# Tag: cash flow

## 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.

## New Version of our Income-Property Video Tutorial

We’ve just released an updated version of our video tutorial, How to Evaluate an Income Property Investment with REIA Pro. We’ve given the video a serious makeover — additional content, better audio and graphics, greater emphasis on how to use RealData’s REIA software to perform an analysis — and have added a seventh video that provides an overview of some of the software’s more advanced features.

•    You get access to the web-based video series on our new e-learning platform. Watch it online at your convenience — on your desktop or mobile device.
•    The property analysis is based on a sample case study of a mixed-use property.
•    The series uses our REIA Pro product to analyze the investment, but many of of the features portrayed in the videos are found in the REIA Express edition.
•    The series is presented by Frank Gallinelli, founder of RealData, Inc.
•    Includes seven videos with over 2 hours of instruction

If you’ve already purchased the original release of this series, you’ll receive an email with instructions on how to get the new version at no charge. If you haven’t purchased it before, we invite you to download the case study and view a lesson-by-lesson synopsis.

## New Podcast: Investing in Income-Producing Real Estate

I had the privilege recently of recording a video podcast with REICLub, where we discussed investing in income-producing real estate: deciding what kind of property you should buy, how to begin the analysis process, understanding the income stream, estimating value or worth, dealing with long-term projections, recognizing common pitfalls, investing with partners.

I invite you to view it here:

http://www.REIClub.com/FrankGallinelli

—Frank Gallinelli

## New Edition of Frank Gallinelli’s “What Every Real Estate Investor Needs to Know..”

Frank Gallinelli’s popular book, “What Every Real Estate Investor Needs to Know about Cash Flow…” is now available in a new third edition. Frank has added detailed case studies while maintaining the essentials that have made his book a staple among investors. The new cases show how to evaluate an apartment building, a mixed-use, and a triple-net leased property — not just running the numbers, but also looking beyond the surface data to see how you might discern what’s really going on with a potential investment.

See the new edition at Amazon here.

McGraw-Hill first published Frank’s book in 2003 and has since sold over 100,000 copies. For more than a decade it has been a top title in the real estate section at Amazon.

For those seeking reviews from readers, look to the 100+ reviews of the second edition at Amazon, which collectively rate the book at 4.6 out of 5 stars.

And finally, a visual clue: Second edition has a blue cover, new third edition has a green cover.

## The Cash-on-Cash Conundrum – a Postscript

A while back, I posted a two-part series called “The Cash-on-Cash Conundrum.” In the first installment I explained the calculation and underlying logic of CoC, and in the second I discussed some of the pitfalls of overreliance on this particular measure.

I try to keep my ear to the ground by reading and sometimes contributing to investor forums, where I continue to see a good deal of discussion on the question of what is or what should be the metric of choice for real estate investors. My unofficial and unscientific gauge of the general sentiment is that most investors agree that cash flow is king. Although I would be reluctant to crown any single measure as the absolute be-all and end-all for property analysis, I agree that cash flow is indeed a critical measure of the health of an investment property.

So what’s the big deal? What concerns me is that I see a kind of tunnel vision on this topic. I frequently hear some variation of these two statements bundled together: “Cash-on-cash return is the only reliable metric and the only one I really need,” and “IRR and Discounted Cash Flow analysis are bogus – they’re a waste of time because you just can’t predict the future.” To put it simply, these folks are saying that they trust CoC because it looks at the here and now, and they distrust IRR/DCF because it tries to look into the future.

On the surface, that argument might seem reasonable enough. Cash-on-Cash return is the property’s expected first-year cash flow before taxes, divided by the amount of cash invested to make the purchase; it’s quick and easy to calculate, and it does indeed focus on a more-or-less tangible present. A strong CoC unarguably provides a good sign that your investment is off on the right foot.

Is that the end of the story – or should it be? I think this narrow focus can cause an investor to miss some vital issues.

By adopting the “can’t predict the future” argument, aren’t you ignoring what investing is all about? You don’t have a crystal ball, but still — isn’t investing about the future, and isn’t the ability to make sensible choices in an uncertain environment a key trait of the successful investor?

