593: Using Data Driven REI to Find Discounted Properties

January 31, 2022bmanasseroUncategorizedNo comments

SHOW NOTES FOR EPISODE 593: USING DATA DRIVEN REI TO FIND DISCOUNTED PROPERTIES

The real estate market is hot! As a result, trying to find below-market properties is nearly impossible! In today’s podcast, engineer, real estate investor and founder of RealtyQuant Stefan Tsvetkov shares how he is finding tons of below-market properties in competitive markets through data-driven real estate investing strategies.

What You Will Learn

Where you can find “under market” deals in today’s booming real estate market
Why data-driven REI is a “numbers game”
How you can learn to data scrape and find deals from your own computer
How to write and publish to Blockchain for maximum results
The four states that were the most in overvalued as a result of the pandemic
Three states he is targeting for the best deals

About Our Guest

Stefan Tsvetkov

Stefan Tsvetkov is the Founder of RealtyQuant (https://www.realtyquant.com), a company that brings data-driven and quantitative techniques to the real estate industry. On a mission to add massive industry value through education, investment, technology, and analytics. Financial engineer turned multifamily investor, analytics speaker, and live webinar host. He holds a Master’s degree in Financial Engineering from Columbia University, and during his finance career managed ~$90 billion derivatives portfolio jointly with colleagues. Featured on multiple Podcast and Webinar events including InvestUp, Best Ever Real Estate Show, Discovering Multifamily etc. Host of Finance Meets Real Estate webinar series

More About Stefan

Stefan came from Eastern Europe to the U.S., at age 22, to work on his Master’s degree in Finance and Engineering
He had career in finance for nearly a decade
After that, he was a full-time multifamily investor
He lives and invests mainly in New York City and New Jersey
His first property was a fourplex he bought and house hacked (lived in one unit and rented out the rest) in New Jersey
From there, he started using data to find other good properties
What states are the most overvalued?
He also started writing scripts that he could use when talking to sellers

Using Technology to Find Good Deals

He started writing programs that could scan thousands of on-market and off-market properties at one time. He used
- MLS
- County records
He started to look at properties by key criteria
- Best cap rates
- Discounts
- Properties that would be good candidates for condominium conversions – a good spread from multifamily to condo
  - Converting a multifamily property into a condo only requires
    - Doing the legal side work
      - Bylaws
      - Master deed
    - Setting up an HOA/condo association
    - Determining the HOA fees
    - Conditions and requirements for use of the common areas
      - How the common area is separated
  - While the condos are being sold you do need to run the HOA
Finding residential is easier because you can literally pull thousands of listings and can zero in on the top .01%
- He had great deal more success in areas that
  - Were undervalued
  - Where liquidity is a bit less
  - Places like:
    - Upstate New York
    - New Jersey
  - He could find discounted deals pulling county records
    - He would look at the market value of the properties according to the tax authorities
      - The assessment times the equalization rate
    - He found a small condominium building
      - Purchased it perfectly turn-key
      - He had 25% upside by simply recognizing that he could find buyers who would not be overly concerned about the profile of the property
    - He had a residential fourplex that he turned into a commercial 5 unit – that doubled the valuation
    - He recognized that most real estate players are focused on the renovation/rehab aspects
      - The hardest deals to find in New York City are like a gut rehab
        
        There were like 15 offers in a day
      - Instead, he focused on where his advantage was
        
        He could structure more deals around turn-key properties
        
        He looked mainly at stabilized, turn-key properties – stabilized arbitrage strategy
        
        Very little rehab/renovation, if any
    - He was flipping but not with the greatest urgency (usually 6 months to 2 years) for the greatest equity gain
    - He has done 7 properties with this strategy – usually 3-4 family multifamily properties into condominiums
      - Not too many people in his area want to attempt condo conversions
    - To find the right kind of property to convert takes a lot of work
Today, he’s more recently focused on commercial, which is more limited

