Radar Logic Incorporated and my appraisal and consulting firm Miller Samuel Inc. have entered into a joint venture named Radar Logic Research, LLC.
Radar Logic Research Press Release [pdf]
Radar Logic White Paper Here’s more technical information.
Radar Logic Incorporated, through its partner Ventana Systems, Inc. a mathematics consulting and software firm, have leveraged methodologies commonly used in the sciences, and applied it to real estate. The objective was to make sense of the national residential housing market by creating a daily housing “spot” price to be used in the trading of real estate derivatives.
The Radar Logic Daily Index is a single, statistically accurate value representing the price per square foot paid in a defined metropolitan area on any given day. Data is gathered from public source records and then translated by our proprietary algorithms into an accurate reflection of the values paid in actual arms-length real estate transactions.
First, a little history…
The name Radar Logic references modern radar, and its ability to illuminate order out of chaos.
When I met with the CEO Michael Feder not too long ago and began to grasp what he and his team had accomplished, a light bulb went on in my head (despite the usual foggy conditions) and I wanted to be a part of this effort immediately. (more on that below) The Radar Logic approach solved the glaring problems found in national market statistics, such as moving averages and omission of data types. Up until now, this has prevented the financial markets from efficiently using residential real estate as a basis of trading instruments such as derivatives in a manner similar to the futures and options contracts available in more traditional commodities.
A derivative is a financial instrument used to trade or manage the asset upon which the instrument is based. It “derives” its value from something else (another asset or instrument). Derivatives are most often used to manage risk or to take positions on future market directions. Derivatives exist for a wide range of assets, such as commodities (gold, oil, corn), stocks and bonds, and on indices, such as the Dow Jones IndexÂ®. Until now, there have been few derivatives markets for residential real estate. Radar Logic Incorporated was founded for the purpose of enabling financial derivatives based on real estate.
The residential housing market is the largest asset class in the United States. To provide some perspective, the Federal Reserve indicates that the US housing market represents about $21 trillion in value. Commercial real estate, while a large asset class, is only about 20% of that amount. Yet because the residential real estate market is made up of 124 million units worth an average of around $240,000, it is fragmented and difficult to measure.
In addition, residential real estate as an asset class, is constantly changing. It is characterized by seasonality, new development, the surge of condos in metro areas and now, the rise in foreclosures. Its always changing. The Radar Logic methodology considers all verifiable transactions in a market to arrive at a value for the day that is not a moving average.
Its really exciting, and its groundbreaking stuff, to say the least. The beauty of this approach, is that there are no hidden filters, assumptions or calculations. In other words, the market is the market.
In addition to my duties at Miller Samuel and Miller Cicero, I have become Chairman of Radar Logic Research, LLC as well as Director of Research for Radar Logic Incorporated. I am still going to be active in the operation of Miller Samuel and produce the New York area market report series for Prudential Douglas Elliman that I created and have authored since 1994, with more markets to be added. Trust me, I have simply invented more time in a day. (More on that at another time, when there is more time in the day.)
Radar Logic Research will develop and publish research products providing market commentary and analysis related to real estate values across the United States later this year for institutions as well as enterprise-specific consulting services to real estate and financial organizations, including builders, developers, brokerages, commercial lenders, REITs, and investors such as pension funds, hedge funds and insurance companies. The initial plan is to offer these services to cover 25 major metro areas, roughly 2/3 of the value of the US housing market.
More on this to come!
Ok, back to work.
Tags: Seasonal Adjustment, Miller Cicero
Wow (I think). Congrats (I am pretty sure). I need to see it to get it, though.
Regardless, you will probably make more people happy (and make more money) on that inventing-more-time-in-the-day thing. What a break-through!
I hope you didn’t refinance your home to invest in this new venture.
Good luck, hope it’s a success.
Quote from today’s NAR press release.
“NAR President Pat Vredevoogd Combs said market conditions are clearly favoring buyers…First-time buyers now have more power to negotiate with sellers for help on downpayment or closing costs.”