I find it difficult to accept the argument that I should make a decision to buy or not to buy an investment property based on its first-year cash flow alone and without regard to projections of future performance. Ironically, there is a hidden message in this point of view: If the first year performance data is sufficient, then apparently I should believe that such data will be representative of how well the property will perform all the time. In other words, it really is OK to predict the future, so long as I believe the future will always be like the present.

I would argue that it is in fact less speculative to make the kind of projections that you typically see in a Discounted Cash Flow analysis, where you look at the anticipated cash flow over a period of time and use those projections to estimate an Internal Rate of Return over the entire holding period.

With any given property, there may be items that you can forecast with a reasonable degree of confidence. For example, on the revenue side you may have commercial leases that specify the rent for five years, ten, or even more. You may even be able to anticipate a potential loss of revenue at a point in the future when a commercial lease expires and you need to deal with rollover vacancy, tenant improvements, and leasing commissions.

You could be looking at a double- or triple-net property where you are insulated from many or most of the uncertainties about future operating expenses like taxes, insurance and maintenance.

Or, with residential property, you may have a history of occupancy percentage and rent increases that permit a credible forecast of future revenue.

Then there is the more basic question, why are you analyzing this property at all? Why are you running the numbers and making this CoC calculation? Are you trying to establish a current market value, as a commercial appraiser might? Or are you trying to make a more personal decision, i.e., will this particular property possibly meet your investment goals? And what are those goals?

Seems like I just took a nice simple metric and wove it into a more complicated story. Sorry, but in your heart of hearts you know if investing really were that simple, then everyone with a pulse would be a huge success. At the same time, it doesn’t have to be so complicated either, so long as you approach it in a reasonable and orderly way.

That orderly approach begins with deciding what you are looking to get out of this investment. Maybe you want to hold it for a few years to get strong cash flow and then sell it, hopefully for a profit. Perhaps you intend to hold it long term, less concerned with immediate cash flow (so long it as it positive), and then sell the property much later to fund your children’s college costs or your own retirement. In either case, if your plan is to buy and hold then there is one thing you can’t ignore: the future.

This approach continues with projection of the revenue, expenses, potential resale, and rate-of-return metrics, running out to your intended investment horizon. Perhaps key here is the realization that you shouldn’t really expect to nail your projections with a single try. Consider several variations upon future performance: best-case, worst-case and somewhere in-between scenarios to give yourself a sense of the range of possible outcomes.

All this brings us back to the duel between the Cash-on-Cash metric and DCF/IRR. I believe if you rely only on the former, then you are not just saying, “You can’t predict the future.” You’re saying, “If the first year looks good, then that’s all I need to know.” This is, quite literally, a short-sighted investment strategy. The takeaway here is that there should be no duel between metrics at all; that prudent investors can use Cash-on-Cash to get an initial reading of the property’s immediate performance, but they should then extend their analysis to encompass the entire lifecycle of the investment. To quote the folks at NASA (who, after all, really are rocket scientists), “It takes more than one kind of telescope to see the light.”

—-Frank Gallinelli

####

Your time and your investment capital are too valuable to risk on a do-it-yourself investment spreadsheet. For more than 30 years, RealData has provided the best and most reliable real estate investment software to help you make intelligent investment decisions and to create presentations you can confidently show to lenders, clients, and equity partners. Learn more at www.realdata.com.

## How to Look at Reserves for Replacement When You Invest in Income-Property

It may sound like a nit-picking detail: Where and how do you account for “reserves for replacement” when you try to value – and evaluate – a potential income-property investment? Isn’t this something your accountant sorts out when it’s time to do your tax return? Not really, and how you choose to handle it may have a meaningful impact on your investment decision-making process.

What are “Reserves for Replacement?”

Nothing lasts forever. While that observation may seem to be better suited to a discourse in philosophy, it also has practical application in regard to your property. Think HVAC system, roof, paving, elevator, etc. The question is simply when, not if, these and similar items will wear out.

