kim226

Joanne Sparta is a 48-year old, successful physician who earns in excess of $500,000 per year. She has also been successful speculating on small business startups, which has added an average of $200,000 to her annual income over the last 10 years. Sparta travels extensively. She likes to consider herself someone who lives in the fast lane and possesses refined tastes in both the arts and entertainment. Sparta’s annual expenses, including travel and entertainment, average $375,000. Sparta has no foreseeable liquidity needs, legal, regulatory, or tax concerns, and has no unique circumstances. Which of the following most appropriately describes Sparta’s ability and willingness to bear risk? Sparta is:

A) willing, but unable to accept risk.

B) neither able or willing to accept risk.

C) both willing and able to accept risk.

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Based on the information provided, Sparta’s fast life style, speculative activities, and relatively large income in excess of expenses, indicates both a willingness and ability to accept risk.

kim226

The process of elimination can be used to arrive at an individual’s asset allocation. Which step is often considered the first hurdle in the elimination process?

A) Risk objective.

B) Return objective.

C) Liquidity constraint.

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The first step in the elimination process is to select those allocations that at least meet the real after-tax total return objective of the investor. Once that step is completed, then other considerations are addressed.

kim226

After selecting allocations based on a return objective criterion, the process of elimination for selecting the appropriate individual investor allocation can next use which of the following factors?

A) Risk objective.

B) Unique considerations.

C) Liquidity constraint.

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Once the return objective has been met, eliminating allocations via the risk objective can be accomplished.

kim226

If more than one allocation exists after elimination via return and risk criteria, the advisor then can eliminate those that do NOT meet an individual’s:

A) familial heritage.

B) unique considerations.

C) acquaintance recommendations.

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Unique preferences and other considerations should be used to eliminate those allocations that are inappropriate beyond risk and return objectives. These unique preferences may be related to statements made about what type of securities an individual does not desire holding or some desired liquidity level not already considered explicitly in the liquidity constraint. Any indication as to inappropriateness can be used to eliminate all but the most appropriate allocation.

kim226

Which of the following inputs is NOT used in both deterministic and probabilistic analyses in individual retirement planning?

A) Current income.

B) Assets owned.

C) Input variable probabilities.

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In both approaches, the individual supplies a similar set of personal information, including the above as well as age, savings, etc. The difference between deterministic and probabilistic analyses is that deterministic planning techniques use single values for economic and financial variables. Monte Carlo (MC) simulations generate a probabilistic forecast of multiple retirement period values. Only Monte Carlo simulation would require the input of variable probabilities.

kim226

Which of the following statements about approaches in retirement planning is least accurate?

A) Monte Carlo techniques can be used by most individual investors.

B) Monte Carlo techniques take into account probabilities for input variables.

C) Deterministic planning techniques use multiple values for economic and financial variables.

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Deterministic planning techniques use single values for economic and financial variables. Monte Carlo (MC) simulations generate a probabilistic forecast of retirement period values. Although MC analyses require computing powers, the advent of computers available at low cost provides the individual investor a means for incorporating probabilities into retirement planning process.

kim226

Which of the following statements about Monte Carlo simulation is CORRECT? Monte Carlo simulation:

A) typically produces approximately 100 trials.

B) is best when it uses only historical data.

C) forecasts a more accurate risk/return tradeoff than a deterministic approach.

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History provides a view of only one possible path among the many that might occur in the future. It is difficult to estimate expected returns using historical figures because of the volatility factor. Monte Carlo analysis produces probability distribution by tabulating the outcomes of a large number (often 10,000) of simulated trials.

kim226

When planning for retirement, an individual investor may wish to use a Monte Carlo approach over a deterministic approach because:

A) Monte Carlo approaches are simpler and quicker to implement.

B) deterministic approaches use inappropriate inputs.

C) Monte Carlo approaches provide a better analysis of outcome ranges than the single wealth figure estimate generated by deterministic approaches.

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Monte Carlo approaches generate ranges of outcomes that can be associated with probabilities of their occurrences. Although slightly more involved in implementation, and sometimes taking longer to generate, Monte Carlo generated ranges and or probabilities may better indicate to the client realistic retirement opportunities.

kim226

Deterministic approaches differ from Monte Carlo approaches in that deterministic approaches:

A) use probability forecasts whereas Monte Carlo approaches use best estimates.

B) generate single numbers whereas Monte Carlo approaches generate a range of outcomes.

C) generate ranges of outcomes whereas Monte Carlo approaches generate single numbers.

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Monte Carlo approaches rely on probabilistic inputs to generate a range of outcomes that may provide better information than any method that generates a single number, like deterministic approaches.

kim226

Probabilistic outcomes generated by a Monte Carlo approach to retirement planning do NOT generate which of the following?

A) Potential risk/return tradeoffs.

B) Higher probabilities of meeting high return expectations.

C) Better incorporation of tax implications.

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No forecasting method can affect probabilities of meeting high return expectations. Forecasting methods can only indicate future outcomes, and in the case of Monte Carlo approaches, potential risk/return tradeoffs can be generated, as well as better incorporating tax implications.