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A Better Index? (3/16)
Annuity Rates Will Move Up Even If Overall Bonds Yields Don’t (1/13)
A Better Index? (3/16)
The capital market theories of Markowitz and Sharpe are used by millions in the financial world to determine the relative value of securities. They are simple to understand and compute. They favor a story of passive investing through capitalization weighted indices. And, a growing chorus says they are also...wrong. The major assumptions of these theories are that markets are efficient, that there are no such things as inflation, taxes, transactions costs or changes in interest rates, that investors always maximize expected utility, and that knowing the portfolio's mean and standard deviation is all you need to know. There is no risk management. However, acknowledging that the real world does not operate like the assumptions means managing for risk can produce better results than passively waiting.
A study by Wojciechowski and Thompson captures the results of thousands of random portfolios they created where they then compared their performance within a thirty three year overall period with a market capitalization approach, such as the S&P 500 Index uses.
What they found was in twenty two of the years over half of these random portfolios had returns above the capital market line. What this means is a non-passive approach can "beat the market". Sharpe’s theory says the reason why some of these random portfolios have higher returns is because they probably have higher risk than the market as a whole. However, Wojciechowski and Thompson found that there was no correlation between the portfolios with higher returns and risk (defined as volatility). Their conclusion was that a risk based approach can generate higher returns than a market capitalization one.
Applying a more active rules-based approach appears to offer the possibility of the higher returns than simply using the S&P 500
A new study by Ernst, Thompson and Miao says the S&P 500 can be beaten, precisely because it is a market capitalization weighted portfolio. As an example, they compare the performance of buying one share each of the stocks of the S&P 500 versus buying stocks based on their market cap. From 1958 to 2014 the annualized geometric return for the one-stock non-market cap approach was 10.4%, for the market cap weighted S&P 500 the return was 7.1%. The authors did another study where they picked the top twenty stocks each year with the highest medians from the S&P 500. The geometric mean return was 10.8%. Indeed, their simple 20 stock rules-based portfolio beat the S&P 70% of the time. Neither return includes dividends.
Tying this into a rules-based VCI Although many of the volatility controlled indices use the stocks of the S&P 500 Index as their catalogue, many of them also apply rules based strategies and only select a small percentage of the overall universe for their own index and these stocks are then moved in and out based on the rules in place. The 20 to 100+ stocks selected, depending on the index, are reallocated based on performance or dividends or individual volatility or undiscovered value, based on the rules applied. These indices are not actively managed, like a mutual fund, but simply move based on the formulas in place.
Regardless of the strategy used, if the results of the studies I mentioned are not flukes, the implication is one or more of these rules-based indices could outperform the passive S&P 500 over the long term. In other words, everything else being equal, an index picking a subset of S&P 500 stocks could outperform the S&P 500 over the long-term. In the volatility-controlled world of FIAs these rules based strategies are restrained by the volatility controlled mechanism, but could still generate more interest.
P. Ernst, J. Thompson & Y. Miao. February 2016. Portfolio Selection: The Power of Equal Weight. arXiv:1602.00782 [q-fin.PM]
W. Wojciechowski & J. Thompson. 2006. Market truths: theory versus empirical simulations. Journal of Statistical Computation and Simulation. 76(5):385–395.
Low Yields Foretell Difficult Year (2/15)
The 10 year Treasury was exactly 1% lower at the end of January than it was a year earlier. The precise opposite of where most predicted it would be and where the economy implies it should be. The U.S. economy has recovered from the 2008 Crash. GDP set a new high. The S&P 500 has tripled and Nasdaq has almost quadrupled. The unemployment rate is 5.6% and the supply of labor is tightening, putting upward pressure on wages. By historical standards, the bond yield increases that started in the spring of 2013 should have the 10-year U.S. Treasury around 3.5%; instead it ended January at 1.67%. FIA Caps & Rates Are Unlikely To Head Higher This continues to be a weak recovery and confidence about the future is thin. Rates are low because businesses aren't borrowing to expand. Rates are also low because the recovery in much of the rest of the world has stalled and investors are putting money into government bonds for safety, not yield.