A prudent investor may wish to put money away for the eventual rainy day (again, the roof comes to mind) when he or she will have to incur a significant capital expense. That investor may plan to move a certain amount of the property’s cash flow into a reserve account each year. Also, a lender may require the buyer of a property to fund a reserve account at the time of acquisition, particularly if there is an obvious need for capital improvements in the near future.

Such an account may go by a variety of names, the most common being “reserves for replacement,” “funded reserves,” or “capex (i.e., capital expenditures) reserves.”

Where do “Reserves for Replacement” Fit into Your Property Analysis?

This apparently simple concept gets tricky when we raise the question, “Where do we put these reserves in our property’s financial analysis?” More specifically, should these reserves be a part of the Net Operating Income calculation, or do they belong below the NOI line? Let’s take a look at examples of these two scenarios.

Now let’s move the reserves above the NOI line.

The math here is pretty basic. Clearly, the NOI is lower in the second case because we are subtracting an extra item. Notice that the cash flow stays the same because the reserves are above the cash flow line in both cases.

Which Approach is Correct?

There is, for want of a better term, a standard approach to the handling capital reserves, although it may not be the preferred choice in every situation.

That approach, which you will find in most real estate finance texts (including mine), in the CCIM courses on commercial real estate, and in our Real Estate Investment Analysis software, is to put the reserves below the NOI – in other words, not to treat reserves as having any effect on the Net Operating Income.

This makes sense, I believe, for a number of reasons. First, NOI by definition is equal to revenue minus operating expenses, and it would be a stretch to classify reserves as an operating expense. Operating expenses are costs incurred in the day-to-day operation of a property, costs such as property taxes, insurance, and maintenance. Reserves don’t fit that description, and in fact would not be treated as a deductible expense on your taxes.

Perhaps even more telling is the fact that we expect the money spent on an expense to leave our possession and be delivered to a third party who is providing some product or service. Funds placed in reserve are not money spent, but rather funds taken out of one pocket and put into another. It is still our money, unspent.

What Difference Does It Make?

Why do we care about the NOI at all? One reason is that it is common to apply a capitalization rate to the NOI in order to estimate the property’s value at a given point in time. The formula is familiar to most investors:

Value = Net Operating Income / Cap Rate

Let’s assume that we’re going to use a 7% market capitalization rate and apply it to the NOI. If reserves are below the NOI line, as in the first example above, then this is what we get:

Value = 55,000 / 0.07

Value = 785,712

Now let’s move the reserves above the NOI line, as in the second example.

Value = 45,000 / 0.07

Value = 642,855

With this presumably non-standard approach, we have a lower NOI, and when we capitalize it at the same 7% our estimate of value drops to \$642,855. Changing how we account for these reserves has reduced our estimate of value by a significant amount, \$142,857.

Is Correct Always Right?

I invite you now to go out and get an appraisal on a piece of commercial property. Examine it, and there is a very good chance you will find the property’s NOI has been reduced by a reserves-for-replacement allowance. Haven’t these people read my books?

The reality, of course, is that diminishing the NOI by an allowance for reserves is a more conservative approach to valuation. Given the financial meltdown of 2008 and its connection to real estate lending, it is not at all surprising that lenders and appraisers prefer an abundance of caution. Constraining the NOI not only has the potential to reduce valuation, but also makes it more difficult to satisfy a lender’s required Debt Coverage Ratio. Recall the formula:

Debt Coverage Ratio = Net Operating Income / Annual Debt Service

In the first case, with a NOI of \$55,000, the DCR would equal 1.41. In the second, it would equal 1.15. If the lender required a DCR no less than 1.25 (a fairly common benchmark), the property would qualify in the first case, but not in the second.

It is worth keeping in mind that the estimate of value that is achieved by capitalizing the NOI depends, of course, on the cap rate that is used. Typically it is the so-called “market cap rate,” i.e., the rate at which similar properties in the same market have sold. It is essential to know the source of this cap rate data. Has it been based on NOIs that incorporate an allowance for reserves, or on the more standard approach, where the NOI is independent of reserves?

