— There are a few common questions that many clients
will eventually ask their financial adviser to answer.
much will my portfolio be worth at retirement? Will I
outlive my money? How would my plan be affected by a
stock market downturn?
are the adviser will not try to answer any of those
questions before running the numbers through a
computerized mathematical system that is practically
unknown to the general public, yet widely used in the
financial services industry. It is called the Monte
has nothing to do with French Riviera, casinos, Grace
Kelly or James Bond.
Monte Carlo method used by financial advisers is a
technology that analyzes the likelihood of a client’s
portfolio being successful. The adviser inputs certain
data, such as the client’s age and what assets are in
the portfolio. The computer looks at thousands of
portfolio return outcomes over multiple time periods and
market conditions to arrive at the most likely — or
highest probability — outcome.
form is used by just about every wealth management firm
that has made an investment in financial planning tools
and resources. But some industry players also warn that
these simulations are only as good as the quality of the
information provided, and that improper use can give
users a false sense of security.
Hapanowicz, president of Hapanowicz & Associates
Financial Services in downtown Pittsburgh, said his firm
has been using this sort of analysis in financial and
retirement planning for more than five years.
"Monte Carlo enables us to analyze a client’s
plan across many different life scenarios, thus
providing a very effective way to stress test the plan
and estimate the probability of success."
of the things advisers love so much about the method is
its strong basis in mathematical statistics.
Monte Carlo, you can model thousands of potential life
outcomes by using random variables — such as stock
market returns, inflation rates, interest rates — to
measure probability of success within a financial
plan," Hapanowicz said.
Monte Carlo report will assign different probabilities
to different outcomes. A 95 percent probability is
considered the gold standard.
method was named by mathematician Stan Ulam in 1946. The
name refers to the casino in Monaco where his uncle
would borrow money from relatives to gamble. According
to mathematics website Motherboard, Ulam was inspired to
develop the method with his partner John Von Neumann
while playing solitaire and trying to calculate the
likelihood of winning based on the initial layout of the
computational algorithms are used in a variety of fields
outside of financial services, such as production
management, engineering, physics and weather
Johnson, president and CEO of the American College of
Financial Services in suburban Philadelphia, said those
who rely too heavily on Monte Carlo reports should be
reminded of previous instances where quantitative models
of the greatest examples, he said, is the failure of
Long Term Capital Management, a firm founded by some of
the best minds in finance, including Nobel Prize
winners. The Greenwich, Conn.-based hedge fund nearly
collapsed the global financial system in 1998 as a
result of high-risk arbitrage trading strategies.
more recent example is the failure of rating agencies to
properly assess the risk of mortgage-backed securities
failing," Johnson noted.
Carlo simulations give users the illusion of
precision," he said. "That is, you can
construct a retirement portfolio that, according to
Monte Carlo simulation, will only result in a 3 percent
chance of a shortfall. Yet, that assumes that your
assumption and inputs accurately reflect the future, as
are the interactions between variables consistent with
Besh, investment director for PNC Bank, sees Monte Carlo
analysis as a great tool to show probability of outcomes
of a total portfolio of diversified assets. But it is
not a forecaster of investment returns, nor is it used
to evaluate individual stocks.
planning uses capital market assumptions — expected
long-term returns and standard deviation — for each
asset class used in a portfolio," Besh said.
"These assumptions are devised using historical
data combined with projections of future returns.
Carlo analysis helps us to determine the most likely, or
highest probability, outcome based on the assumptions
used," he said. "This type of analysis is
widely used and present in every financial planning
said all projections PNC Bank shares with clients come
with disclosures that past performance is not indicative
of future results. "Again, Monte Carlo is just a
quantitative method that gives us more confidence in our
projections — but never 100 percent," he said.
financial planner who is sold on the method is Martin
Schamis, vice president and head of wealth management at
Janney Montgomery Scott in Philadelphia.
am pro-Monte Carlo," he said. "I feel the
Monte Carlo system is a very powerful set of tools for
investment professionals. Many of the criticisms we see
of Monte Carlo aren’t about the methodology or system
itself, but about the input that we use to set the
we use the Monte Carlo in an investment portfolio, we
have to put in a series of data that defines how we
believe the market will behave. In many cases, we’re
using historical data to predict what the future will
look like. However, as we know past performance is no
guarantee of future returns."