Entering into a commercial real estate investment is a significant long-term investment, and reaching a valuation you are comfortable with is a challenge. Real Estate is an emotional investment as well, for all but the most hard-nosed investor. You've probably asked yourself at some point whether you’ve allowed your emotions to get the better of the hard facts.
Allocating a few hundred dollars to buying data is a great risk reduction strategy in this regard, and nowadays you can get great bang for the buck. There are many reasonably-priced sources of data available in the market today that can help keep you honest. At dmi.io we've been scouring the landscape of data providers and building tools to help you find data quickly and easily. In this blog I break down the valuation challenge into actionable steps you can take with data. You can view all of these through the dmi Data Explorer.
The real estate valuation model is simple in concept - develop a picture of the future income streams and costs from the CRE opportunity, and using your preferred valuation technique arrive at a potential valuation. Deduct any renovation costs after acquisition from the valuation and you are left with the maximium amount you should spend to achieve your desired return.
The real test of quality for your model is the degree to which your data inputs reflect reality. If your assumptions are too conservative you may leave good opportunities on the table. If you are too aggressive, you’ll be overexposed to the downside. Questions you may be asking yourself are:
- How do I find appropriate data for my specific situation?
- How do I estimate income and costs for my real estate opportunity?
- How do I estimate income and cost growth in future years?
- What discount rates or cap rates should I use for my valuation?
Let's dig into each of these areas and look at the options available to you.
Finding the right data - understanding your hyper-local market
Before we even start populating a financial model, gathering information on the local context of your investment opportunity is one of the most important steps you can take. Financial assumptions without this context are little better than guesswork. By local I don't just mean zip code, but location information down to the individual street location. With this data, you will have a framework against which you can assess your data assumptions.
This context also needs to be viewed over time - what is the current environment, how did this develop, and what is the expected future trajectory? I've grouped this contextual information into two buckets:
Neighborhood stability is critical to a sustainable growing rental income stream. Issues you want to consider include:
- socio-economic profiles
- town level commitment to growth and investment
- facilities and amenities - school quality, neighborhood quality, transportation
- crime statistics
Specific location desirability
- foot traffic and car traffic
- ease and safety of access
- parking availability and quality
- quality of other properties in the area
- proximity of anchor tenants for office / retail opportunities
There's plenty of sources for this sort of intelligence. On the free data side, you can explore data.gov resources such as census results. Sites like city-data.com provide a free snapshot of a particular community but remember that there is limited historical context to the data. The knowledge and experience of your realtor is another valuable resource (though remember many realtor opinions are grounded in instinct not data, and they have a conflict of interest.).
If you want to save time and access a richer set of data the commercial data vendors can provide this, often at reasonable cost. The dmi Data Explorer provides some examples of data providers for the above areas and you can search their listings and examine their pricing. For example, select Demographic Data and filter on Commercial Real Estate, Lifestyle Preference or Property Location to find targeted data that can meet your needs.
How to forecast rental cash flow
Rental cash flow is the key income figure in a valuation, but there are many considerations that go into it. Here are some questions to consider:
- How much ‘headline’ rent should I charge?
- Do I need to offer a rent free period?
- What is the average tenant improvement allowance?
- What is a good vacancy rate assumption?
- What type of commercial lease is appropriate?
'Marking to market' is the way to address these questions, but reliable lease comparables data is difficult to source without spending some money. With significant personal time investment, it's possible to build up a picture of asking rents in your area from various listings sites. Provided there is a reasonable volume of lease activity in properties of similar use and location, this can provide an indication of the ceiling on the rent opportunity. However the net effective rent can be substantially lower by the time a negotiation is concluded, with credits for free periods and enhancements eating away at that headline figure, in addition to any negotiated rate reductions. It's that net effective rent that you need to arrive at - anything less than that you should treat with caution.
Money invested in sourcing some data to support these assumptions is well spent. A number of vendors have developed some good quality data covering many of these components of net effective rent. In dmi Data Explorer search for datatype ‘Price Data’ and narrow down your options to Commercial Real Estate and Tenants.
Operating cost assumptions
The most significant operating costs for a commercial building are typically local taxes, utilities and property management charges. You have little to no direct control over these costs and their growth. Your best option is to build confidence in the quality of how these have been managed historically, and use that as a basis for creating a high and low scenario for future cost growth.
- who are the utility providers and what is their historic cost growth picture?
- how well does the local taxing authority manage its budget and what are the trends in taxes and mill rates?
The local context we have already built helps a lot in this step. Towns and cities experiencing positive growth in living standards and desirability are probably investing in schools and infrastructure locally to make them attractive. That’s good news for your income opportunity, but a risk to your tax bill. Conversely areas suffering significant socio-economic change and pressure on household incomes may have less opportunity to invest in upgrading and improving the neighborhood. Taxes may stay low but don't bank on a socio-economic lift that will drive additional business to your commercial opportunity.
A number of data vendors provide insight into these costs. Some also provide limited access to a free subset of data which may meet your need for tax information. This data combined with a review of news and events related to these topics over the last five years should build a sufficiently rich picture to allow you to put in a sensible range of cost growth assumptions. For example search for ‘Tax and Legal Records Data’ in Data Explorer, and filter on ‘Property Tax’.