Obviously, there has to be consistency. If one chooses to reduce the NOI by the reserves, then one must use a market cap rate that is based on that same approach. If the source of market cap rate data is the community of brokers handling commercial transactions, then the odds are strong that the NOI used to build that market data did not incorporate reserves. It is likely that the brokers were trained to put reserves below the NOI line; in addition, they would have little incentive to look for ways to diminish the NOI and hence the estimate of market value.

The Bottom Line – One Investor’s Opinion

What I have described as the standard approach – where reserves are not a part of NOI – has stood for a very long time, and I would be loath to discard it. Doing so would seem to unravel the basic concept that Net Operating Income equals revenue net of operating expenses. It would also leave unanswered the question of what happens to the money placed in reserves. If it wasn’t spent then it still belongs to us, so how do we account for it?

At the same time, it would be foolish to ignore the reality that capital expenditures are likely to occur in the future, whether for improvements, replacement of equipment, or leasing costs.

For investors, perhaps the resolution is to recognize that, unlike an appraiser, we are not strictly concerned with nailing down a market valuation at a single point in time. Our interests extend beyond the closing and so perhaps we should broaden our field of vision. We should be more focused on the long term, the entire expected holding period of our investment – how will it perform, and does the price we pay justify the overall return we achieve?

Rather than a simple cap rate calculation, we may be better served by a Discounted Cash Flow analysis, where we can view that longer term, taking into account our financing costs, our funding of reserves, our utilization of those funds when needed, and the eventual recovery of unused reserves upon sale of the property.

In short, as investors, we may want not just to ask, “What is the market value today, based on capitalized NOI?” but rather, “What price makes sense in order to achieve the kind of return over time that we’re seeking?”

How do you treat reserves when you evaluate an income-property investment?

—-Frank Gallinelli

####

Your time and your investment capital are too valuable to risk on a do-it-yourself investment spreadsheet. For more than 30 years, RealData has provided the best and most reliable real estate investment software to help you make intelligent investment decisions and to create presentations you can confidently show to lenders, clients, and equity partners. Learn more at www.realdata.com.

## Podcast: “Learn the key principles to effectively analyzing and evaluating your real estate deals”

I had the pleasure of recording a podcast recently with real estate entrepreneur Kevin Bupp. We discussed what I feel are some of the key principles that every real estate investor ought to understand — and so, I invite you to listen to that podcast here.

## Understanding Net Operating Income

My recent discussions here of cash flow, DCF, pro formas and the like have prompted some readers to ask for a review of the key metrics that underlie a good and thorough income-property analysis.

One of the downsides of hanging around in business too long — we’re closing in on our 33rd anniversary — is that some of our best material is now lurking off in the archives.  So, after digging around in our virtual attic, I’ve found several topics that go to the heart of the matter, and that attracted quite a few readers when they first appeared.

Topping that list is our article about Net Operating Income. Here is a trailer of sorts, with a link to the complete article:

Understanding Net Operating Income

In a recent article, we discussed the use of capitalization rates to estimate the value of a piece of income-producing real estate. Our discussion concerned the relationship among three variables: Capitalization Rate, Present Value and Net Operating Income.

We may have gotten a bit ahead of ourselves, since some of our readers were unclear on the precise meaning of Net Operating Income. NOI, as it is often called, is a concept that is critical to the understanding of investment real estate, so we are going to backtrack a bit and review that subject here.

Everyone in business or finance has encountered the term, “net income” and understands its general meaning, i.e., what is left over after expenses are deducted from revenue.

With regard to investment real estate, however, the term, “Net Operating Income” is a minor variation on this theme and has a very specific meaning. …

read the rest of the article here—>>

—Frank Gallinelli

####

Your time and your investment capital are too valuable to risk on a do-it-yourself investment spreadsheet. For more than 30 years, RealData has provided the best and most reliable real estate investment software to help you make intelligent investment decisions and to create presentations you can confidently show to lenders, clients, and equity partners. Learn more at www.realdata.com.

## The Cash-on-Cash Conundrum, Part 2

In the first part of our discussion, you looked at the simple math that underlies Cash-on-Cash Return. The short version goes like this:  First you calculate your property’s first-year cash flow before taxes—essentially all the cash that comes in from operating the property minus all the cash that goes out. Then you divide that by your initial cash investment, and that percentage is your Cash-on-Cash Return. Nothing could be simpler.

