These Two Techniques May Help You Avoid Gambling with Your Financial Future

How certain are you that you’ll achieve your crucial financial goals? Even if you’ve had the most basic experience preparing for the long-term, you likely know that having the right financial target in mind for retirement, financial independence, or a big-ticket purchase is vital to a successful planning outcome. But did you know that basing your financial allocation decisions on a static, unchanging view of the world might leave you gambling with your financial future?

Indeed, understanding how your financial target may rise or fall based on shifting financial and economic conditions or varying lifestyle preferences is vital to the success of achieving your long-term goals. So, how can you sift through these varying factors and identify the right savings target for you? That’s where two techniques — scenario analysis and Monte Carlo simulations — play critical roles. Rather than coming up with one fixed solution, you can use these tools to choose from a host of possible outcomes, enabling you to make more informed planning decisions and likely increase your chances of success as you prepare for the future.

Scenario Analysis: Evaluating Tradeoffs

A savings discipline, a modest rate of return, and time can help you achieve your financial goals. Simple enough, right? Well, how can you be sure that you’re not saving enough (or too much) if your financial needs rise or fall in the future? What if your financial priorities change? And how can you be sure that your assumed modest rate of return will help you reach your savings goal? Incorporating scenario analysis and Monte Carlo simulations into your financial planning process can help you tackle these and similar questions. Let’s take a look at each in a little more detail.

A scenario analysis acknowledges that no one perfect answer exists to fulfill a given set of desired planning outcomes. Indeed, identifying one result to meet your financial goals would be the most straightforward approach. Even so, every savings decision will have its own unique set of costs and benefits. An example here may help illustrate this point.

Assume that you can save $25,000 per year. Maybe you’d like to use this money to pay down your $500,000 mortgage, but you’d also like to accumulate $500,000 for a big-ticket purchase in 20 years. We can evaluate the tradeoffs between paying down the mortgage and building up savings from a scenario analysis approach. So, should you pay down the mortgage first or concentrate your efforts on investing your savings? Let’s take a look at what would happen if you paid down your mortgage first.

Scenario Analysis Example

Assuming that you have 30 years left on your mortgage and you use all of your annual $25,000 savings to make additional principal payments, you might be able to pay off your mortgage in 12 years and reduce your lifetime mortgage interest by $230,000. With your house paid off in 12 years, you could then apply what would have been regular mortgage payments to your extra savings. Invested over 8 years with a 5% return, your savings could grow to $529,000. So far, so good, right? Now let’s consider an alternative.

What would this situation look like if you invested $25,000 over 20 years instead of waiting to pay off your mortgage? Assuming that you achieved your investment return rate consistently over this period, you’d likely have accumulated $826,000 for your big-ticket purchase. Even if we consider the opportunity cost associated with mortgage interest savings, your savings’ end value is notably higher than in the first scenario. Here, you could surmise that you’d be better off investing your savings from the start. Such a conclusion, however, misses a crucial point.

While building savings is vital, paying down your mortgage as you move toward financial independence might still be an essential lifestyle value to consider when allocating your financial resources. Is there a way to have the best of both worlds? One compromise between the two alternatives is to apply half your savings toward investing and the other toward paying down your mortgage. What’s the result? Well, at the end of 20 years, not only have you paid off your mortgage, but you’re likely to have also accumulated $552,000 for your big-ticket purchase.

These three situations illustrate how scenario analysis can help you evaluate tradeoffs between two or more competing financial priorities. This iterative process is extremely useful in assessing the cost and benefit of selecting an ideal outcome to come up with an optimal solution for prioritizing your financial resources. Even so, one crucial factor to consider is that your simple growth rate may not account for market volatility. To address such uncertainties, you’ll likely want to incorporate Monte Carlo simulations into your process to ensure that your plan stays on the right track.

Monte Carlo Simulations: Evaluating Risks

So, what exactly is a Monte Carlo simulation? Simply put, it’s a statistical technique that may enable you to calculate the risks associated with achieving specific financial outcomes. In other words, it’s a way to quantify the unknown.