Maintenance, insurance and repairs are other important cost lines in your analysis. These costs are very location specific and often tied to the actual condition of the property. However there are a number of data vendors providing benchmark data that help you form an initial basis for cost expectations (look in Data Explorer for ‘Financial Data’). To get more specific talk with your broker, understand the likely costs for the particular property, and test any provided information from the seller for accuracy and completeness.
The local context we discussed earlier will help you assess risks, crime and safety. These can all impact insurance in particular.
Property improvement costs
Property improvement costs are often the single biggest variable and risk in your model. If improvements are a major part of the plan, take advantage of the various construction cost benchmark providers and unit cost estimators to help you form a view of the likely range of investment. You can triangulate these costs against estimates you get from contractors for the actual proposed work, as a safeguard against lowball estimates. Estimates also reflect only what is visible to the contractor, and these third party data sources allow you to construct a range of potential investments for best to worst case scenarios.
List the assumptions you are making regarding investment improvements and then review them with a skeptical eye. Are you assuming only superficial work to electrical and plumbing installations. Is the roof good enough, needing minor repairs rather than replacement? Work out what you need to do to support those major assumptions with data or your physical due diligence.
Search Data Explorer for ‘Financial Data’ and filter on the ‘Construction’ topic to get relevant listings.
Equity and debt investors
Financing your CRE project will involve a mixture of equity and debt and a search on Data Explorer for 'Financing Data' will uncover potential pools of investors and lenders. Filter on topics like ‘Commercial Real Estate’ and ‘Multifamily’ to find relevant listings. If you are looking to share risk in your investment, a number of data providers have details on potential investors searchable on key attributes related to the opportunity.
Borrowing costs are a key element of your final cost structure, and highly specific to both you and the specific opportunity. A lender will be assessing your credit worthiness, as well as a number of property specific factors including loan to value, appraised value, and expected cash flows. At the modeling stage your best approach is to identify the low and high range of expected financing that meets your particular criteria. Leverage your existing relationships with your lenders to get insight into rates and term structures. There are also plenty of freely available sources of data on the web such as this site which shows financing rates for different loan structures and terms. Use these sorts of sources as a starting point but remember that publicly published rates are the best rates on offer and are part of a lender’s marketing strategy. Add some basis points to the rates shown to provide some cushion in the event you don’t achieve such a rate.
Modeling your valuation
Fundamentally, a valuation involves applying a discount rate to the future net operating cash flows of the opportunity. This may be an industry specific approach such as applying a cap rate to the current NOI's of the opportunity, or identifying an appropriate discount rate to apply to a detailed ten year cashflow. If you have gone to the trouble of building a detailed line by line income and cost model, I'd recommend justifying that work with a full DCF calculation and identify. You'll need to use a discount rate that reflects the additional return you you are seeking over the risk free rate. This will provide you with a more accurate benchmark against the broader market of investment opportunities.
The CRE investor applying a cap rate to current NOI's will be mentally ticking off those assumptions on income and costs even if it isn't written down in a model - the cap rate approach is of course just a short cut for valuing a constant annuity stream of NOI's discounted at the cap rate.
There's sources of cap rate data available from various vendors which you will find under 'Financing Data' in Data Explorer. If you find they are too expensive to acquire or inappropriate to your situation, ask your broker to provide some information. You can browse listings for asking cap rates but take them with a pinch of salt - after all these are sales listings, not audited accounts.
The Real Estate Capital Institute also provides some great free material such as this posting showing cap rates by property type over time. It is a summary of a broad set of data but it’s another data point to let you triangulate against other sources to see if your expectations on cap rates and discount rates are reasonable.
I'll be providing access to our commercial property valuation calculator in another posting soon.
Bringing it all together - scenario analysis
Having built a data-grounded picture of income and expenses, and identified a range of acceptable rates of return for valuation purposes, we can arrive at a base case valuation. The only thing we actually know about this base case, is that it’s highly likely not to materialize in practice!
Running a set of scenarios around the base case is a great way to build a visualization of how this opportunity sits in terms of risk / reward. Flex your key assumptions across the range of best to worst case outcomes and run the valuation for each one. If your scenario analysis shows a greater number of attractive outcomes compared to the bad scenarios across a range of reasonable assumptions, you're making good progress. For the extreme outcomes (both positive and negative) and the tipping point outcome (ie the boundary at which you would switch from a 'yes' to a 'no'), look especially closely at those scenarios. What would have to be true for those outcomes to materialize. Does that still make sense within that rich context you have built up?
Creating scenarios doesn't have to be a case of 10,000 Monte Carlo simulations across your model - even a simple model which tweaks five or six key variables between a low / medium / high set of options brings the story alive. I'll share my valuation model in another post as an example of this.
No free lunches
Investment markets are pretty efficient today, and although real estate is a little less so if you are looking at something that seems like an unbelievable opportunity, keep that skeptical eye focused on the opportunity. Unless you know you have preferential access to a deal or have found an angle that you believe others have missed, you are unlikely to achieve a significant excess return to the market. If a seller is to sell at that return, you are probably missing some costs, or taking on a major undisclosed risk. The truly sweet deals likely never hit the public listings.
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