Simplicity is a good part of CoC’s appeal. Unfortunately, that is also part of its weakness. If you are using this metric to help you decide whether a potential income-property purchase is a promising investment or not, then you need to look carefully at the story—or stories—that may lurk behind these numbers. In keeping with our literary metaphor, let’s call them our subplots.

Subplot #1: A Point in Time

Clearly, when you take the first-year’s cash flow and divide it by the cash used to purchase, you are looking at a property’s performance essentially at a point in time, a single year. To be sure, the reliability of your cash flow projection is likely to be greatest in that one, immediate time frame. I often hear investors say that they are not comfortable trying to predict the future, that they would rather just look at what is happening now; and they are quite justified in saying that if the return looks grim or perhaps negative right out of the box, then they have no interest in looking further.

Understandable, but potentially shortsighted—literally. By looking at a single year, you are looking at what may be an improbable investment horizon.  Will you keep this property for just one year? If not, if you plan to hold on to it longer, then you’re not taking into account anything having to do with its possible future performance.  Do you believe each future year will be exactly like this year, or could reasonably anticipated changes in cash flow (such as schedule increases in commercial lease rents, or large expenditures for needed repairs) push the needle far to one end or the other?

Subplot #2: The Time Value of Money

“All right,” you say, “then I’ll estimate the Cash-on-Cash Return for each of the next several years.” That may look like a step in the right direction, and I talk to a lot of folks who insist on doing just that, but it won’t take into account the time value of money.  You’ll be looking at the face value (undiscounted) of expected future cash flows, and weighing them against the present value of your cash investment today. Go back to that original example, where you invested \$100,000. If you predict a \$20,000 cash flow ten years from now, does that really mean your investment is returning 20%?

To be fair, future-year Cash-on-Cash can impart some useful information. For example, if the metric is both positive and increasing, then you can infer that your cash flow is improving each year. The trend can help inform your decision, but the actual percentage return may not have a great deal of meaning.

Subplot #3: Smoke and Mirrors

You retreat and say, “OK, let’s go back to thinking about just the first year of operation. Surely the Cash-on-Cash should give me a good sense of initial performance.” Do you remember the old computer chestnut, “Garbage in, garbage out?” Your results are only as good as the assumptions and data that you put in the dispose-all, and perhaps things aren’t always (or ever) what they seem.

Consider:

You are looking at in income-and-expense statement (what we call an APOD in real estate investing—Annual Property Operating Data) provided by the seller of the property. The cash flow is based, in part, on operating expenses, one of which is Maintenance and Repairs. The figure in the example above is \$6,000; you secure the owner’s tax return and confirm that this is indeed the figure he declared.

That is how much he actually spent, but the figure seems a bit low to you. Does it mean the owner performed as little maintenance as he could get away with and never fixed anything until it was absolutely necessary?  Perhaps the owner did this to prop up the property’s cash flow in anticipation of selling. Despite the fact that the expense disclosed is technically correct, you decide you shouldn’t use it as a forward-looking assumption. Instead, you will probably have to project spending more once you take ownership, resulting in a diminished cash flow and a lower Cash-on-Cash Return. In addition, the property may actually be worth less than you assumed, since it does not throw off as much net income as you were led to believe.

Now take a different point of view. Based on your experience, you think the maintenance and repair expenditure shown is surprisingly high. Could there be an explanation for that? Perhaps the owner used the past year to catch up on deferred maintenance so the property would look more presentable when he put it up for sale.  You might be tempted (but only in your most private thoughts) to test the impact of lower maintenance costs on your cash flow and CoC return.  Once again, the amount that was disclosed, although correct, may not be the amount that gives you the best estimate of future cash flow or Cash-on-Cash Return.

Subplot #4: The Forecast—Cloudy, with a Chance of Cash Flow

Finally, there is the larger issue of the structure of the cash flow statement itself. What you decide to include or exclude in your forecast of future cash flow will almost certainly be driven by your personal agenda in creating that cash flow statement.  Are you the seller of the property, looking to make its income stream appear as strong as possible? Are you the buyer, trying to make a realistic projection of how this property will really perform, and perhaps also conveying that stark realism back to the seller as part of your price negotiation?

