing transactions as possible. Players like Zillow, Opendoor and Redfin offer buyers, sellers, and renters the option to find an agent or search, distribute, finance, and even close a transaction online.
Article | March 26, 2020
As most of us have adjusted to the new reality brought on by the coronavirus (COVID-19), developers and lenders are forced to look at the resulting economic shut down on ongoing real estate projects. When this virus first started making the news late last year, few people anticipated that it would turn into a global pandemic that would virtually shut down world economic markets. In the real estate world, when this did happen, it was easy to predict that the deals that had not yet been signed, would come to a stop and/or be terminated, and that deals that had been signed would be paused and extended. But what about deals in progress and under construction? Supply chains have not only been disrupted, but in many cases, have been stopped altogether. This could cause many borrowers to miss important benchmarks under construction loan agreements. It could also cause developers to miss delivery dates under leases and contracts. Will lenders declare loan defaults for missed benchmarks? Will tenants and buyers?
Article | February 17, 2020
The use of big data has permeated a wide range of sectors. In fact, professionals from every field rely on it to improve the accuracy and effectiveness of their analysis. As you would expect, big data had the same impact on the real estate industry as well. Over the past decade, big data has come to occupy a central place in real estate analysis and every savvy real estate investor relies on it to provide an accurate overview of the housing market. So what exactly are the benefits of big data for residential real estate? And how to use big data for real estate analysis?
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