IBF - Updates - 2009 (Q1 v1.0)

QUARTERLY UPDATES Q1 2009

Copyright Š 2009 by Institute of Business & Finance. All rights reserved.

v1.0

Quarterly Updates Table of Contents INSURANCE LIFE SETTLEMENTS

1.1

MUTUAL FUNDS BREAKING THE BUCK STABLE-VALUE MUTUAL FUNDS VARYING ASSET ALLOCATION MODELS

2.1 2.1 2.2

FINANCIAL PLANNING CITIGROUP STUDY PORTFOLIO REBALANCING FREQUENCY 2009 RMD WAIVER GENERATING LIFETIME INCOME WITH $500,000 CONSUMER REPORTS SALES CALENDAR MORTGAGE PRE-PAYMENT REDUCING MEDICAL COSTS MONTE CARLO SIMULATION RETIREMENT RISK MANAGEMENT EVENSKY WITHDRAWAL STRATEGIES

3.1 3.1 3.2 3.2 3.3 3.4 3.5 3.6 3.12 3.14

ANNUITIES ANNUITIES AND CREDITOR PROTECTION QUOTES ABOUT ANNUITIES AND LIFE WEISMAN ANNUITY GUIDELINES ANNUITY SOURCES LIFETIME ANNUITY COMPARISONS ANNUITY DEATH BENEFITS VARIABLE ANNUITY PROSPECTUS LONG-TERM CARE RIDER COSTS BONUS CREDITS

4.1 4.3 4.6 4.8 4.9 4.9 4.10 4.11 4.11

QUARTERLY UPDATES INSURANCE

INSURANCE

1.LIFE

1.1

SETTLEMENTS

Some life settlement companies, such as Life Partners Holdings, let individual accredited investors to buy fractions of life policies. Although the policies are held like any other investment, investors pay any remaining premiums while eventually receiving a lump sum that is less than the policy’s death benefit.

A 2007 study by Life Policy Dynamics estimated that investor payouts range from 1029% of the death benefit, depending on the insured’s health, age and other factors; the average has been estimated to be a 24% payout across the industry. For the entity (or investor) who buys a life insurance policy, it is estimated that they payout is 3-5 times greater than the contract’s then surrender value (i.e., what the insurance company would offer the insured).

In an effort to prevent STOLI transactions (stranger originated life insurance policies), some states have enacted laws that require the policy owner to wait at least five years after purchasing a policy before it can be sold to a third party, such as a settlement company or non-related individual. These states also allow exceptions for things such as bankruptcy.

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QUARTERLY UPDATES MUTUAL FUNDS

MUTUAL FUNDS

2.BREAKING

2.1

THE

BUCK

Investors of the Reserve Fund, a money market fund that was originally founded by the person who invented money market funds, is the second money market fund in U.S. history to “break the buck.” Investors in this fund received 92 cents on the dollar. The fund’s losses were caused by its short-term debt holdings from Lehman Brothers. The fund managed $62 billion in September 2008 and just $7 billion by February 2009.

STABLE-VALUE MUTUAL FUNDS For the calendar year 2008, stable-value funds averaged 4.7% (vs. -34% for the DJIA); these funds are only available within 401(k) and other tax-deferred savings plans. The objective of a stable-value fund is preservation of principal. Stable-value funds invest in diversified bond portfolios and contracts from banks and insurers designed to provide protection against sharp market swings. Banks and insurance companies provide the “wrap” contracts that help to smooth the funds’ returns.

Stable-value funds held $520 billion in assets at the end of 2008, according to the Stable Value Investment Association. The value at which investors typically buy and sell a stable-value fund is the “book” value, but the actual market value of the funds’ holdings can be substantially different from the book value. According to Hueler Cos. The average stable-value fund had a market value of 95% compared to its book value at the end of 2008 (vs. 99% at the end of 2007). Funds are supposed to disclose their market-to-book ratio at least once a year.

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MUTUAL FUNDS

2.2

VARYING ASSET ALLOCATION MODELS The next table summarizes model portfolios recommended by four investment advisors in the early 1990s: Fidelity, Merrill Lynch, the financial journalist Jane Bryant Quinn and the New York Times. Notice the percentage differences in the stock allocations for just the conservative investor: Fidelity recommended 20% while Merrill Lynch recommended 45%, a 125% difference.

Asset Allocation Models [1997] Cash

Bonds

Stocks

Bond/Stock Ratio

Fidelity conservative moderate aggressive

50% 20 5

30% 40 30

20% 40 65

1.50 1.00 0.46

Merrill Lynch conservative moderate

20 5

35 40

45 55

.78 .73

aggressive

5

20

75

.27

J.B. Quinn conservative moderate aggressive

50 10 0

30 40 0

20 50 100

1.50 0.80 0.00

N.Y. Times conservative moderate

20 10

40 30

40 60

1.00 0.50

aggressive

0

20

80

0.25

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FINANCIAL PLANNING

3.CITIGROUP

3.1

STUDY

A 2009 study by Citigroup shows that a portfolio should have 25-30 stocks in order to minimize stock-specific risk (unsystematic risk). The study found that over the past 20 years, only one in 10 stocks consistently outperformed the S&P 500 over any rolling three-year period. A third of the stocks in the S&P 500 underperformed the overall market by at least 15% or more for any given year.

