Tag: real estate education

The Single-Family Home as a Rental Property Investment — Using Regression to Estimate Value

Regression – no, it’s not what your family and friends accuse you of when you want to trade in the mini-van for a two-seater stick-shift convertible (well, maybe it is, but that’s a topic for a different article).

If you’re familiar with our RealData software, my online video courses, and my other blog posts here, then you know that I’m usually talking about income-producing property like multi-family, retail, office, or the like — seldom about single-family homes. And when we estimate the value of most income properties, we typically do so by looking at their income stream.

Recently, many investors (both big and small) have been buying up single-family homes to hold as rental properties, and that presents something of a conundrum: We still want to analyze cash flows and returns as any investor should, but when we think about the price we pay to acquire a home or the price we’ll get when we sell, our usual income-capitalization may not be the best approach.

Simply put, that’s because most single-family residences are bought and sold based on the price of comparable sales, not on their ability to produce rental income. Often, our comparable sales approach is informal and unscientific. The neighbor got \$250k, so I guess this house is worth the same. Or not.

Linear regression is a statistical technique we can use to approach this with more rigor. To put it into non-technical terms, it lets us look at a situation where we can take some facts that we know (dare we call them real data?) and use them to identify a trend. If a trend really does exist, that trend, in turn, allows us to predict the value of something otherwise unknown.

Let’s look at some examples. Five years ago my property taxes were \$1,000. Four years ago they were \$1,100. Three years ago, \$1,200. Two years ago, \$1,300 and last year \$1,400. Given this trend, what can we reasonably predict we’ll pay this year? Right. \$1,500.

How did we guess? We probably had a flashback to our junior high school algebra class (talk about regression!). In the graph paper of our mind, we plotted a perfectly straight line. The line was formed by a series of data points and it clearly suggested a trend.

Each data point on this graph represents two pieces of information, or “variables:” an independent variable (time) plotted along the horizontal x-axis and a dependent variable (the tax amount) plotted along the vertical or y-axis. The first data point, therefore, is a dot that appears where “5 yrs ago” and “\$1,000” intersect. The second point lands where “4 yrs ago” and “\$1,100” intersect and so on. The tax amount is the dependent variable because it changes as a function of time. In other words the tax bill depends on the year, not the other way around.

When we play connect-the-dots as in the graphic above (hence the name linear regression), we see that those dots form a perfectly straight line. If we extend that line beyond our known data points a bit, we can see that in the current year, assuming that the trend holds up, we could reasonably expect the taxes to be \$1,500. Of course, in real life our ducks don’t always line up so nicely in a row. When they look like the graphic below, we’ll probably need computer software to fit the best possible line to the series of points. Then we can use the resulting straight line to make our predictions.

There are numerous ways that we can use linear regression in real property analysis. We invite you to download a RealData® model to give the concept a spin. “Real estate value by linear regression” is a Microsoft Excel® workbook designed to help us estimate a property’s worth using the market data, or comparable sales, approach to valuation. This approach assumes that recent sales of properties that are nearby and are comparable to the subject provide the best indicators as to the value of the subject.

While we might sometimes use this model with other types of real estate, let’s assume for the sake of example that we want to estimate the value of a single-family residence. Although previously sold homes may be comparable they are unlikely to be identical, either to each other or to the subject being appraised. One may have more land; another may offer more interior space; a third may boast a better layout and so on.

As a rule such differences are generally reflected in the selling prices of the homes. Properties that are otherwise similar sell for more or less as a function of their distinguishing features. If we can identify some measure (index) of the appeal or amenities of the properties in a given neighborhood, then we may also be able to discern a pattern between that measure and the value of the properties — our trend line again. We can then use the pattern to predict the values of other properties in the same locale.

Our model will permit us to determine by regression analysis whether or not a linear relationship exists between selling price and some independent variable that we define. One possible technique is to use the property tax assessment as an index of value. Although assessments seldom reflect true market price, they often provide a good indication of relative value, so they’re worth a try. If the assessments and prices from a number of recent home sales in a neighborhood define a linear relationship, our model can measure the strength of that relationship and use it to estimate the worth of a home not yet sold.

After we open this model we can enter the address, an index and an adjusted selling price for as many as fifteen comparable sold properties. (Regarding the term “adjusted:” We may want to correct for price inflation whenever a sale is more than a few months old.) At the bottom (after #15), we’ll enter the address and the index amount of the subject property. The program will fill in the field for the number of comparables used and compute the subject property’s estimated selling price.

