RevPARTY has recently introduced a new component to its financial projection modeling for property underwriting that is a game changer for any company evaluating the risk involved in a new property or looking to benchmark their property’s performance against expectations. RevPARTY’s Monte Carlo Simulation now provides value to companies that other products simply cannot. Rather than just spitting out a number, RevPARTY’s Monte Carlo Simulation provides a range of possibilities and the probability that each outcome will occur. As opposed to relying on assumptions that may be too aggressive or too conservative and ignoring interconnected components of a model, now its possible to accurately asses risk in a variety of future possibilities and make better decisions now. RevPARTY’s Monte Carlo Simulation allows property managers and property owners to better understand ROI, evaluate best and worst case scenarios, avoid potential mistakes, and act on better opportunities.
What Is A Monte Carlo Simulation?
Monte Carlo Simulations are algorithmic models that rely on random sampling to produce a range of results. The repeated iterations of the same model with different randomized inputs produces a range of outcomes as opposed to a single, deterministic, expected value.
For example, we know that if we flip a fair coin four times its expected that (or the most probable outcome is that) two times the coin will land on heads and two times the coin will land on tails. However, we also know that this won’t happen every time. A deterministic model, like standard property underwriting, would only output the expected result of two heads and two tails. A Monte Carlo Simulation would simulate the four coin flips thousands of times and show the range of possibilities: how likely it is that heads or tails appears only once, how often can we expect the result to be all heads, and so on.
This sort of analysis adds value when different results have different consequences. For instance, if the above example is a fair game and a you when the coin lands on heads you might expect to break even … but you would also want to know how often you will lose money; or even further, how often will you lose all your money. This sort of risk assessment becomes even more valuable when a company is deciding between multiple opportunities or have different appetites for risk. Applying this to vacation rentals and hotels is especially important with how many variables affect each other and drastically alter profitability from one scenario to the next.
Monte Carlo Simulations are especially helpful when random variables follow some type of distribution or range (like a normal distribution), when multiple random variables interact (how ADR and occupancy combined determine revenue or how occupancy directly drives housekeeping fees), previous static states effect future states (as is the case when one month’s bookings and reviews influence the next month’s bookings), or when multiple variables are random but correlated (such as how ADR and occupancy have a negative correlation to one another but also share a positive correlation to market RevPAR). All considered, Monte Carlo Simulations are the perfect fit for property underwriting and vacation rental financial projections!
How Does It Benefit Property Financial Projections?
First, a Monte Carlo Simulation more accurately predicts outcomes when a scenario depends on sequential states. This is why it’s often used in planning project schedules, but it also applies to vacation rental underwriting and hotel underwriting. When the success of one month is dependent on the success of the previous months, this causes a ripple effect through the remainder of the projection and a Monte Carlo Simulation more accurately accounts for the randomness of when these events will happen.
A great example of this is the number and quality of reviews on a property’s listing. The quality and number of reviews largely influence the total bookings a listing receives through both occupancy and rate. The more reviews and the better the reviews the easier it is to get bookings; and thus, the easier it is to get even more reviews. While we could estimate the number of reviews during a certain time period there is some randomness as to when exactly that will actually occur. If these bookings and reviews occur earlier than expected, then the following months will likely see revenue results better than projected; but these bookings and reviews could also happen later than planned and have a negative impact on the months to follow. Monte Carlo Simulation allows anyone to play out both scenarios and have the distribution of risk, including the second order effects later in the timeline, displayed in the model outputs.
Second, a Monte Carlo Simulation more accurately models the outcomes of binary events like legal reform or exogenous market shocks. In a normal underwriting model, one would have to model the effect of new laws effecting short term rentals as a risk discount or maybe as two different scenarios (one where the law passes and one where the law fails). However, with a Monte Carlo Simulation we can aggregate both of these scenarios into the same output and it is represented in the range of outcomes. It also allows a business to model the effects of not only IF the law passes, but WHEN the law passes. This leads to a much more realistic range of outcomes and a more accurate reflection of risk.
Third, the simulation more accurately models the range of possibilities and variability which also means it can more accurately model the effects of portfolio size. Everyone remembers the “law of large numbers” and its always at work in the hospitality industry. The same reason that hotels can more easily revenue manage is the same force that causes huge financial swings in vacation rentals, sample size and variability.
For every unit, every night, there are only two possible outcomes that couldn’t be more different: booked and empty. Its 0% or 100% occupancy. Its part of the difficulty with data for vacation rentals. However, with ten units there are now possible occupancies of 0%, 10%, 20%, 30%, etc. Moreover, the increased sample size will cut the outcome variability by more than half. A larger portfolio has less variation and outcomes are easier to predict. Without a probability driven model (i.e., standard underwriting) a portfolio with identical units would always yield the same results regardless of portfolio size. One unit is the same as 100 units. However, with a Monte Carlo Simulation portfolio size, and its increased or decreased risk, is represented in the model outcomes and paints a more accurate picture for any property manager. It directly enables the modeling of scale and diversification.
How Would I Use It?
RevPARTY’s Monte Carlo Simulation is the best tool for property evaluation; whether that’s underwriting a property not currently in one’s portfolio or trying to successfully forecast financials and benchmark performance. The model accounts for the most variables and generates the most reliable outcomes. The repetitive modeling directly tackles many of the data obstacles vacation rentals face. While it can do everything a standard underwriting or forecast model can do, a Monte Carlo Simulation adds the most value by providing solutions in these instances:
Investment Opportunity:
- When expected value isn’t enough and a fuller picture of probable outcomes and risk is needed
- When the number of units and the subsequent price is being negotiated but needs to be weighed against the benefits of having an additional unit
- When there is a possible exogenous shock (like policy, enforcement, development, market trend, etc.) at some point during the underwriting period
- When trying to obtain financing (especially if trying to demonstrate a low risk of default)
- When trying to make the best decisions for portfolio selection
Target Setting:
- To show not just how much a property over/under preformed compared to the target, but to quantify how much the property did so taking everything into account and not just a single metric
- When setting more accurate targets with a confidence interval
- When trying to attribute outcomes to or determine the effects of underlying causes (occ, ADR, market performance, a shock, etc.) or trying to drive organizational accountability
Where Can I Get This For My Business?
RevPARTY is thrilled to offer Underwriting with a Monte Carlo Simulation model to all of our clients seeking to underwrite future deals or create targets for future performance. We remove a lot of the leg work and lead time out of the process by developing our model with several clients to standardly incorporate all possible inputs and outputs saving you time and money. Moreover, we customize each simulation to answer the questions your company needs to be successful.
With a model developed by industry experts, tested in the field repeatedly with clients, and analytic sophistication that includes 10,000 simulations you can rest assured that RevPARTY will help you make the best decision possible.