The U.S. dollar is strong. A year ago it took $1.35 to buy 1 Euro, today it takes $1.13. That's great news if you're a tourist in Paris, but if you're a U.S. company selling in Europe your goods got a lot more expensive. Concerns over future growth have ramped up stock market volatility, as demonstrated by the big market swings in recent weeks. Looking at a 20-day moving average, the S&P 500 Volatility Index (VIX) has increased from the 12-ish level from last summer to over 19, meaning option prices are higher. In addition, after a six-year run there doesn't seem to be much room in the stock market's plaza de toros.
The problem in setting index annuity participation rates is not only are the current yields low and option prices higher, but the future looks worse. If a carrier thinks bond yield will go up later in the year they are often more generous on current-yield based pricing – giving up a little profit today might maintain the pace of sales and you'll make back the profit with the future sales. However, if one thinks rates will stay low or head even lower, it makes for a frugal situation.
What it would take to get bond rates heading higher this year would be a continuation of falling unemployment as well as rising GDP aided by an improved outlook for the global economy. Unfortunately, this is an unlikely hat trick. Current FIA pricing probably won't get better this year. This scenario also means a greater use of managed volatility indices. While they aren't a panacea for low bond yields they do offer a better return story than more traditional methods.
In spite of a pricing environment indicating lower index participation FIAs remain attractive, because the alternatives look worse. Rates on intermediate term multi-year annuities (MYGAs) from higher rated companies are paying in the low to mid 2% range, the best 1-year certificate of deposit rates are barely over 1%, bond returns are low and if rates do rise, can turn negative, and gambling that the stock market's run will extend for seven years is looking dicey. Even with lower caps FIAs still offer the potential for more interest, protection from stock market loss, and a low opportunity cost when compared to MYGAs and CDs or doing nothing.
Hypothetical FIA Returns Are More Real Than Real Returns (and so is a Bayesian model) (7/14)
In the financial world statistics are used to try understand the past and predict the future. People look at past numbers and attempt to see patterns. At its simplest, these numbers are expressed as an average such as "the long-term annual stock market return is 10%" – the Ibbotson return numbers often quoted are examples of this. In the last twenty years or so this has been replaced or at least augmented by looking at past returns using the Monte Carlo method that came out of the world of physics. The Monte Carlo method does a far more nuanced job of showing how the past looks than merely reporting the average by looking at the distribution of returns. What makes using a descriptive frequentist inferential statistical* or classical approach easy is the basis for the historic returns does not change.
* All this term means is observing (drawing inferences) how often (frequently) certain returns occur.
What this means is regardless of your data source for the S&P 500 or XYZ stock you will see the same return for the same past periods for each. However, the same cannot be said for past fixed index annuity (FIA) returns.
phynances ain't physics (and fisics ain't finances)
The S&P 500 is the underlying index represented in the majority of past and current FIA purchases. However, for any given time period there were wide differences between the returns of different annuities using this index. The main reason was different crediting methods. At one time there were over 40 ways used to tweak the index values to produce a return and the differences produced by these tweaks could be huge – there were years when the difference between the highest and lowest S&P 500 index-linked return was over 30% for the same timeframe. The remaining variation in returns was largely explained by the amount of participation in the crediting method (two annuities could use daily averaging with a spread, but one used a 2% spread and the other had a 3% spread). In addition, there would even be differences in returns for the same period between owners of the same annuity product.
Same Annuity – Different Returns
Whether you bought, say, the Vanguard 500 Index fund in 2006 or 2008 or 2010 your return for 2012 was the same for all. However, if you bought the exact same annuity index using the S&P 500 in 2006 or 2008 or 2010 you very likely earned three different returns for 2012. The reason why is index participation is strongly influenced by the bond yield environment when you purchased the annuity. When you buy a fixed annuity the carrier typically buys bonds to provide the interest to cover the minimum return guarantee and provide additional interest to buy the index-link (the hedge) on the underlying index. Typically the maturity of the bonds roughly mirrors the anticipated life of the annuity – if you think the annuity will be around for 10 years you buy 10 year maturity bonds. What this means is the money available to buy index-links in future years is strongly influenced by the level of bond yields when the annuity is purchased. Thus, if yields are high when you buy the annuity there will be more money from interest available in future years than if yields are low at time of purchase. This means in future years the annuity bought when yields were high will have better caps, lower spreads and higher index participation. These differences narrow as years past and the underlying bonds are replaced, but the bond yield environment at time of purchase influences annuity renewal rates, caps and spreads for years and years.