The results appear in a report and graph, in the section below.

Notice that the program will specify a correlation coefficient. This is a new bit of terminology we didn’t see in our simplified explanation above. This number is a statistical measurement of the reliability of the relationship between the index and the adjusted selling price. To put it another way, it’s a numerical way of expressing how straight our dots line up. A correlation of 1.00 is a perfect relationship, while zero indicates that we have completely random data. In most cases, we would like to see a correlation coefficient of at least 0.80 to believe that there is a strong enough relationship between the index and selling price to use that relationship as the basis of a prediction.

As an interesting sidebar, we can see how accurately this regression analysis would have predicted the values of the homes whose actual selling prices we know. That is because the program computes and displays the selling prices that the analysis would have predicted for each of the comparables. We also see the dollar and percentage differences between the projected and actual prices. This section provides a very graphic demonstration of the accuracy — or inaccuracy — of our model’s prediction.

We need to keep in mind that, as with most projections, the quality of our output is entirely dependent on the quality of our input. We certainly have to make appropriate choices for our comparables. Otherwise we can’t reasonably expect to achieve meaningful results. In addition, the kind of index we select must relate consistently to value. If we find tax assessments to be unreliable, we may want to try gross living area or experiment with a scoring system (X points for each bedroom, Y points for each bath, etc.). We may also want to consider trying for even greater accuracy in our predictions by advancing to what’s called “multiple linear regression,” a similar technique where we consider two or more independent variables as possible predictors of an outcome (i.e., a dependent variable).

A regression analysis like the one provided in this model can be very useful because of its ability to provide statistical support to what might otherwise be a subjective estimate of value. Property sellers and buyers can use it to support price negotiations; and agents can use it to enhance the effectiveness of their listing presentations. And of course, investors can estimate the initial cost and ultimate reversion value of a single-family home bought and held as a rental property. With a bit of imagination, linear regression can be used in many ways to poke and prod our analyses and projections. It’s name notwithstanding, it can take us a big step forward.

The information presented in this article represents the opinions of the author and does not necessarily reflect the opinions of RealData® Inc. The material contained in articles that appear on realdata.com is not intended to provide legal, tax or other professional advice or to substitute for proper professional advice and/or due diligence. We urge you to consult an attorney, CPA or other appropriate professional before taking any action in regard to matters discussed in any article or posting. The posting of any article and of any link back to the author and/or the author’s company does not constitute an endorsement or recommendation of the author’s products or services.

What Every Real Estate Investor Needs to Know About Cash Flow — thanks for the recent reviews

Many thanks to one of my favorite podcasters, Keith Weinhold, for his youtube review of my book, “What Every Real Estate Investor Needs to Know About Cash Flow.”

Also a “thank you” to Flagship Bank for including my book in their list of  “…the best commercial real estate investing books you can buy…”

—Frank Gallinelli

President, RealData, Inc.

Love Your Hat! What is Your Lender Really Looking at When You Apply for a Commercial Mortgage?

If you’re not an all cash buyer, then when you purchase a piece of income-producing real estate you’ll probably need to secure mortgage financing to complete the deal. It’s essential for you to understand what your lender is looking at when underwriting that loan.

And — If you guessed that he or she is not admiring your millinery —  ok then, stick with me here. I’m going to discuss briefly a couple of key yardsticks.

Of course, this short video blog post is just the tip of the iceberg when it comes to evaluating, financing, and acquiring a successful real estate investment.

For in-depth insight into on all the key metrics and methods, check out https://realestateeducation.net/

And you’ll find the software that will do all the heavy lifting for your analysis and presentation at https://realdata.com

The information presented in this article represents the opinions of the author and does not necessarily reflect the opinions of RealData® Inc. The material contained in articles that appear on realdata.com is not intended to provide legal, tax or other professional advice or to substitute for proper professional advice and/or due diligence. We urge you to consult an attorney, CPA or other appropriate professional before taking any action in regard to matters discussed in any article or posting. The posting of any article and of any link back to the author and/or the author’s company does not constitute an endorsement or recommendation of the author’s products or services.