Earlier, we showed several scenarios in which you might grow $25,000 to $500,000 in 20 years using a 5% return rate. But how certain can you be that you’ll receive precisely 5% per year, mainly if your return is based on investing in financial markets that vary in performance from one year to the next? In other words, how can you ensure that you’re saving the right amount to account for a potential savings shortfall in any given year? Monte Carlo simulations can help.

Indeed, a Monte Carlo simulation is a computer model that, given a set of assumptions — like risk and return — produces thousands of random return observations within the parameters specified. The process not only tells you what might happen, but it also gives you a way of quantifying the likelihood of your desired outcome. Let’s demonstrate how this works with our previous mortgage payoff, big-ticket purchase example.

Monte Carlo in Practice

You’ll recall that the three scenarios aimed to answer how to apply annual savings of $25,000 best: 1) pay off your mortgage first, then invest 2) invest all of your savings from the start or 3) a 50/50 split between mortgage payoff and investment savings. Each of these outcomes exceeded the $500,000 threshold we set for a big-ticket purchase through investment growth. Even so, what’s the probability that each of these outcomes will occur?

In the first scenario, while savings are projected to grow to $529,000, our Monte Carlo simulations tell us that there’s only a 60% chance that your savings will be higher than your $500,000 threshold. How so? It all comes down to volatility. In fact, over a third of the 10,000 simulated investment portfolios fall short of this goal, ranging in value between $400,000 to $500,000. How did the other two portfolios perform?

In the third scenario, an even split of savings between mortgage payoff and investment savings over 20 years led to only a marginally higher probability of meeting or exceeding the savings benchmark. However, the Monte Carlo simulations for the second scenario, where we committed all savings to investments, showed a 95% likelihood of achieving or exceeding the $500,000 savings threshold. While a positive solution, you have to consider a critical point: is this the most optimal outcome? Put differently, the mortgage still hasn’t been paid off. Let’s see how the combination of scenario analysis and Monte Carlo simulations can help.

Optimal Outcome: Combined Monte Carlo Analysis

Each of the three scenarios discussed has its benefits and drawbacks. Pay off a mortgage sooner and accept a lower likelihood of achieving your savings goal, or up your savings goal and pay off your debt as scheduled. Let’s consider a fourth alternative: optimize. Here, our goal is to optimize cash flows to find a balance between paying down your mortgage and accumulating savings with a higher success rate of reaching its threshold. How exactly?

First, we ask the Monte Carlo simulation to identify a value that meets or exceeds our threshold with an 80% certainty level. After another 10,000 iterations, the software tells us that the target value should be $661,000. When we run this figure through our scenario analysis again, we find that the split between saving and debt payoff changes to 80/20 from 50/50 savings vs. mortgage payments in scenario 3. And while you won’t pay off your mortgage in 12 years as in scenario 1, this new outcome may shave seven years off of your payments and save you about $90,000 in lifetime mortgage interest expenses.

At this point, you might be asking yourself, why not go for 100% certainty that you’ll achieve the $500,000 threshold? Remember, your goal here is to achieve an “optimal”, not “maximum” outcome. Increasing your probability might lead to saving more money than you need.

To be sure, Monte Carlo simulations aim to help you evaluate the tradeoff between how much risk you’re willing to take to achieve to reach a given effect.

Considering all four scenarios, the analysis as a whole tells us that if you’re willing to accept that the probability of your big-ticket savings outcome is somewhere around 80%, you could allocate more savings while still eliminating your debt sooner. At the end of the day, it really comes down to evaluating which tradeoffs are more important to you.

Are You Gambling with Your Financial Future?

The Monte Carlo method gets its name from a popular casino in Monaco. The irony of its name is that this technique can actually help you increase your odds of financial success when paired with a concrete scenario analysis framework.

Indeed, if you have two or more financial objectives that you’re trying to evaluate then using a Monte Carlo Analysis is one way to help you find an optimal balance between your lifestyle needs and financial goals. More importantly, however, if you’re not using a disciplined, quantitatively-based process to assess the likelihood of reaching your financial goals, then you might be gambling with your financial future.