An annuity purchased in 2006 won’t have the same future returns as the identical annuity purchased in 2008 or 2010 Even so, if you’re only looking at the past classical statistics works for both investments and FIAs. In other words, if your goal is to find out the average return or the return patterns of either an investment or an FIA for previous time periods the same statistical approach works for both. But what if you're trying to predict the future? If one believes that the warning on every piece of investment literature is incorrect and that past performance really does predict the future, then both averaging and Monte Carlo models would provide indications of future returns on investments. After all, reversion to the mean would provide evidence that if current returns are lower than the historic average then the return is bound to move up, or vice versa. Or our 95% confidence level derived from some Monte Carlo model on the investment might means the odds of a bad return are very low and this would encourage us to invest more. However, even if past performance did predict future investment returns, past FIA returns would not predict future index annuity ones.
When looking at historic FIA returns the bond yields in effect at time of purchase play a bigger role than actual index performance. Even if the future daily index movements were identical to the past the FIA returns would be different – unless the pricing patterns also repeated and annuity carrier management set the new rates, caps and spreads exactly as they had the last time around. The bottom line is past historic index annuity returns bear no relationship to future return predictability and the classical statistical approach does not and cannot work with FIAs because there are too many other factors in play besides the movements of the index. However, using hypothetical models and not actual performance may create a more accurate picture.
A Bayesian Approach
For the period from September 2003 to September 2008 the average annualized FIA return on the 28 annuities reviewed by Advantage Compendium was 5.6% and a few annuities posted annualized returns for this 5 year period of over 7%. However, even if index movements over the next five years were identical to this period it'd be almost impossible to earn 5.6% using those past crediting methods because the current pricing environment is worse – bond yields are lower so index participation is lower. In addition to the current pricing environment, the Federal Reserve Board has made it very clear that their goal for the foreseeable future is to keep interest rates low. In the light of this, using past returns to predict the near future will produce the wrong answers. Or, to put this in Monte Carlo model terms – I have a 95% confidence level that the returns produced by my classical statistical model will be 100% wrong. However, Bayesian statistics provide a solution.
Bayesian statistics combines new information with existing information to try to determine future outcomes; it does not simply use past data or assume that the probabilities of past data will be true for the future, without first looking to see whether conditions have changed. It then determines the odds that these outcomes will happen. A race track is a good place to see how Bayesian is different from classical statistics.
A Bayesian Horse Race
The horse Bayes Bay has won nine out of its last ten races. A classical statistician would look at the past and say that the probability of winning today's race would be 90% or that the odds are 9 to 1 that Bayes Bay will win and bet accordingly. However, a Bayesian tout would look to see if things were different for this race when compared to the previous wins and the loss. Perhaps the only loss Bayes Bay suffered was on a muddy track and it rained all through this morning. In addition, two of the horses in this next race have winning records on muddy tracks. In light of this information the Bayesian tout will conclude that the true odds that Bayes Bay wins are not 9 to 1. In fact, Bayes Bay may not even show in this race, and so the tout bets against Bayes Bay. A Bayesian approach uses subjective probabilities – what are the results based on what we think is going to happen. With this method actual return data is treated as additional information and not the sole source of information. A Bayesian approach to FIAs also relies on what is happening and what we think will happen instead of relying on the past to predict the future. Since hypothetical return FIA models typically reflect current pricing, the results generated should prove more accurate reflections of the future results than using prior actual returns.
Hypothetical returns are more truthful than actual returns Say that current pricing permits a 4% cap. We know that the Federal Reserve hopes to keep interest rates down for at least the next couple of years and has said their long-term goals are a low interest rate environment. Even if each of the next five years of the underlying index has double digit gains it is highly unlikely our annuity would credit even 5.6% annualized (that previous 5-year average return I mentioned) because that would require at least a 6% cap in years two through five and the future interest rate/bond yield forecast won't provide enough interest to be available to buy the 6% index-link.
Hypothetical FIA returns based on a current cap of 4% would provide a much more realistic future return picture than a picture painted from past return colors. Simply put, creating a hypothetic illustration based on today's rates, caps or spreads provides a more realistic view of possible returns than using actual historic returns for the same annuity.
