Recently, one of us (Maria) was at a bank trying to set up a small custodial IRA on behalf of a nephew and was told that “a minor can’t have an IRA.” It was an interesting experience, and one we think may be common. While an IRA may not make for an exciting birthday present for a teenager, it’s a good way to start investing at an early age. The conversation occurred about the same time we were working on our IRA Insights piece Now is the time to graduate to an IRA, and our research found that young investors, who have the most to gain from making a contribution, are contributing at a lower rate than their older counterparts.
According to our projections*, a 20-year-old investor who begins saving $200 per month in a Roth IRA, invested in a portfolio of 80% stocks and 20% bonds, would have about a 55% chance to accumulate over $1 million by age 65. On the other hand, if a 30-year-old investor follows the same program, the likelihood of being a millionaire drops to 14%.
The reason for this dramatic difference is that young investors have the opportunity to take advantage of compounding—the process where investments make returns, and those returns make returns, and so on. The more time you have, the more “so on’s” you can add to that sentence, and the bigger and bigger the potential returns get. The graph below shows how the wealth curve really begins to bend up as time goes on (using the same example as above)—especially as you get to 40 years and beyond. In our example, it takes 35 years for the median investor to get to half a million dollars. Then just 10 years for the next half-million. Then just 8 years to tack on another million.
Median projected value for an IRA with a $200 monthly contribution*
Don’t let these excuses keep your young investor from getting started:
- “There‘s plenty of time.” Well, maybe. But as we showed above, the time you have will never be more valuable than the time you have now. The fact that there is “plenty of time” is exactly the reason you should be investing now, instead of waiting for the future. Every dollar you invest now is a down payment on life options down the line.
- “I‘m too young.“ Anyone with earned income can open a Roth IRA. That includes minors with a summer job (contrary to that bank teller’s questioning). At the extreme, some people even open IRAs for infants who have modeling income. The youngest IRA owner at Vanguard is less than one year old.
- “I don‘t have the money.“ Perhaps you need every cent of income from your summer job to pay for college expenses. But every dollar matters—the example we used above was based on $50 per week. Windfalls like a tax refund or cash gifts from aunts, uncles, and grandparents are great sources of money for contributions. And some parents will even choose to match contributions that their children invest for the future rather than spend. Perhaps such an arrangement can work for you.
- “I don‘t want to tie that money up where I can‘t get it. I might need it for an emergency.“ One good thing about choosing a Roth IRA is that the contributions that you make (although not the earnings) can be withdrawn at any time, for any reason. While we wouldn’t recommend using a Roth IRA as a place to store short-term savings, the money can be used in a pinch, and in the meantime you’ll be generating earnings that can continue to compound.
- “I already have a 401(k).“ If you just got your first job with a company that offers a 401(k), congratulations! However, once you get past contributions that are matched by your employer, you might still want to consider a Roth IRA for saving additional money. This is especially true if your employer’s plan is filled with high-cost investment options, or if they don’t offer a Roth option for your 401(k) contributions. Later in life, you may be grateful for having “tax-diversified” with money in different kinds of accounts.
$1 millon sounds like a lot—and it is. But if you get started early, you may be surprised at how attainable it is.
*All results are in nominal dollars (not inflation-adjusted) and based on a portfolio invested in 80% U.S. stocks and 20% U.S. bonds. Median projected balances and other results generated by the Vanguard Capital Markets Model® regarding the likelihood of various investment outcomes are hypothetical in nature, do not reflect actual investment results, and are not guarantees of future results. VCMM results will vary with each use and over time. The VCMM projections are based on a statistical analysis of historical data. The asset-return distributions shown in this paper are drawn from 10,000 VCMM simulations based on market data and other information available as of December 30, 2013. Future returns may behave differently from the historical patterns captured in the VCMM. More important, the VCMM may be underestimating extreme negative scenarios unobserved in the historical period on which the model estimation is based.
Notes: All investing is subject to risk, including possible loss of principal.
Withdrawals from a Roth IRA are tax free if you are over age 59 1/2 and have held the account for at least five years; withdrawals taken prior to age 59-1/2 or five years may be subject to ordinary income tax or a 10% federal penalty tax, or both.
The Vanguard Capital Markets Model® is a proprietary financial simulation tool developed and maintained by Vanguard’s primary investment research and advice teams. The model forecasts distributions of future returns for a wide array of broad asset classes. Those asset classes include U.S. and international equity markets, several maturities of the U.S. Treasury and corporate fixed income markets, international fixed income markets, U.S. money markets, commodities, and certain alternative investment strategies. The theoretical and empirical foundation for the Vanguard Capital Markets Model is that the returns of various asset classes reflect the compensation investors require for bearing different types of systematic risk (beta). At the core of the model are estimates of the dynamic statistical relationship between risk factors and asset returns, obtained from statistical analysis based on available monthly financial and economic data from as early as 1960. Using a system of estimated equations, the model then applies a Monte Carlo simulation method to project the estimated interrelationships among risk factors and asset classes as well as uncertainty and randomness over time. The model generates a large set of simulated outcomes for each asset class over several time horizons. Forecasts are obtained by computing measures of central tendency in these simulations. Results produced by the tool will vary with each use and over time.