PORTFOLIO REBALANCING FREQUENCY From its peak in August and September 1929, what is now the S&P 500 went on to lose more than 83%, hitting bottom in 1932. Over the same period, intermediate Treasury bonds went up 12.4%. Even with dividends reinvested, an all-stock portfolio did not recover its 1929 high until January 1945; at that point, bonds had a cumulative gain of 80.3%.

If the investor had a 50/50 (S&P 500/Treasurys) in September 1929, he would have lost 35.5% by June 1932. Had this investor rebalanced once every 12 months, the loss would have been 48.2%; more frequent rebalancing would have resulted in an even greater loss.

By the beginning of 1945, a portfolio that was 50/50 in 1929 and never readjusted would have gained 40.5%; rebalancing the same portfolio every 12 months would have resulted in a cumulative gain of 53.7%.

If you had invested in a 50/50 mix of stocks and bonds in December 1993, you would have had a 144% gain by December 1999; by September 2002, the cumulative gain would have dropped to 92%. Rebalancing annually would have resulted in almost the same results.

From 1993 to February 2009, an annually rebalanced 50/50 portfolio would have grown 150%. Over the same period, 100% invested in the S&P 500 would have grown 110%; a 50/50 portfolio never rebalanced over the period was up 126%.

The conclusion reached from all of this is that rebalancing is probably a chance worth taking.

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FINANCIAL PLANNING

3.2

2009 RMD WAIVER The Worker, Retiree and Employer Recovery Act of 2008 allows traditional, SEP, SIMPLE, and inherited IRA owners the flexibility of not having to make a required minimum distribution (RMD) for the 2009 calendar year. The waiver also applies to 401(k), 403(b) and all other defined contribution plans.

GENERATING LIFETIME INCOME WITH $500,000 Average annual income for 30 years

Median portfolio after 30 years

$26,300

$0

50% stocks & 50% in bonds

$26,200

$775,800

25% in stocks & bonds 75% fixed-rate annuity annuitized

$26,300

$193,950

25% in stocks & bonds 75% fixed-rate annuity annuitized

$26,300

$387,900

25% in stocks & bonds 75% fixed-rate annuity annuitized

$26,200

$81,800

Investment Mix 100% fixed-rate annuitized

annuity

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3.3

CONSUMER REPORTS SALES CALENDAR Consumer Reports Calendar of What is on Sale When January cookware swimwear bedding linens

February houses & condos indoor furniture small electronics

May cordless phones small consumer electronics athletic clothes

June summer sports gear swimwear furniture consumer electronics October digital cameras winter coats gas grills bikes

September large appliances shrubs & trees bikes tires

March winter coats humidifiers television sets winter sports gear July computers outdoor furniture indoor furniture swimwear

April digital cameras spring clothing

November computers electronics gas grills toys

December cars computers gas grills television sets

August computers outdoor furniture cars toys

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3.4

MORTGAGE PRE-PAYMENT Since 1969, home-price growth averaged 6.5% annually; the S&P 500 has averaged 910% per year over the past 20 years. Generally, the longer the holding period, the more it makes sense not to pay an extra amount toward the mortgage—investing any extra money into the S&P 500 is usually the better choice.

Home holding period

Gain returned by an extra $100 per month spent on…

Mortgage

S&P 500 index fund

Jan. 1986 to Jan. 1996

$4,810

$10,820

Jan. 1990 to Jan. 2000

$4,030

$20,790

Oct. 1992 to Oct. 2002

$4,860

$2,060

Aug. 1994 to Aug. 2004

$4,230

$1,420

Dec. 1996 to Dec. 2006

$3,251

$3,590

10-Year holds:

Averages for 10-, 15- and 20-year holding periods 10 years

$4,030

$10,060

15 years

$8,820

$19,610

20 years

$14,680

$41,930

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3.5

REDUCING MEDICAL COSTS Seven Wall Street Journal tips for cutting your medical costs: [1] The Right Plan  Some plans cover hospitals but not outpatient care  Other plans may skip maternity, rehabilitation or radiation coverage  Talk to the human resources department at work  Compare plans: http://reportcard.ncqa.org/plan/external/plansearch.aspx.  Young people can benefit from high deductibles with pre-tax dollars  For pre-existing conditions: consider a state-sponsored, high-risk pool  Uninsured should contact federally funded community clinics [2] The Best Care  Compare hospitals: www.hospital-compare.hhs.gov  Doctors may reduce fees if they believe you are short on cash [3] Take Control  Make sure each network member (specialist) accepts your coverage  Make a written request before you check in for a procedure [4] Take Care of Hospital Bills  Do not pay directly until charges are matched to plan’s explanations  Hospitals often charge uninsured more than those with group coverage  Ask for discount if you pay upfront by cash or check  Set target rate of 125% of payment rates used by Medicare  Check bill for errors [5] Manage Medications  A number of people take different versions of the same medication

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3.6

MONTE CARLO SIMULATION According to a 2002 article in the magazine, Investment Advisor, “The future of financial planning is Monte Carlo. Monte Carlo replaces the misleading assumption of a single stream of average returns with the calculation of hundreds (or thousands) of possible sequences (called iterations) of returns. It then converts these many possible results into a single, seemingly more accurate answer—the probability that your client will meet all of her goals.” The article’s author then goes on to write, “There are some serious misconceptions about how it works.”