Creating Bayesian FIA Models
Although index annuity hypothetical models generate results that are more truthful than real returns in predictive power they are typically static; the participation in the index is assumed to remain the same over time. One can attempt to create a model of what future index participation would look like based on assumptions of future bond yields and index-link (hedging) costs – the further assumption being that the carrier's future setting of caps, rate, and spreads will reflect only these external factors. The other subjective aspect would be assigning probabilities to the occurrence of past segments of actual historic index movements. In other words, we would take a look at what is happening in today's stock market, speculate on what we think might happen tomorrow, and then assign odds that the next few years will look more like a particular past time period than another.
A Bayesian FIA hypothetical return model would calculate index participation (caps, rate, spreads) on historical movements of the index. This participation would be based on where we think interest rates will be, what hedging costs will be, and what part of the index history is more likely to occur. This isn't as far out or difficult as it sounds. As examples, the odds of investment grade bond yields staying under 7% for the next five years have a far higher probability than yields shooting to 10%; the odds of a bear stock market occurring in the next five years are greater than the current bull market extending until 2019. The math formulas to create these Bayesian hypothetical models are available and the probabilities can be estimated.
Actual FIA returns are essentially worthless in predicting future returns
Hypothetical FIA illustrations do a better job because the index participation reflects current pricing
A Bayesian approach to FIA hypothetical illustrations would do an even better job
A Less Inaccurate Forecast
The warning is true – past performance does not predict future results, except in very broad arcs. Even if it did, classical statistics would still be useless as predictors for fixed index annuities if actual index annuity historic returns are used. The reason why is FIA returns are driven by participation in the index which is dependent on bonds yields and hedging costs. Hypothetical models offer a more realistic picture of possible FIA returns – at least over the next five to ten years – because today's caps, rate, and spreads are a known and provide a base for what future index participation will be.
The predictive power of hypothetical illustrations could be increased (or, better stated, major inaccuracies could be decreased) by modeling FIA hypothetical returns using a Bayesian approach that adds probabilities to future bond yields, future hedging costs and even which parts of the index history should be used in the predictive model. These Bayesians FIA illustrations should provide a more accurate future picture than static hypothetical illustration or attempting to prophesize based on looking at actual returns. Even though S&P 500 and Vanguard are mentioned no fixed index annuity is sponsored, endorsed sold or promoted by either. This information is for educational use and is not intended as financial or investment advice or to persuade or induce anyone to do anything.
Managing FIA Volatility: 1995 to Today (3/14)
Volatility means the degree to which returns sway from the average or Mean return. Here are two investments with different degrees of volatility:
Investment A has a Mean return of 5%. The worst expected return is 4% and the best expected return is 6%.
Investment B has far greater volatility than Investment A – B's return in any one year could be 20% higher or lower than the average return while A's range of returns is 1% in either direction. Which is the better choice? Over the long term they are a match – both average 5%; over the short-term it depends to an extent on your expectations and risk aversion. If your goal is to never to earn less than 4% then "A" is best, but if your goal is try for double digit returns then "B" is the only choice – keeping in mind "B" could also incur double digit losses.
In the 12 months ending 31 August 2012 the S&P 500 gained 15.4% and a 100% nominal rate using daily averaging of the index produced a gain of 7.4% for an effective participation rate of 48%. However, a 31 August 2011 year closed with the index up 16.2%, but daily averaging of the S&P 500 produced a gain of 19.9% for an effective participation rate of 123%.
The previous example is one version of averaging, and this type of averaging has been computed over daily, monthly and quarterly index values. Another way to average and limit volatility is to cap the size of the interim gains.
How Well Do Cap Rates Correlate With Bond Yields & The VIX? (12/13)
Hedging Longevity Risk (3/13)
But what if too many people live too long? A problem for annuity carriers is life expectancy has been steadily increasing for the last half century. What if new drugs are found that increase life expectancy by, say, adding on another decade? It would be difficult to even calculate how high the rider fee would need to be to cover this unknown risk or how low to set the payouts. One way to deal with mortality unknowns is to hedge the risk in case the annuityowners live too long.
However, natural doesn’t mean easy. If the longevity and mortality timelines don’t match up, or if your business model is too concentrated in either life or annuities, then you may be unable to create a workable natural hedge. If you can’t build a hedge you can try to buy one.