Having the seller pay a higher share of closing costs is one thing. But downpayment? Let’s say a house sells for $500K, with a $400K mortgage and $100K in downpayment “help” from the seller. Isn’t that in fact a sale for $400K, with 100% financing?
Is that what he is talking about? Or is he talking about having sellers finance the seconds, since now no one else will and no one has any savings?
Looks like pressure to hit the number is going up.
Appraisers need cutting edge data that realtors don’t use, and since most MLS data is published by realtor associations, measuring the market as it changes has to be done by the individual appraisers. For busy appraisers, this kind of market research is difficult to accomplish. I hope your new venture will fill the niche.
Wow. Excellent news. The infrastructure for residential real estate derivatives trading is growing the right way.
Jonathan, this is fantastic news. Congratulations…
I’m sure all the institutional shops will be chomping at the bit for the analysis. You know, I was thinking that you were getting slothful these days; good to know that you aren’t slacking! 🙂
Congratulations, Mr. Miller! I am very excited for you!
Thanks everyone! This is one of those things that, when you read about it, the concept just “clicks” and you can’t wait to get to work on it. Thats how I felt about this one.
In my spare time, I’ll continue to work on my more-time-in-the-day-concept.
How will will this undertaking differ from the Case-Schiller index? I know that derivatives are already offered on this index at the CME. What information does this index attempt to capture that the Case-Schiller does not?
Hi Mitch – RL creates a daily spot price rather than a moving average. The CSI index provides a data point once a month and doesn’t include new construction, condos or foreclosures. Take a look at the white paper on the Radar Logic site – the link is within the post.
So, Jonathan, help me to understand a few things. How does the CSI Index or RL help me as a broker? How can daily vs Monthly info of this sort help me? Is this simply like trading bets on if itsn a Seller’s market or a Buyer’s market? How does this iformaton help my buyers, or the developers that I work with. How does this confront the daily onslaught of uninformed news from reporters assigned to cover the real estate beat? Will there be a charge to use your index? Why did you make this move? Is it your asspirations to do somehting other than be a big shot appraiser? Was appraising getting too small for you? Was the overal apprasing industry to small to define what your interests where? I saw you devour all that info Ken Swig and the Related guy speweed off the tips of their tongues at Lincon Center Conference. Thanks for your answers and best of luck
Residential housing is not a homogenous asset. The differentiation in types seems like a great difficulty to overcome in creating a “spot rate” for residential derivities. Would there have to be too many sub-classes within the asset class itself for the “spot rate” to be useful?
Hi Jonathan; I hope that some financial services people will get wealthy enough selling financial instruments based on the data, so that I can sell them that trophy penthouse they want to buy.
BTW, I agree with #1. The inventing more time in the day algorithm you’re using is the secret formula I think we all really want! Congratulations on the new venture.
downtown broker – any sort of housing index probably doesn’t help you directly in the course of a day as a broker. What it does do, however, is allow developers and financial institutions better under stand and adjust for market risk, something that current tools don’t allow for.
brian – good question – however, the spot rate is not used to price a specific property. I agree – with too many subclasses, the data set gets awfully thin. The idea with tracking a spot price on a daily basis, of say single family and condos, rather than a 90 days moving average of repeat sales is that a reliable trend for a market area can be demonstrated. Currently, through case shiller and ofheo, there are too many of the major property classes omitted (condos, new dev, forclosures and/or purchases with jumbo mortgages) that are relevant to a local real estate market.
I’m wondering how you’re planning to get accurate data for square feet to go into the calculation. In my forays into the manhattan residential market, I’ve discovered that the relationship between the advertised square footage of an apartment and its actual square footage is not very consistent (the stated square footage can range from slightly less than to as much as a third more than the actual square footage, in my experience).
It may be that, so long as the relationship between advertised and actual doesn’t shift too much, you’ll accurately track movements in $/sf, even if the spot average is systematically off.
But, especially if you’re tracking a daily spot price, with so few sales in a day, a few outliers might significantly impact the index.
Ari – ahhhh, thats the heart of it. Read the white paper and take a look at TPL. That controls for outliers in order to derive a daily price.