When looking at Monte Carlo simulation, the numbers look right and the experts believe they sound right, but something about them does not feel right to the seasoned financial advisor.

The interpretation and explanation of Monte Carlo is often a struggle. For example, what does it really mean to tell a client, “You have a 78% chance of reaching your goals and a 22% chance you won’t.” Does this instill confidence in the client? Is the client likely to adapt such odds? How precise or likely are these figures? According to at least one critic, “The profession may find this exercise (Monte Carlo analysis) is little more than hype developed by mathematicians and promoted by financial planning software companies.”

The Intent of Monte Carlo Assuming the advisor and client are confident in using historical data to make future predictions, return sequence is extremely important—as shown in the table below.

Importance of Sequence: $1 million Nest Egg for 65-year-old [objective: $62,000 yearly income, 3% annual inflation adjustment] Return Sequence Loss 1 year Yearly average Gain 1st year $62,000 $62,000 $62,000 st

Annual withdrawal Return 1st year Return years 2-29

-10% 7.6%

7.6% 7.6%

+29% 7.6%

Return year 30

+29%

7.6%

-10%

30-year average Money lasts…

Ending value

7.6% 22 years $0

7.6% 30 years $98,000

7.6% 30 years $1,543,000 QUARTERLY UPDATES

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3.7

The table above assumes a lump-sum investment that averages 7.6% a year on a pre-tax basis. The couple needs $62,000 a year to live on; after the first year, annual withdrawals will annually increase by 3% to offset inflation (e.g., for year two, the couple will take out $63,860 and $65,775 in year three).

The different ending values after 30 years (last row of table) are the result of just one variable: portfolio returns in the first year. One ending value is zero because the portfolio had a loss of 10% the first year (but a 29% gain the last year). Another portfolio has an ending value of $1,543,000 (more than the original principal), simply because it gained 29% the first year (and despite a -10% return the 30th year. The “middle” portfolio has an ending value of $98,000 because its returns are 7.6% each and every year. This middle portfolio will not survive a 31st year because the withdrawal would exceed the remaining principal ($62,000 compounding at 3% for 30 years means a withdrawal of over $150,000 in year 31).

In short, the advisor and client may strongly believe in the use of historical returns, but neither party would be foolish enough to predict the sequence of future returns. This hidden reality is sometimes referred to as return sequence risk. As the advisor might suspect, the sequence of returns plays a critical role in the success or failure of a portfolio that is largely, or fully, designed for retirement income. Return sequence risk is usually highest if the portfolio experiences losses in the initial years of distribution—the double “whammy” of a withdrawal and market drop.

Monte Carlo simulation (analysis) was developed to address the problem of returnsequence risk. Thus, instead of assuming a single, and specific, return sequence, Monte Carlo explores all possible sequences (not all, but statistically all since 100s or 1000s of simulations are generated). The table below presents the same conclusions reached by the previous table by using Monte Carlo. Results are based on a wide range of historical returns within two standard deviations (95% of all observations). The table shows there is a 5% chance that the portfolio will have an ending value of $0 (after 14 years) or $7 million (after 30 years).

Monte Carlo Simulation Using 1,000 Iterations Probability Annual Withdrawal Money lasts…

Ending value

5%—worst $62,000

50%—median $62,000

5%—best $62,000

14 years $0

27 years $0

30 years $7,000,000

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3.8

A popular way to illustrate Monte Carlo results is to compare outcomes to a client’s income goal, using a single figure, often referred to as the probability of success.

Probability is determined by adding up the number of iterations (simulations) that meet the goal and then dividing that sum by the total number of iterations. In this particular case, the result is 42%. Thus, based on a specific software program, the client is projected to have a 42% of having a $62,000 annual income stream (adjusted upward each year by 3%) that lasts 30 years.

Monte Carlo Problem #1: Programming An irony of financial planning is that nobody knows future returns but you still must predict them. Just like modern portfolio theory (MPT) Monte Carlo makes a assumptions about rates of return, standard deviation and return distribution. The formula used is referred to as a mathematical algorithm. Unfortunately, there are many valid opinions as to which assumptions are right. Change the numbers just a little and portfolio composition can change radically. For example, domestic stocks may be a highly favored asset category at a number of different risk levels if the historical period used for the model represents a period wherein returns were high and/or standard deviation was lower. Use a different time, a period when average stock returns are lower and volatility is higher, the software program may then minimize the category.

According to Moshe Milevsky, a finance professor at York University in Toronto, “These concepts [algorithms] need a Good Housekeeping seal of approval. They are not widgets.

They are nuclear reactors. I would like to know that a competent nuclear engineer built my reactor.” The advisor may not want to use a program unless he or she is comfortable with its results and can explain them to the client. These means knowing the program’s assumptions and calculation methods used to produce the results.