Carriers offering both annuities with lifetime income benefits and life insurance have the capability to create a natural hedge that may give them a competitive advantage, but longevity bonds or swaps are needed to more fully hedge the risk of annuityowners living too long
In December 2003 Swiss Re introduced mortality bonds that paid a handsome yield to investors if there wasn’t a catastrophic increase in deaths during the life of the bond, but the investors could lose some or all their money if future mortality (life insurance death claims) were far above the historic norm. The bonds were snapped up by investors. Someone at BNP Paribus looked at this concept and wondered, “why couldn’t we create an un-mortality bonds?” And so the first longevity bond was offered for sale in 2004. It didn’t sell well (for a variety of reason), but it got a lot of people thinking.
No one has developed the definitive longevity bond and the market will ultimately develop a variety of solutions. One concept would be for the annuity carrier to issue bonds that pay a certain coupon rate, but if the longevity of the covered group of annuity living benefit buyers increases more than a certain amount, the bond could be structured to reduce the coupon or the maturity value.
One might approach this from the other end by producing bonds the annuity carrier would buy because these bonds would increase in value, either in coupon rate or in maturity value, if longevity increased. Who benefits financially from increased longevity and, thus, might be interested in hedging longevity? Life insurance carriers are aided when payment on the death benefit is delayed and they could issue bonds that paid a higher coupon when longevity increased. One report suggested that drug companies could issue these bonds because increasing life expectancy means consumers would buy their Lipitor® longer.
The wonder of an annuity is the consumer is able to transfer their risk of living too long to the insurer. The problem is how does the insurer handle the added risk? Although natural hedging is a partial solution the development of different types of longevity bonds as tradable securities in capital markets could protect insurers and possibly increase lifetime payouts to the consumer. The reality is lifetime income benefits pose certain distinct unknowns. One is not knowing how many annuitybuyers will use the benefit (a topic discussed in other articles) but the biggest unknown is how long will the users live. If the carrier has a strong book of life insurance policies these can work as a natural hedge, for others it may come down to the creation of a viable actively traded market in longevity bonds.
My thanks to Noel Abkemeier for his help with this article.
Blake, D., T. Boardman & A. Cairns (2010).The case for longevity bonds Center for Retirement Research Number 10-10
Cox, S. and Y. Lin (2007). Natural hedging of life and annuity mortality risks. North American Actuarial Journal. 11, 1: 15
Luciano, E., L. Regis & E. Vigna (2011). Natural delta gamma hedging of longevity and interest rate risk. ICER Working Paper No. 21/2011
Wang, J., H. Huang, S. Yang, and J. Tsai (2010). An optimal product mix for hedging longevity risk in life insurance companies: the immunization theory approach. The Journal of Risk and Insurance. 77, 2: 473-497
Buy This Annuity (and win a chance at a new car) (2/13)
Private lotteries have been offered for a number of years in several countries. Perhaps the most successful one ever was started in 2005 by First National Bank of South Africa. Savers received 1 lottery ticket for every 100 rand ($16) deposited. The savers earned a slightly less than market saving rate and 114 prizes were awarded each month (with payoffs up to $160,000). Within three years the bank had opened 1.1 million new accounts and collected $170 million in new deposits. The private savings lottery worked well – too well – which is why the South African Lottery Board successfully sued to shut it down. And competition is the reason that all U.S. states have laws that prohibit private lotteries.
People like the idea of prizes being associated with savings. A survey conducted in 2009 asked consumers ‘Would you be interested in a savings account that awarded chances to win prizes based on the amount of money you save?’ Only 26% of the people said they weren’t interested. In 2009 a few Michigan credit unions offered the ‘Save to Win’ program with the requirement that money be deposited in a savings account. The grand prize was $100,000. In eleven months 11,600 new accounts were opened. A similar program offered by in Indiana was also successful.
The reason the Indiana and Michigan credit unions were able to offer prizes is that technically the Indiana one was a “sweepstakes” and the Michigan one was a “raffle”. Most states permit a sweepstakes where a purchase is not required (but they may not limit the difficulty required for a person to enter that hasn’t made a purchase). There are 39 states that allow raffles (source: www.raffleahouse.com.) that may legally require a purchase (usually a non-profit is involved). The reasons for the Indiana and Michigan experiments was to see whether in a low interest rate environment the addition of a “lottery prize” would increase deposits. It did. The other reason was to see if an interest-paying savings vehicle that also offered a prize would get people to save that normally did not. This too was a success with 56% of the new accounts opened by people that had never before had a savings account.