Video post: Understanding Net Operating Income, Part 2

In Part 1 this post, we looked at the revenue side of our NOI calculation. Now let’s look at the expense side, and how the end result – the NOI itself, is typically used when evaluating a potential real estate investment. Click the image below.

If you missed Part 1, you can watch it here.

The information presented in this article represents the opinions of the author and does not necessarily reflect the opinions of RealData® Inc. The material contained in articles that appear on realdata.com is not intended to provide legal, tax or other professional advice or to substitute for proper professional advice and/or due diligence. We urge you to consult an attorney, CPA or other appropriate professional before taking any action in regard to matters discussed in any article or posting. The posting of any article and of any link back to the author and/or the author’s company does not constitute an endorsement or recommendation of the author’s products or services.

Video post: Understanding Net Operating Income, Part 1

One topic that seems to generate a lot of interest and questions among investors I speak with is the subject of net operating income. Those who are new to real estate investing and even those with some experience are often unclear as to exactly what it is, what it means, and how to use it.

To shed some light on this topic, I’m going to try something new here – new for me at least – a video blog post. I’ll try to answer those questions by giving you a basic roadmap of how Net Operating Income is calculated, and how it’s used in real investment situations. So —  here we go with Part 1 of 2. Click the image below.

Part 2 is now available here.

The information presented in this article represents the opinions of the author and does not necessarily reflect the opinions of RealData® Inc. The material contained in articles that appear on realdata.com is not intended to provide legal, tax or other professional advice or to substitute for proper professional advice and/or due diligence. We urge you to consult an attorney, CPA or other appropriate professional before taking any action in regard to matters discussed in any article or posting. The posting of any article and of any link back to the author and/or the author’s company does not constitute an endorsement or recommendation of the author’s products or services.

New content in my online video course

Those of you who are already enrolled in my course, Introduction to Real Estate Investment Analysis, are probably aware that I’ve been regularly adding new content to the course over time.

My most recent addition is a lesson on “Phantom Income.” The lesson discusses how and when it might be possible for your taxable income to outpace your cash flow. Probably something you’d prefer to avoid if you could.

New content like this is always available at no charge to those who are enrolled in the course, but for a limited time this new lesson will be my treat to anyone who would like to view it.

So, even if you’re not already enrolled, just go to the course home page, and scroll down about two-thirds, past my smiling face, until you see the curriculum. You can find the lesson in the middle of the section called Real Estate Pro Formas. Click the Preview button to watch.

In case you missed it, I also added a three-part series this summer called, “Blend and Extend.”

This is a technique that landlords and tenants have used during difficult times in the past — a technique where a bit of give and take could potentially benefit both parties. A timely topic, I believe, given the upheaval in commercial real estate during the pandemic.

I’m making the first video in the series available as a free preview. Again, go to the curriculum, but this time expand it and scroll to the very bottom to find “Blend and Extend.” That’s where you can preview Part 1.

In the two remaining lesson in this series, I go into more specifics about the ways you might actually run the numbers on a possible lease restructuring to find a scenario acceptable to both sides. I include examples was well as an Excel model that should help you with the calculations.

Since the original release of the course, I’ve added a great deal to my core content, including a series of case study examples, as well as modules on partnerships, development projects, and value-add investments.

But I’m always enthusiastic about broadening the scope of the learning you can derive and the benefits you can reap from the course. Do you have an idea for an additional topic you’d like to see? If so, please pass along your suggestion in the comments section! Thank you.

— Frank G

The information presented in this article represents the opinions of the author and does not necessarily reflect the opinions of RealData® Inc. The material contained in articles that appear on realdata.com is not intended to provide legal, tax or other professional advice or to substitute for proper professional advice and/or due diligence. We urge you to consult an attorney, CPA or other appropriate professional before taking any action in regard to matters discussed in any article or posting. The posting of any article and of any link back to the author and/or the author’s company does not constitute an endorsement or recommendation of the author’s products or services.

“The Top 10 Real Estate Finance Books Every Investor Should Read.”

I was honored to find that one of my books was featured at the top of a recent article on Motley Fool: “The Top 10 Real Estate Finance Books Every Investor Should Read.” The book, “What Every Real Estate Investor Needs to Know About Cash Flow,” was originally published in 2004, is now in its third edition, and is alive and still doing well —  a surprise certainly to me, and probably to the publisher as well.

