The Big Picture is an application for wealth and retirement planning. It allows financial advisors to back-test retirement portfolios over hundreds of historical periods, and answer questions like:Based on history...
Endless "what if" scenarios can be explored—each an opportunity for client engagement. "What if spending is raised, or lowered?", "What if retirement lasts a few years longer?
No clutter or tedious data entry—and no bored clients!
The Big Picture app functions on the basis of rolling historical periods. It shows how much a retiree needed in retirement savings, and how much could safely be withdrawn, not only in average market conditions, but in every market condition that retirees have ever faced. It shows how your client's nest egg would have fared if retirement had begun on January 1, 1926, on February 1, 1926, and so on throughout history.
Would your client's retirement strategy have survived the Great Depression, hyperflation, and 1970s stagflation? If so, it may survive future unfavorable markets. Or would it have produced a shortfall, even in the stock market boom of the 80s and 90s? If so, it may fall short in the years ahead, too.
The following eleven total-return indices are currently available with a “Premium” subscription. Each index begins in 1926 and is monthly in frequency. Data are updated quarterly via an automatic feed.
We hold long-term agreements with respected index compilers, such as the Center for Research in Security Prices (CRSP) at the University of Chicago. For technical details, please contact us.
The variety of asset classes featured in the Big Picture app allows you to build as simple or elaborate a portfolio as you like. You can simulate a client's actual investment portfolio, that of a specific fund offering, or whichever hypothetical portfolio you wish to illustrate.
The historical indices featured in the Big Picture app begin in 1926—the longest range available for reliable data. For any given investment horizon, whether one year in duration, or forty, this breadth of data gives the Big Picture app hundreds of historical rolling periods from which to draw meaningful conclusions.
Yes. Both our Core and Premium plans allow you to upload your logo.
The Big Picture app is grounded in the methodology used by William Bengen in his seminal 1990s research (later replicated by the Trinity Study and others). Namely, it assumes constant inflation-adjusted distributions throughout retirement.
But, don’t retirees’ spending patterns evolve as they age? And, what if portfolio values rise or fall significantly after retirement begins?
Researchers have studied the first question in depth. Some studies have shown that spending declines over time, as retirees downsize and adopt a slower-paced lifestyle. Others show an increasing trend as health care needs rise with age. Still others show a u-shaped spending pattern that reflects each of the above.
If it’s difficult to discern clear patterns across thousands of cases, it is doubly so to reliably anticipate the spending needs of an individual retiree. Personal circumstances, market conditions, and random chance will dictate the path a given retirement takes.
Researchers have also studied the second question, and have developed the concept of dynamic, or “rules-based”, withdrawal strategies that would adjust distributions in response to significant post-retirement portfolio fluctuations. “Guyton’s Rule” and others like it attempt to provide retirees with some protection against portfolio depletion (by cutting spending in poor market environments) while allowing them to boost spending if returns exceed expectations.
The problem with rules-based spending is two-fold. First, in some historical cases, these rules would have called for massive reductions in spending. Such cuts are unrealistic for most.
Second, spending rules can create the illusion that a reliable formula exists for the future, and complicate what should be a straightforward exercise.
The result can be “options paralysis”, whereby the search for the perfect plan precludes sensible action.
With these limitations in mind, we reaffirm Bengen’s fixed spending assumption in computing safe withdrawal rates, and suggest to advisors the following:
If a client’s portfolio appreciates or depreciates significantly, or if his spending needs change unexpectedly, simply revisit the Big Picture app with inputs that reflect this new reality. Repeat as necessary.
This approach, in our view, is more adaptive than sticking steadfastly to any rule committed to under past circumstances.
No. For two reasons:
First, your clients’ names, ages, investment holdings, and other personal details constitute highly sensitive data. This information should be confined to software that offers bank level security. A data breach, such as this one from Redtail, could be ruinous to your clients’ financial lives—and to your advisory business. While it can be convenient to view client data across platforms, we believe that the risks outweigh the benefits.
Second, our mission is to provide investors with, quite literally, the Big Picture. With the added complexity of managing client data, not only do security risks arise, but this focus is compromised.
Reliable market data do not exist prior to 1926. Retirement plans built on the basis of figures that pre-date this point in history are, in our view, unsound.
As the University of Chicago’s Center for Research in Security Prices (CRSP), a leading authority on U.S. market returns, affirms:
“A major consideration for the choice of the initial date (of 1926) was the availability of complete and reliable data sources. Primary source material prior to 1930 is often incomplete or inaccurate.”
With over nine decades of reliable market data, the Big Picture App covers a vast range of historical scenarios. For any given investment horizon, whether one year in duration, or forty, this breadth of data gives the Big Picture app hundreds upon hundreds of historical rolling periods from which to draw statistically meaningful results.
The Big Picture allows you to ascertain, based on history, how best to consider allocating capital. And not just between Bonds and Stocks, but a wide range of major asset classes, including Small-Cap Stocks, Mid-Cap Stocks, International Stocks, and T-Bills, to name just a few.
The below table highlights the differences in historical success rates between two portfolios.
|Portfolio A||Portfolio B|
|Historical Success Rate at a 4.0 percent Withdrawal Rate||94%||100%|
|Safe Withdrawal Rate*||3.8%||4.1%|
*Data starting 1926.
*The maximum withdrawal rate that would have guaranteed solvency over the full course of a 30-year retirement, in all 30-year periods for which data exist (starting 1926).
The difference in outcomes—and the implications for retirement planning—could not be clearer.
A rolling period is a fixed period of time that shifts from one start and end date to the next start and end date for which data are available. The start date for each rolling period always precedes the end date of the previous one. In this way, rolling periods are partially overlapping.
Tax rates have varied significantly through time, by jurisdiction, and by the legal and financial circumstances of particular individuals. They also vary according to the interest and dividends generated by a given portfolio, as well asits cost basis. Taxes are therefore excluded from the app's calculations.
Within the app, you can adjust the Total Expense Ratio to gauge the impact of expenses on investment results.
Per standard practice, the app considers withdrawal rates as percentages of starting capital. The annual dollar equivalent is calculated, and then divided by twelve. The resulting amount is then adjusted by the actual rate of inflation that prevailed in each historical month over which the portfolio is back-tested, and is withdrawn monthly from the portfolio balance. Withdrawals are not adjusted based on portfolio performance.
Historical index data are updated quarterly via an automatic feed. You can see the most-recent update at the bottom of the app's Settings page.
We hold long-term agreements respected index compilers, such as the Center for Research in Security Prices at the University of Chicago. For technical details on a specific historical index, please contact us.
Yes, you can cancel your subscription at any time. Annual fees are refundable within the first 60 days following the expiry of your 10-day free trial. Subscriptions automatically renew and will continue renewing until you cancel. Once your subscription is canceled, you will retain access to the Big Picture for the duration of your subscription term.