A Monte Carlo “black box” makes understanding more difficult; the more assumptions the black box (software program) makes, the harder it becomes for the advisor to feel comfortable and/or to be able to explain the process. In theory, confidence and accuracy would increase if several different Monte Carlo programs were run and results were similar. Unfortunately, this is not the case.

Bloomberg Wealth Manager Magazine (2002) looked at some Monte Carlo programs and used the same parameters for each software application. The hypothetical couple was in their 50s and requested a retirement income strategy. The likelihood that the couple’s assets would support their desired retirement income for their projected life spans ranged from less than 50% with one software application to 95% using a different software provider.

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3.9

Monte Carlo Problem #2: Meaning of Projection If you use Monte Carlo and the software’s conclusion is that there is a 75% probability of success, the question then becomes whether or not 70%, 75% or 85% is “good enough.”

Some programs will reach a conclusion for you. If the probability is 70% or higher, the program will conclude that this is good; anything less than 70% is considered bad.

Another program defines the “comfort zone” as anything between 70% and 90%. The shortcoming of these percentage figures is that each program may define good and bad differently. There is also the issue of client perception.

Someone 70 or 75 years old may not feel comfortable with a probability number less than 90%; a 45-year-old may be content with 50-60% likelihood. Keep in mind that Monte Carlo probability does not prioritize a client’s goals; its results are all-or-nothing.

According to the program, either the client is expected to succeed at all goals or fail at all goals. Although a Monte Carlo program may show that there is a 30% chance of clients outliving their assets, it does not address the following realities: [1] During retirement, clients do not keep spending down to zero; spending adjustments are made along the way.

[2] The projection does not say how badly failure could be. A shortfall of $1 is counted the same as a shortfall of $300,000. A minor change in an assumption can result in a major change of probability.

[3] Even under a “failed” projection, the client is not broker. She may have other sources of income such as Social Security, rental property, a pension or part-time job. Monte Carlo only considers the immediate portfolio.

[4] Monte Carlo assumes no changes are made to the plan over its entire 20-40 year span; it is expected the client and advisor are on automatic pilot. Obviously, if initial portfolio performance is poor, adjustments can be made.

Monte Carlo Problem #3: Hiding Risks Suppose the advisor and client are fortunate enough so that the Monte Carlo probability of not running out of money is now 90% or higher. The issue of systematic risk may be solved, but there is still no measurement of certain “unsystematic” risks. For example: [a] 40% of all people over age 65 will spend some time in a nursing home; [b] the average stay in a nursing home is 2.4 years and [c] the average cost of a nursing home stay is $70,000 per year. Monte Carlo cannot address this issue because it is a possibility problem, not a probability issue.

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3.10

There may be little probability that the client will need long-term care in the future, but such an occurrence is hard to predict. If the client needed 2-3 years of such care, the cost could be devastating. The probability may be low, but the impact severe. The solution is long-term care insurance; a cost that will reduce the value of the portfolio (and perhaps increase the chances of “failure”).

There is also the problem with using individual equities. It may be fine to suggest that the S&P 500 will average 9% annually with a standard deviation of 13%, but what about making 20-year projections for individual stocks, such as GE or IBM? On April 20th, 2008, GE closed at 11.35, with a 52-week range of $5.73 to $33.66. The past performance of individual stocks may have no value when it comes to predicting their future returns. Just think what the standard deviation of an individual stock is that has experienced an 80-90% decline. The volatility is so extreme, a range of returns of -40% to +30% (or whatever) has no meaning or real value within the context of Monte Carlo.

Like long-term care, the probability of a handful of stocks reacting wildly may be small, but the possibility must still be addressed.

Another concern is life expectancy. Actuarial predictions for life expectancy within large groups of people are very accurate. Such calculations can be embedded within a Monte Carlo analysis. The issue of longevity can be addressed by having the program make the assumption that income will be needed until age 95 (or whatever age you feel is a “cushion”).

Monte Carlo is just like financial planning, both represent a process not an answer.

A survey of several hundred financial planners resulted in three important rules: 1. Clients care about one thing—attaining goals, even if risk must be accepted.

2. If a client loses money, risk becomes the foremost concern; rule [1] is forgotten.

3. Advisor advice is most effective when presented within the context [1] and [2].

To be effective, a financial plan needs to focus on client goals and potential risks. Goals must be prioritized. The plan addresses the issues of return-sequence risk and unsystematic risks (e.g., longevity, long-term care, individual securities, etc.). The following process properly utilizes Monte Carlo simulation: [a] Help client create a list of goals. [b] Create a base plan using historical numbers. [c] Stress test the plan for return-sequence risk and unsystematic risks. [d] Repeat steps [b] and [c] as needed to create a plan that works for the client. [e] Use Monte Carlo to compare relative results.

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3.11

Goals The goals of an individual or couple may be more than just “X amount for each of the next 30 years.” The client may also want to replace a car every five years, spend $10,000 for an annual trip, make gifts to grandchildren, etc. By prioritizing, the chances of obtaining each goal can be determined (e.g., $43,000 in a balanced fund is earmarked for $7,000 of gifts for each of the next five years). Separate computations can be made for each goal along with the assets used to try and obtain such a dollar amount.

