Data Driven Decision Making Under Constraints In Real Estate
Constrained Decision Environments
Decision making is almost never an easy play.
Neither are all the informations needed available, nor are all of the possible options weighted and evaluated in order to get a well balanced decision with all the risks and perspectives taken into proper account.
Decision making is always a decision making under certain constraints. And those decision frameworks are even worsened when facing huge amounts of capital to be committed with an asset in a market with lower fungibility.
The alternative investment segment and here especially real estate is one of those markets which confronts decision makers with situations of a very constrained nature.
In this article, we talk about one of the major restraints in the real estate business: time respectively timing — and how a data driven approach can lift some of the burdens.
Real Estate Investments
In most of the cases, investment into real estate assets is done to earn money which can be expressed in terms of e.g. equity yield.
Equity yield mainly depends on the equity capital invested in an asset, the market yield for the asset class in question at the time of selling and — the period of time the equity stayed invested in this asset.
In other words, the longer an investment is kept the more you have to earn in order to keep up with the same level of equity yield.
Besides, there are all sorts of investor types in this industry.
The scope of investors runs from those which are jumping into a market with tiny fragments of equity (compared to the overall investment), an ultra-short investment perspective and the hope that the market yields are depreciating fast enough to exit the asset with a nice profit. This is the highly speculative end of the rope.
On the other side of the spectrum is the really longterm oriented investor which draws in a significant portion of equity, which is not impressed by cyclical price behaviours, collects the running cash-income during the lifetime of the investment and has the big investment picture in mind (which can even outlive a working generation).
Maybe this is not so crucial for this ultra-longterm investor, but for all the other investors the time aspect of an investment and with this the timing of an investment — including the timing of the exit of this very investment — is of essence.
Relieving Constraints
Here is an example how the time frame affects the equity yield:
In order to get the best deal for his/ her money, an investor has to find the best investment term based on the investor’s risk profile. Problem is that the exit scenario rests upon assumptions about future market situations.
How do you know that an exit price of 100 can be achieved in 3 years time? How do you know that this might still be the case in 5 years time?
This is just one parameter to be taken care of. A lot of other parameters are impacting an investment. Issue is that those exit parameters are unsure in their nature as future developments are concerned. That is why this poses restraints on the decision maker’s ability to choose his/ her best options.
One way of dealing with this decision making under uncertainty is to simulate potential investment scenarios grounded on respective market patterns and weighted by their probability of materialising.
Advanced predictive analytical models are stepping in here!
Those methods are here to support the decision maker in relieving some of the constraints. Two main considerations in this context:
- Dealing with different potential market scenarios and weighting them by means of chances to get materialised. In other terms, what is the most probable scenario an investor might face at the end of an investment term.
- Taking into account the term of the investment in itself, i.e. evaluating how the risk profile of an investment changes over the period of time.
This second aspect is extremely important as it constantly monitors the risk/ opportunity profile of an investment (or a portfolio to stay with the broader picture) and gives the decision maker a hand to be capable of reacting in due time.
Change of Risk Profile during Lifetime of an Investment
As soon as the key parameters of an investment are fixed, an investor naturally is exposed to the further development of the respective real estate market.
Question is what can be expected from the market in the future and how does this impact the performance of the investment (or portfolio). More important, how do these risk/ performance profiles change over time and are there windows of higher opportunity respectively are there periods of significantly increased risk
Those are in fact topics, decision makers have to react upon — the earlier this is possible the more room for manoeuvre stays in place.
The graph below shows the possible development of the equity yield of an investment over a period of time grounded on simulated market developments while the frame of the investment itself remains unchanged (red … loss area, blue … profit area):
It seems obvious that this investment does not count for short term considerations as the probability of making a loss in the early years is so much higher than in later years (leaving the question to invest at all).
This is also confirmed by the median value of the equity yield per each of the time scenarios as well as the chances to earn an equity yield of, let’s say, more than 5 % p.a. See the table below:
And this would be the moment to consider if the ideal investment term as shown here does fit to the overall strategy/ risk profile of the investing entity.
The result, of course, is not static as the market further develops and market patterns also might change over time. This is the trigger point of a regular monitoring of the investment respectively the overall portfolio in order to keep the ideal time frame (e.g. investment time, exit time) in mind and to be able to react in due time.
Conclusion
Incorporating the time frame and the timing into the risk/ performance metrics of an investment or a portfolio enhances the possibilities for decision makers to act under uncertain conditions.
And it does not end with equity yields. The combination of different risk modules, like short term liquidity considerations, covenant breach issues with debt financing partners and similar, can make the difference in deciding under constrained environments.
By the way, transparency in the decision making process comes as a side effect.
Another important point is that sometimes investment companies are bound to certain deadlines within their investments. Example could be that the loan granted for the investment ends its term, corporate bonds have to be repaid with a fixed deadline, or the term of an investment fund ends breaking the path to a fixed exit time line.
In all those scenarios, it is very helpful to know what could be the most probable scenario at the respective deadline and to start to prepare for it in due time.
Given that fact that those helping tools can be delivered on an automated basis is definitely another pro — argument for advanced predictive analytic methods to be incorporated in an up-to-date risk management system.