The Lotto Annuity
Current state laws do prohibit annuity carriers from offering lotteries and may ban raffles and sweepstakes as well (although in the few state codes I checked I didn’t see specific bans on insurance carrier raffles, but if prizes are considered “rebates” that would ban them in most states). In any event, any carrier that managed to get a “prize” annuity approved by the insurance department would almost certainly be sued by the lottery commission (perhaps the solution is for the annuity to offer state lottery tickets). However, from a behavioral viewpoint a prize annuity would result in more people saving for retirement resulting in less financial strain on future state services; a prize that benefits everyone.
1) Kearney et al. 2010. Making savers winners” An overview of prize-linked savings products. NBER Working Paper 16433. http://www.nber.org/papers/w16433
Annuity Rates Will Move Up Even If Overall Bonds Yields Don’t (1/13)
The early ‘00s were a different story. The millennium recession, although mild in the U.S., caused credit problems in foreign markets, and that fear fueled an unjustified fear about U.S. corporate debt. Between the summers of 2002 and 2003 Aaa corporate bond yields averaged 6.1%, which should have meant a 10-year Treasury yield of 5.5% based on history. However, Treasury Notes instead paid 4.0%, or 66% of the Aaa bond yield instead of 90%. Based on fear of foreign contagion, and a possible double dip recession, investors did not so much as build in a risk premium for owning corporate bonds as they instead created a safety rate discount for owning government debt. This caution proved unwarranted and those that had purchased Treasury Notes instead of Aaa corporate bonds experienced relative losses as the correlation between the two steadily increased to 88% by 2007. To put a head on it, during this period while 10 year Treasury yields rose from 3.9% to 5.1% (and T-notes market value declined) Aaa corporate bond yields rose from 5.7% to 5.8% (and market values barely shuddered).
The financial crisis of 2008 shook investor confidence and the credit markets to the core. Once again there was a flight to Treasuries, but the safety discount became even more drastic with 10-year Treasury’s yielding less than 50% of Aaa corporate debt yields by the fall of 2008. This ratio steadily improved in 2009 and reached 73% by the spring of 2010, before slowly falling back again as worries increased about the strength of the recovery. However, the next stumble was strictly due to the summer 2011 folly in Washington and the nonsense with the debt ceiling.
When the politicians almost caused the U.S. to default in August of 2011 the ratio again dipped below 50% and then got worse. By the time of the 2012 election the yield on 10-year Treasuries was half of its long term ratio – 45%. To put this into perspective, based on 60 years of history the 10-year U.S. Treasury Note should have yielded 3.25% in November 2012. Using the Asian financial Crisis as a worse case the T-Note should have been yielding 2.4%. Instead it was at 1.59%. Simply put, based on the actual risk of default on corporate debt the 10-year Treasury yield is far too low and should be much higher. Even if we approach this from the other side and say corporate yields are too high and should come down to the 2.7% range – only briefly seen 60 years ago – it would still mean 10-year Treasury notes should be yielding 2.5% today.
Different Standards For Today?
Once again it appears the financial markets have severely overreacted to the possibility of default of Aaa corporate debt. However, rather than increasing the yield on the corporate debt the market’s reaction has been to give a safety rate discount for U.S. debt, which is unwarranted. The end result is that even if rates on corporate bond do not improve the yields on Treasury debt will go up over the next couple of years bringing a measure of relief to insurance carrier investment portfolios.
Annuity Unbundling – Cost vs Benefit (2/12)
Bonuses and commissions are obvious costs; others are more subtle. Most products include a waiver of surrender charges if the annuityowner is confined to a nursing, some extend this waiver to cover a terminal illness, a few even cover unemployment. All of these benefits impose a cost on the annuity, but anecdotal evidence suggests that these benefits are almost never used. A less subtle cost is offering an initial interest rate or interest cap that can’t be supported by carrier earnings and so it is recaptured with lower renewal rates to the annuityowner, but the initial unsupported rate or cap is not disclosed as such.The reality of the lowest bond yield environment in over 50 years is there simply isn’t enough spread to recapture all of these costs from the renewal rates, therefore carriers are being forced to unbundle the benefit, state the cost, and allow the annuitybuyer to decide whether the benefit is worth the cost.