Stress Test If all dollar goals can be reached and there is little, or no, safety margin, this indicates that the goals will be reached only if everything works out exactly as projected. An appropriate stress test would be to assume bad market timing (initial years result in poor returns). For example, the advisor could assume that the plan initially suffers its two worst years, as measured by two standard deviations. If expected return is 7.6% with a standard deviation of 12%, see what happens if returns for each of the first two years is 16.4% (7.6% - 12% -12%) or a cumulative loss of about 30% (plus add to this negative number whatever is going to be withdrawn for income each year—perhaps resulting in a total principal loss of something in the 38-45%).

As you can see from this rough stress test, the bad news is that the client will probably never recover. The good news is that this might simply mean secondary goals such as gifting or travel may have to be scaled back. The advisor does not need to point out that a stress test shows a 45% likelihood (or whatever the percentage number is) of failure.

Instead, the advisor may be able to say that there is a strong likelihood that most important goals are should be met. Usually, a client understands that if things go wrong, spending may have to be reduced or lesser goals modified.

Unsystematic risks can be handled by pointing out the potential problems created and possible solutions (e.g., buy a certain type of insurance, sell individual securities and use mutual funds, etc.). This is also the appropriate time to show how a reverse mortgage at some time in the future could solve any retirement income shortfall. The use of a reverse mortgage might even increase overall probability from something in the 40-50% range all the way up to 90% or some other high number. A financial plan is valuable only if the client sticks with it over the long term, even if losses occur along the way. To do this, the client must “own” the plan; it must become their plan and not your plan. This can only happen if the client understands it, believes in it and most importantly, is prepared for its inherent risks.

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3.12

The Advisor’s Goal The greatest value you provide a client is not just analyzing probabilities. You must also consider possibilities. Software programs coupled with stress testing can help accomplish this, but nothing can replace informed judgment. Understanding trumps sophistication every time. Perhaps Monte Carlo, or any other analysis, should include the following disclaimer: “Your probability of success is 86%; projections are based on a number of assumptions that cannot be proved and do not include or reflect the risks of longevity, long-term care needs, lawsuits, a lengthy economic depression, tax rate changes, Social Security benefit reductions, concentrated stock positions or changes in goals.”

Adding sophistication to any model, including MPT and Monte Carlo, may increase its accuracy, but ignoring stress testing is like the captain of the Titanic focusing on the speed of the ship instead of having someone on deck looking out for icebergs. Since there may only be a few icebergs in an ocean, the chance of a ship reaching its destination is very high, but it takes only one iceberg to sink an “unsinkable” ship.

RETIREMENT RISK MANAGEMENT If a retiree invests too much in equities, he runs the risk of ruin if returns are poor during the first decade of retirement. Conversely, too little in stocks may mean the portfolio lacks sufficient growth also resulting in ruin. In a sense, you are “damned if you do and damned if you don’t.” Fortunately, the advisor does not have to choose between either; there is a third choice— option. The idea is to purchase a form of equity insurance (buying put options) and to minimize such costs by limiting equity upside potential (selling call options). The strategy is sometimes referred to as a retirement collar.

By selling a call option (giving someone the right to buy the stock at a specific price) and using the proceeds to purchase a put option (giving the client the right to make someone buy an equity at a specified price) with a lower strike price, the client is likely to have a more predictable range of returns, at least for the equity portion of the portfolio.

Probability of success is increased because the risk of large negative returns is removed (by owning put options); the cost for such insurance is the stocks can only appreciate a certain amount before they are called away (by selling call options to pay for the put options). The strategy may be to sell a call option that is “out of the money” by 10% (thereby limiting upside potential to 10%) and use the proceeds to buy a put that is out of the money by 5-10% (or whatever the client’s risk tolerance).

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3.13

Visualizing this strategy from the perspective of Monte Carlo simulations, all computer “runs” that include a stock loss of greater than the put option (meaning a loss of 5-10% in this example) are eliminated as well as all iterations that include stock gains above the strike price (anything above +10% in this example).

Obviously, the strategy could be varied to fit the client’s risk level or stock market beliefs. One client may wish to limit downside stock losses to no more than 5%; another client may accept up to a 15% loss but no more. The same thinking is applicable to the upside. One client may feel that a return of more than 10-15% a year from stocks is not realistic, while another client may only want to give up returns in excess of 20%.

A further variation of the strategy would be to just buy put options and not limit upside potential. The cost of buying put options over the course of a year may be in the 3% range, more or less depending upon how much downside risk the client is willing to accept before the put option kicks in. The cost may be, say 3%, but it would be 3% of the stock portion, not 3% of the entire portfolio return for the year. This or any other strategy may be of greatest benefit during the first decade or so of retirement, when negative returns have their greatest impact. When designing the portfolio, the advisor should keep the following in mind: [a] For a couple, both age 65, expect one of them to live to age 90. [b] After 20-25 years, expect purchasing power to drop by >50%. [c] A withdrawal rate >5% adjusted for inflation may not be sustainable. [d] The first 7-10 years the most critical for plan success. [e] Consider retirement income “collars” (buying puts and selling calls). [f] Revisit the idea of lifetime annuitization for a portion of the portfolio. [g] Reduce uncertainty by conducting “stress tests.” [h] Fear is a greater motivator than greed. [i] Always consider a 40-60% fixed-income exposure.