In either case—as well as in any of several others, such as buyer looking for financing, general partner looking for equity investors, etc.—you might be putting a bit of a spin on the data, the better to support your point of view and the message you want to deliver.

If you’re the seller, then a bit of topspin seems like a good idea to you. In the example shown in Part 1 of this discussion, you might argue that, not only did you provide accurate and verifiable income and expense data, but that you were being exceptionally open and above-board by suggesting an allowance for vacancy and credit loss even though you experienced no such loss.  Group hug.

But if you’re the buyer, you might return this with some backspin. You thank the seller for being so forthright, but add that you believe the vacancy and credit loss allowance should be closer to 5%, not 3%. In addition, you point out that routine maintenance is great, but will not prevent big-ticket items from wearing out eventually. For example, the heating boiler is barely hanging on, and the flat roof has less than 10 years of life left in it. Hence you propose reconstructing the cash flow statement to reflect the higher vacancy allowance, as well as need for an immediate capital improvement and an ongoing set-aside of cash flow into a reserve account to deal with future replacements, such as the roof.

What previously was a robust 10.4% return now becomes an anemic 2.1%.

The seller objects that this isn’t entirely fair, since the boiler repair is a one-off event, and removing that cost would bring us up to 6.1%.

The seller’s argument cycles you right back to Subplot #1 about the hazards of relying on a rate-of-return metric that looks only at a point in time in what is probably going to be a long-term investment.

Is There a Bottom Line?

What should you conclude about Cash-on-Cash Return? Is it, as some contend, the only metric worth looking at?  Is it of no use at all? The best answer probably lies somewhere in between, that you need to recognize both CoC’s strengths and its limitations, and not rely on it as your sole investment decision-making tool.

On the plus side:

• It is quick and easy to calculate.
• It can give an immediate comparison to the return on other short-term investments.
• It focuses on the most current performance of the property; the more recent the data, the more likely it is to be reliable.

Among the negatives:

• It focuses on single point in time; you may be intending to buy and hold for an extended period, and the future performance of the property can differ greatly from the short term.
• It does not take into account the time value of money; if you use it beyond the current period, you may be comparing a future, undiscounted cash flow to the amount invested today.
• It is easy to manipulate the results; hence, a novice investor who relies on this metric alone can be misled by what a third party chooses to include or exclude from a property’s cash flow statement.

So are there some bottom-line recommendations here?  Of course.

Start off by trying to develop a CoC calculation in which you can have reasonable confidence.

To do so, remember that there is no substitute for due diligence. At the most basic level, you need to confirm whether the data you see on the cash flow statement for a particular property is reasonable and accurate. Then you need to go further and examine the physical property and the market to see if there are issues that may affect your confidence in those numbers. Is there any reason to doubt that the current revenue stream will continue as it is now? Is the demand for space in this market changing, for good or ill? Is there deferred maintenance that you will have to deal with? Based on what you find, you may have to reconstruct that cash flow statement.

Don’t just look at what is on the cash flow statement; look for what might be missing. A seller may not volunteer an allowance for vacancy or a need to fund a reserve account, but such items are going to be part of your reality as an owner.

So long as you approach it with sufficient care and due diligence, the Cash-on-Cash Return can give you a useful first look at how a property might perform; but before you commit your investment dollars, you need to do more.

If you plan to operate this property for several years, then you need to take the long view. You should identify your likely investment horizon, and then build a series of pro formas to forecast how the property might perform over time.

A series? Yes. Don’t try to nail your projections of future performance in one pass. Do a best-case, worst-case, and in-between forecast of future cash flows and ultimate resale of the property. Look at the ongoing Debt Coverage Ratio in each case. Examine the IRR or MIRR. Even compare this property to others you might be able to acquire.

Be thorough. Be wary of shortcuts. You’re buying a future income stream; do your homework and run your numbers so you can understand just what it is that you’re buying.  Your investment success depends on it.