Will You Have Enough Money in Retirement?
Articles abound with the claim that – if you save $100 a month, earning 10 percent per year, you will have a given sum of money in 30 years. These simplistic future-value exercises (also known as deterministic calculations) are helpful in explaining the potent effect of compound interest and encouraging investors to start saving early; after all, it was Einstein who once said, “the most powerful force in the universe is compound interest.” The problem with such deterministic calculations is that they assume the average annual earnings will remain constant throughout the investment period – in other words, investments will always have positive returns. If we have learned anything these past few years, it is that stock markets do not always earn positive returns each year, and that returns can be volatile. Until recently, most financial advisors used deterministic calculations to forecast future portfolio values; however, such calculations fail to answer the most crucial questions on an investor’s mind: Will I have enough money to retire? What if I run out of money? Am I saving enough to reach my goals? — Each of these questions are valid and should not be discounted when developing an investment portfolio. After all, you hire a financial advisor to help you answer these exact questions. Therefore, in recent years, financial advisors have shifted away from using deterministic calculations and toward Monte Carlo simulations to be able to answer the aforementioned questions with a greater level of confidence.
Monte Carlo simulation is a robust algorithm used by financial advisors to estimate an investor’s probability of meeting his/her financial goals. Instead of using a single future value based on deterministic calculations, Monte Carlo simulation calculates your portfolio value under thousands of random scenarios that may affect portfolio value, and then takes the average of those scenarios to determine a probability of success. It provides information about the range of possible outcomes and the likelihood that each outcome will occur. For many years, financial advisors were limited to deterministic calculations mainly because the computing power was not available in most commercial investment software. Now with more advanced planning software available, more advisors are using Monte Carlo simulation methods to make better informed investment decisions. Monte Carlo simulations are widely used and relied upon across many industries beyond finance. In fact, it was used to develop the hydrogen bomb; it was used by NASA to determine how the Ares I rocket launch vehicle would behave in flight; and is used in nearly every analysis involving risk management. Because of its reasonably reliable outcomes, financial advisors who accurately use and interpret Monte Carlo results can add tremendous value to their clients.
To illustrate how Monte Carlo simulation models work, assume that the far left column in the chart below is your current age, and the first row is how much money you plan to save each year until retirement. Assume further that your current portfolio is worth $25,000, you plan to retire at 65, and your estimated total expenses will be approximately $50,000 a year for 30 years of retirement. What is the probability that you have enough money during retirement and reach your financial goals?
|Additions to Savings Each Year (current portfolio value is $25,000)|
If you are curious to know whether your current savings will last during retirement, use the chart above to find your approximate age and annual savings. For example, if you are currently 45 years old and save $15,000 a year to your $25,000 portfolio, you have a less than 40 percent chance of being able to retire at 65 and live off $50,000 a year. To increase your chance to 88 percent, you would need to save $20,000 each year to meet your goals. Keep in mind that if your current portfolio value is greater than $25,000, then your probability of success will be higher or vice versa.
All financial models, no matter how robust, are subject to limitations, including Monte Carlo simulation. The biggest limitation of Monte Carlo models is the use of historical data to predict future portfolio values. While we can never accurately and consistently predict future investment returns, using historical returns and patterns allow us to gain some understanding of investment returns. Users of Monte Carlo simulation models must fully understand its application, know how to accurately enter data, and most importantly, appropriately interpret results. Despite its limitations, we cannot underestimate the powerful capabilities of using Monte Carlo simulation. Do not rely on simple future value calculations to predict your financial success; seek a trusted financial advisor who uses and understands Monte Carlo simulation techniques to prepare your comprehensive financial plan to increase your chances of reaching your financial goals. You should never have to wonder, “Will I run out of money?”
Ara Oghoorian, CFA, CFP® is the president and founder of ACap Asset Management, Inc., a “Fee-Only” investment management firm specializing in working with medical professionals. Contact Ara at firstname.lastname@example.org or on the web at www.acapam.com for a complimentary consultation.