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3.14

EVENSKY WITHDRAWAL STRATEGIES Harold Evensky is one of, the best-known financial planners in the country. In fact, he may be the best known. This section edits down his company’s retirement income strategy, referred to as the Evensky & Katz Cash Flow Reserve Strategy (E&K-S).

A basic premise of the Evensky & Katz strategy is “paycheck syndrome.” Until retirement, your client was used to paying for things from a paycheck; any excess was set aside in savings. Growth of these savings resulted in a “nest egg.” The rule was: spend paychecks, never principal. This exemplifies what behavioral economists refer to as “separate pockets.” And, even though it may be obvious that spending 5-6% of a portfolio that has a total return of 5-6% or more is the same as spending 5-6% of interest income and/or dividends, it does not feel the same to most clients. To the client, dividends and interest feel like a paycheck; selling assets from a “total return” portfolio often feels like principal invasion. So, keep in mind: [1] cash flow needs to be consistent; [2] paychecks are independent of the market—the income strategy should insulate the client from market volatility; [3] the source of a paycheck should be visible and considered reliable; [4] clients understand paychecks—they need to understand the cash flow strategy and [5] the portfolio should incorporate client tendency to think of “separate pockets.”

Cash Flow Strategy o Longevity Risk—living a long, long time. o Purchasing Power Risk—over time, this “hidden tax” has a real impact. o Volatility—few understand the strain or impact of several downturns. o Flexibility—client needs and markets change; a plan must be flexible. o Behavioral Risk—fears or biases changes perception and/or reality. o Real Cash Flow—annual income must increase to offset inflation. o Distinguish Income—“total return” is different from income/dividend income. o Tax and Asset Expense Efficiency—free risk-reduction via increased returns.

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Annuities

4.ANNUITIES

4.1

AND

CREDITOR PROTECTION

The lawsuits clients read about are newsworthy because they are rare, unusual occurrences. Whether the fear such stories and perceptions are real or not, many people are drawn to the idea of protecting assets from creditors or lawsuits. All states have Homestead laws that partially or fully protect a person’s home from creditor claims.

Some states have laws that protect life insurance and IRAs. In the case of annuities, there are considerable differences from state to state. Some states offer no protection, while others offer total protection. The following list describes protection offered in those states that do protect at least a portion of the value of an annuity. It is important to keep in mind that these laws are always changing. If creditor protection is important to a client, the advisor should check to see what current protection is or is not provided.

Alabama — maximum of $250 per month in benefits.

Alaska — maximum of $12,000 of an annuity that has not yet matured.

Arizona — only qualified annuities under IRC sections 401(a), 403(b) 408 and 409.

California — entire value of annuities that have not yet matured.

Connecticut — only annuities that are ERISA qualified.

Delaware — maximum of $350 per month in benefits.

Florida — entire value of annuities.

Georgia — annuity proceeds to the extent necessary for support.

Hawaii — amounts paid to spouse, child, parent or other dependent of annuity owner.

Idaho — maximum of $1,250 per month in benefits.

Illinois — amounts paid to spouse, child, parent or other dependent of annuity owner.

Indiana — entire value other than payments from excessive prior year contribution.

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Kansas — entire value of annuities that qualify under specific state statutes.

Kentucky — maximum of $350 per month in benefits.

Louisiana — entire value (limited to $35,000 if bankruptcy filed < 9 months of purchase).

Maine — maximum of $450 per month in benefits.

Maryland — entire value if payable to spouse, child or dependent relative of owner.

Michigan — entire value of the annuities.

Minnesota — entire value of annuities are protected from creditors of annuity owner.

Mississippi — amounts reasonable for support due to illness, disability, death or old age.

Missouri — amounts reasonable for support due to illness, disability, death or old age.

Nebraska — maximum annuity value of $10,000.

Nevada — maximum of $350 per month in benefits.

New Jersey — maximum of $500 per month in benefits.

New Mexico — entire value of annuities.

New York — discretion of judge after considering needs of owner and dependents.

North Carolina — annuities that qualify under IRC section 408.

North Dakota — maximum of $100,000 per policy with total protection limited to $200,000; figures may increase depending on support needed for owner and dependents.

Ohio — entire value of annuities payable to spouse, child or dependent of owner.

Oregon — maximum of $500 per month in benefits.

Pennsylvania — payments to owner’s spouse, child or dependent relative.

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Rhode Island — annuities that qualify under IRC section 408(b).

South Carolina — annuities that qualify under IRC section 401(a), 403(a), 403(b), 408 or 409 payments used for payments due to death, disability or old age.

South Dakota — maximum of $250 per month in benefits.

Tennessee — annuities used to provide for owner’s spouse, child, dependent relative.

Texas — entire value of the annuities.

Utah — annuity amounts for reasonable needs and support of owner and dependents.

Vermont — maximum of $350 per month in benefits.