I often get asked what accounts for the book’s long-term appeal, and I think there may be two reasons: First, I avoided “topical” or trendy content, preferring to stick with core concepts and math-based metrics don’t change with time. And second because I really dislike the get-rich quick hype that seems to characterize so many real estate books, and so I shunned that, too.

I don’t think they’ll ever make a movie out of it, but I’m satisfied if it has helped some readers make informed and unemotional investment decisions.

You can find the article here.

Are you involved in real estate education?

We’re reaching out to our followers who teach real estate investment, development, or finance to let you know that our Real Estate Investment Analysis course is available for the virtual classroom – now with volume academic pricing.

For more than a decade I’ve devoted much of my professional life to investor education, as a writer, Columbia adjunct professor, and through my company RealData. As you may know, a few years ago I created an online video course, Introduction to Real Estate Investment Analysis. It has grown to include a broad range of topics that are key to understanding how income-producing properties work, and how investors, developers, lenders, and others evaluate their financial dynamics.

With so many schools and colleges now needing to provide good content for a virtual learning environment, we’ve re-deployed the course as a resource that instructors can add to their existing curricula. We now offer volume academic pricing at a significant discount, depending on class size.

If you’re involved in real estate or financial education, then I hope that this can help you provide meaningful content to your remote learners. To get a quote for volume licenses for student use or to discuss this further, please email me at education@realdata.com.

— Frank Gallinelli

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The information presented in this article represents the opinions of the author and does not necessarily reflect the opinions of RealData® Inc. The material contained in articles that appear on realdata.com is not intended to provide legal, tax or other professional advice or to substitute for proper professional advice and/or due diligence. We urge you to consult an attorney, CPA or other appropriate professional before taking any action in regard to matters discussed in any article or posting. The posting of any article and of any link back to the author and/or the author’s company does not constitute an endorsement or recommendation of the author’s products or services.

Now earn a digital certificate with my video course, “Introduction to Real Estate Investment Analysis”

Professional education is a great thing. And being able to broadcast news of your success makes it even more valuable.

That’s why I’m announcing a new benefit to students who enroll in my course, Introduction to Real Estate Investment Analysis. I’m now awarding a digital Certificate of Achievement and badge to students who successfully complete the course.

Here are some questions you probably want to ask:

What does it cost? For my students: nothing. RealData is picking up the cost of issuing and hosting the certificate.

What do you mean by “digital certificate?” Your certificate will be hosted by Accredible.com, an industry-leading credentialing platform. As you’ll see below, it’s designed so you can share it easily.

Does that mean I don’t get a physical certificate to hang on my office wall? No, you also get a pdf version you can print.

• You receive a unique url for your Certificate, so you can share it with employers, clients, industry groups, just about anyone.
• You can share it on any of your social media networks with just a click on a toolbar.

Your personal certificate page includes a dashboard, as shown at the left. From there you can…

• Get the code to embed it in your website
• Email it to anyone

How do I obtain my certificate?Within a few days after you complete the work to earn your certificate, we’ll send you an email with instructions to access it. If you believe you’ve completed the requirements but haven’t heard from us, please contact us at mailto:education@realdata.com

I believe our online video course provides a solid educational opportunity for those who want to learn about real estate investment and development. I hope this digital certificate will recognize your efforts and will benefit you for devoting the time and effort to pursue that education. I look forward to contacting you when you complete your coursework!

Frank Gallinelli

Learn by Example

I’ve seen a great deal of interest in the real estate investment case studies that are part of my investment analysis video course — so I’ve spun those cases off as a new mini course, one where you can learn by example.

The cases deal with three different property types:

• apartment building,
• mixed-use, and
• triple-net-leased

They’re similar to those I cover in my grad-school course at Columbia, and I’ve designed them with several purposes in mind:

• To give you practice working through bumper-to-bumper deal analysis. On what terms does each deal make sense to you?
• To introduce special situations that you need to understand, such as expense recoveries and triple-net leases.
• To give you an opportunity to put yourself inside the deal as if you were a real participant, to think as an investor thinks — beyond the numbers, beyond the surface data, as if real money were on the table.

Once you’ve learned about deal analysis with this mini course, you’ll probably want to take the complete course, covering detailed real estate investment metrics, partnerships, development, and more. So here’s more good news:

When you upgrade to the bigger course, you’ll get full credit for  this mini course.