RealtyQuant

Stefan set up a company called RealtyQuant, where his mission is to build different data-driven tools and analytics for the real estate industry — to help investors and other people interested in this data
He is coming out with a new product that will do commercial multifamily lead generation
- Off-market properties
- Commercial multifamily only
- He does not do a residential product like this
He also teaches a course on data-driven real estate investing on Python
- He teaches people how to do it themselves
- He teaches people:
  - How to do the scrapes
  - Shows all his models for residential – on-market, commercial off-market
  - Automated evaluation models (zero Zestimate) to price houses automatically
  - Different components of automated underwriting
    - Condition scoring technology
      - Taking an image of a property and automatically giving a score on its condition
        
        1 to 5 score – 1 being perfect and 5 meaning it requires complete renovation
        
        On the textual side, it’s being done using natural language processing models
        
        The main goal is “What’s holding us back from automated underwriting?” – at least in a preliminary sense
        
        It’s more a way to visual rate thousands of properties to help in the narrowing down process
  - He also teaches a class on Blockchain
    - How to set up your own security token
    - How to write up your code and publish it on the Blockchain zero network or other network
- To take his courses it would help if you had technical background and experience who are willing to learn a little Python (the programming languages)
  - He is however, trying to make it with “no code” tools so that more people can benefit

Predicting Overvalued Markets

RealtyQuant also has access to extensive valuation reports on over 2,000 markets/counties:
- A collection of state-level and county-level reports and data, assisting you in best gauging overvalued real estate markets and their appreciation potential.
- It has also developed statistical predictors for market appreciation, as well as a valuation metric to gauge market downside risk.
- Where markets are at and where they are trending
- What markets are over-valued
- Auto-correlation
- Updated quarterly
You can find out which markets are overvalued. For example, for the recent Covid 19-triggered global financial crisis:
- States that most overvalued dropping by 40-60% were:
  - Arizona
  - California
  - Nevada
  - Florida
- State that didn’t drop in value
  - Texas – it only dropped 4%
  - North Dakota didn’t drop at all
- End of 2020
  - Idaho was the only strongly overvalued state
    - It jumped to 47% overvalued by the end of 2021
- From 2017-2021
  - Texas and Florida were in the 8-10% overvalued range
    - Were the top markets for multifamily investors
    - In the 2nd and 3rd quarters of 2021, their numbers doubled
- End of 2021
  - Midwest and Northeast were undervalued
- Undervalued Markets
  - Carry very little downside risk exposure – they’re almost immune
  - Before the global financial crisis, the 10 states that were the most undervalued dropped an average of 4%
    - There was very little change after the crisis
    - They may not see much appreciation either
  - For his own longer term investing, he is targeting these states
    - Indiana
    - Ketucky
    - Ohio
  - For shorter term holds (2 year max)
    - Georgia
    - Florida

Advice for Old Dawgs Looking at Real Estate Investing to Help Them in Their Retirement Years

Only invest in markets with the best downside protection
If you are more active and want to invest in commercial assets, utilize rental listings information to generate leads
- Access data points online
  - Utility charges
  - Rent rates
- Look at those that have the most value-add
  - Undervalued
  - Rents are below market
  - Other income components
    - Administrative fees
- This can benefit you a lot
- He will have a lead-generation product online soon that can help you with this

Current Business

What excites him about the future of his business
- Building out new models and tools for data-driven development
- Utilizing Blockchain for commercial market
  - Liquidity
  - Private equity
  - It will open doors to sponsors
  - It’s decentralized finance
  - Operators in mid-range commercial real estate projects would be tokenized
    - And not just at the asset level (which adds a little bit of liquidity to the project) because you can sell your tokens at the secondary exchange
    - But it’s really building up the equity stream of blockchain tokens that perhaps represent different sectors (i.e. self storage, retail, multifamily, etc.)

Rap-It-Up

Favorite real estate book: Best Ever Apartment Syndication Book by Joe Fairless
Favorite business book: The Richest Man in Babylon by George S Clason
Most valuable web site for success (other than your own): BiggerPockets.com
Favorite app: YouTube
Favorite quote: “We’re intellectually the superficial reflection of what we have learned and taught.”
If you lost everything – all your assets – and had to start all over, knowing what you already know, and you only had $1,000, what would you do to re-launch your real estate investing business? I would use my knowledge and other people’s money.

How to Reach Stefan

Website: RealtyQuan.com
YouTube Channel: Finance Meets Real Estate

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Additional Episode Sponsor: Meno Studio – menostudio777@gmail.com

bmanassero

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