Washington — maximum of $250 per month in benefits.

Wisconsin — entire annuity values if payments for old age, illness, disability or death.

Wyoming — maximum of $350 per month in benefits.

QUOTES ABOUT ANNUITIES AND LIFE  I advise you to go on living solely to enrage those paying your annuities. It is the only pleasure I have left—Voltaire  The question isn’t at what age I want to retire. It’s at what income—George Foreman  An investment in knowledge always pays the best interest—Benjamin Franklin  The future ain’t what it used to be—Yogi Berra  Beware of little expenses. A small leak will sink a great ship—Benjamin Franklin  The pure and simple truth is rarely pure and rarely simple—Oscar Wilde

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 Life is the sum of all of your choices—Voltaire  Retirement is like a long vacation in Las Vegas. The goal is to enjoy it to the fullest, but not so fully that you run out of money—Jonathan Clements  The four most dangerous words in investing are “This time it’s different—John Templeton  There’s no business like show business, but there are several businesses like accounting—David Letterman  Get your facts first, and then you can distort them as much as you please—Mark Twain  A nickel ain’t worth a dime anymore—Yogi Berra  Simplify, simplify, simplify—Voltaire  Never put off till tomorrow what you can do the day after tomorrow—Mark Twain  They say such nice things about people at their funerals that it makes me sad that I’m going to miss mine by just a few days—Garrison Keillor  The hardest thing in the world to understand is the income tax—Albert Einstein  The pessimist sees difficulty in every opportunity. The optimist sees the opportunity in every difficulty—Winston Churchill  When investing money, the amount of interest you want should depend on whether you want to eat well or sleep well—Kenfield Morley  You can be young without money; but you can’t be old without it—Tennessee Williams  In theory, there is no difference between theory and practice. In practice there is— Yogi Berra  I intend to live forever, or die trying—Groucho Marx

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 A very rich person should leave his kids enough to do anything, but not enough to do nothing—Warren Buffet  Just as a cautious businessman avoids investing all of his capital in one concern, so wisdom would probably admonish us also not to anticipate all our happiness from one quarter alone—Sigmund Freud  He who hesitates is poor—Mel Brooks  The Lord giveth and the IRS taketh away—Anonymous (did not want to be audited)  I don’t make jokes. I just watch Congress and report the facts—Will Rogers  Too much of a good thing can be wonderful—Mae West  ‘Tis said that persons living on annuities are longer lived than others—Lord Byron  You cannot escape the responsibility of tomorrow by evading it today —Abraham Lincoln  Children today are tyrants. They contradict their parents, gobble their food and tyrannize their teachers—Socrates  People may or may not say what they mean…but they always say something designed to get what they want—David Mamet  And in the end, it’s not the years in your life that count. It’s the life in your years— Abraham Lincoln  Money, if it does not bring you happiness, will at least help you be miserable in comfort—Helen Gurley Brown  If you want a guarantee, buy a toaster—Clint Eastwood  If the world were perfect, it wouldn’t be—Yogi Berra  Litigation is the basic legal right which guarantees every corporation its decade in court—David Porter

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 A man who does not think for himself does not think at all—Oscar Wilde  As the old saying goes, what the wise man does in the beginning, fools do in the end— Warren Buffet  An annuity is a very serious business—Jane Austen  Many receive advice, only the wise profit from it—Pubilius Syrus  Information is the seed for an idea, and only grows when it’s watered—Heinz Bergen

WEISMAN ANNUITY GUIDELINES Steven Weisman is an elder law attorney who has written extensively about annuities and other issues facing retirees. Listed below are “Steve’s Annuity Rules” edited: [1] It is not what your client make that counts, it is what the client keeps.

[2] The longer the tax-deferred growth period, the better an annuity becomes.

[3] Avoid non-qualified annuities until IRA and qualified plan accounts are fully funded.

[4] Tax deferral is good, a Roth IRA and Roth 401(k) are better.

[5] Never recommend a tax-deferred annuity if there is a chance the client will have to make withdrawals from it prior to age 59 ½.

[6] Annuities are not the best investment to leave to heirs.

[7] Using annuities for Medicaid planning is very complicated.

[8] Annuities are not a good investment for children, but a Roth IRA for a child can be a great idea.

[9] Statistically, annuity death benefits are not a very good benefit.

[10] Avoid tax deferral unless you can invest for at least 10-15 years.

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[11] There can be a huge difference in annuity fees and guarantees.

[12] Consider a lifetime annuity for a person or family that has a history of longevity.

[13] Free bonuses within an annuity are not free.

[14] A charitable gift annuity can provide retirement income and current tax deduction plus benefit a worthy cause.

[15] When shopping for a fixed-rate annuity, make sure the guaranteed rate period is not less than the surrender penalty period.

[16] Annuities work best if the client expects to be in a lower tax bracket during retirement.

[17] Avoid inflation-protected annuities; the protection is not worth the cost.

[18] Owning a low-cost immediate annuity may put the client in a better position to be more aggressive with the rest of the investment portfolio.

[19] Generally, shorter surrender period annuities have higher fees that can greatly reduce the value of the shorter surrender period.

[20] Laddering fixed-rate immediate annuities is a way to take advantage of rising interest rates.

[21] An advantage of all annuities is their â&#x20AC;&#x153;free lookâ&#x20AC;? period; make sure the client is aware of this benefit.

[22] A split annuity strategy may be a safe way to take advantage of current rates while making retirement dollars last longer.

[23] Usually, annuitization based on one life with life insurance is better than a joint and life survivor payout if the client wishes to protect a loved one.

[24] Buying an immediate annuity with money from a reverse mortgage can be a smart strategy.

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ANNUITY SOURCES The Securities and Exchange Commission’s web site www.sec.gov/investor/seniors/seniorscarepackage.htm www.sec.gov/investor/pubs/equityidxannuity.htm www.sec.gov/investor/pubs/varaquestions.htm The Financial Industry Regulatory Authority www.finra.org (type in the word “annuities”) Immediate Annuities www.immediateannuities.com Healthcare and Elder Law Programs Corporation (HELP) www.annuitytruth.org Annuity FYI www.annuityfyi.com Annuities-Central www.annuities-central.com The Variable Annuity Research and Data Service (VARDS) www.vards.com Brokerage Companies Columbus Life Insurance—www.columbuslife.com Vanguard—www.vanguard.com Charles Schwab—www.schwab.com TIAA-CREF—www.tiaa-cref.com Insurance Company Ratings A.M. Best—www.ambest.com Standard & Poor’s—www.standardandpoors.com Moody’s—www.moodys.com Weiss—www.weissratings.com Charitable Giving www.charitywatch.com Reverse Mortgages www.reversemortgage.org QUARTERLY UPDATES

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LIFETIME ANNUITY COMPARISONS The monthly dollar figures below are for a 65-year-old man who is a resident of Massachusetts and invests $100,000 in an immediate annuity. o o o o o o

Lifetime-only payout with no payment to beneficiaries: $672 Lifetime payout with 5-year term certain to beneficiaries: $667 Lifetime payout with 10-year term certain to beneficiaries: $649 Lifetime payout with installment refund to beneficiaries: $632 Joint life—income remains the same after 1st death: $577 Joint life—income remains the same after 1st death w/ 15-year certain: $572

ANNUITY DEATH BENEFITS Variable annuity death benefits need to be compared against term life insurance. The standard death benefit pays the greater of principal or value upon death. Some death benefits can have an annual cost 1.1% to 1.75% of contract value. For example, suppose a client invested $100,000 in a variable annuity and the mortality expense was 1.25% per year (or $1,250 per year +/- contract value). Is the client really getting $100,000 worth of insurance? The answer is only if death occurs when the contract has dropped to zero. If this same client were a 65-year-old male in good health, term life insurance would cost about $580 a year—far less than the $1,250 imposed by the annuity.

There are death benefits that lock-in any gain after specific internals, often once every three or five years. Again, the question becomes what is the expected risk versus what could be protected with life insurance. Also keep in mind that the enhancement is typically taxed as ordinary income when received by the beneficiary. Life insurance proceeds are almost always received tax free.

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VARIABLE ANNUITY PROSPECTUS Some of the things contained in a variable annuity prospectus include:                    

Investment options (subaccounts) Fees and expenses Information about the issuing insurance company Information about the fixed-rate account option Information about the accumulation phase and its options Information about the variable account Renewal options Early withdrawal rules Payment options Account fees Administrative fees Distribution fees Mortality and expense risk fees Surrender fees and provisions Charges for optional riders Tax information Death benefits Optional death benefit riders Change of ownership provisions Historical investment performance

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LONG-TERM CARE RIDER COSTS Beginning in 2010, insurance companies will be permitted to issue long-term care insurance as an annuity rider. The advisor needs to know that the premium for the rider will come from the client’s tax basis. Thus, if a client paid $70,000 for an annuity that is now worth $90,000, the cost basis would be $67,000—if the rider cost $3,000. There are two tax consequences to this cost basis reduction.

First, the annuity owner will pay more in ordinary income taxes when the annuity is liquidated (a larger gain since cost basis has been reduced by $3,000 in this example).

Second, the client loses out on taking a tax deduction on his or her present income tax return for the cost of premiums for long-term care insurance. If a separate policy was directly purchased by the client, the amount of the deduction would depend upon the tax return and client age. On a positive note, if the client were in poor health, he or she might not qualify for an “outside” policy, thereby making the long-term care annuity rider worth considering.

BONUS CREDITS The SEC website compares two annuities, each purchased for $100,000. The first contract offers a 4% bonus credit (allowing $104,000 to be initially invested). The cost of the bonus is 0.5% annually (1.75% vs. 1.25%). Assuming a 10% annual return before expenses, after 10 years the value of the annuity without the bonus credit is $231,360 versus $229,780 for the annuity with the bonus.

The dollar difference in the example above becomes greater in the unlikely event the rate of return exceeds 10% a year. The bonus credit also becomes even less attractive the longer the compounding period. Furthermore, there are a number of ways the insurance company may be able to take away the bonus credit: if early withdrawals are made or upon death if the annuity includes a life insurance benefit.

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