The first unbundling occurred before rates dropped and it was charging for guaranteed lifetime withdrawal benefits. The first two carriers to offer GLWBs charged specific fees for this income benefit and almost every carrier followed their lead in treating GLWBs as an optional benefit. A little over a year later Aviva was the first to charge an annuityowner an explicit fee* for guaranteeing a minimum death benefit, but almost no one followed that time around. It wasn’t until autumn 2011, as bond yields continued to fall, that carriers began to seriously consider charging annuityowners fees for benefits that had heretofore been seen as standard equipment. I feel the reason for this was wariness about breaking the sanctity of the annuity promise, but this promise had already been broken.
Redefining The Annuity Promise
These new examples of unbundling have been caused by a very low bond yield world that will continue to challenge carriers for at least the next few years, but I view it as a positive step because it brings greater transparency to the fixed annuity world and permits the consumer to decide whether a benefit is worth the cost. While I believe bond yields will again head up and carrier spreads will increase, the unbundled approach could become the new annuity promise of greater transparency for consumers.
* Index annuities may talk about an “asset fee” that reduces index-linked interest credited, but it really isn’t a fee because it can never reduce the interest earned to less than zero. An index annuity asset fee is simply another way of saying participation rate.
VA Carrier Seeds in the FIA Garden (10/11)
Interest in FIAs resulted from weakening VA sales and fear of GLWB in-the-money risk
VA sales did recover and rose to set an all-time record in 2007 of $179 billion, aided in large part by strong living benefit riders that helped to shield investors from loss. Since that time sales have slipped. In addition, it was discovered that those living benefit riders could create losses for the VA carriers, instead of profits, because investors were inclined to use them when they presented the greatest risk of loss for the carrier. A Milliman study (discussed in the July 2011 issue) found withdrawals increased when the VA’s income account value was higher than the actual cash value. Essentially, the structure of a VA guaranteed lifetime withdrawal benefit (GLWB) means it is most likely to be utilized at the worse possible time for the carrier – when the annuityowner’s cash value is down he or she is more likely to withdraw and use up all of their own money and thus start using the carrier’s money.
The result was that some VA carriers began to look at the index annuity world as an alternative. After all, FIA sales had steadily risen since 2007 setting new records. In addition, a GLWB on an index annuity coaxes the annuityowner to not take withdrawals because “things can only get better” due to guaranteed roll-up rates or increases in the factors that increase income the longer the withdrawals are delayed (it’s an entirely different mindset and one that works in favor of the index annuity carrier). In addition to this – though it hard to believe today – bond rates had started to move up in the fall and winter of 2010 making fixed products more attractive.
I don’t know how many VA carriers drew up plans for index annuities. I do know four carriers filed fixed index products with the regulators. Phoenix (PHL Variable Insurance Company) was early to sow releasing FIAs in 2010. Hartford Life, Mass Mutual and Pacific Life filed their fixed products within the last 6 months. However, Hartford reportedly pulled their FIA filing in August (Contract: LA-FIA-A-11. SERFF Tr Num: FRCS-127383797). Although Mass Mutual filed in May (FL DOI Initial Filing May 5, 2011) it has not yet come to market. And Pacific Life’s FIA has a requested implementation date of 1 November 2011 (SERFF Tracking Number: PACL-127538215). We know how the index annuities of Phoenix are structured and it might be instructive to see what the other VA carriers were thinking in their product design.
The three unreleased products are pretty straightforward. All offer a fixed account option and all offer a link to the S&P 500. Hartford also filed a Global Allocation (50% S&P 500, 20% S&P 400, 15% Russell 2000, 15% MSCI EAFE Index) while Pacific Life filed to offer the MSCI ACWI All Country World Index. All have an annual point-to-point with cap method. Both Hartford and Pacific Life also offer the Trigger method where a declared rate is paid if the index doesn’t lose ground. Hartford filed to offer monthly averaging less a spread and a monthly cap design. The Mass Mutual design has a 7-year surrender period, with no MVA, with the option of adding 5 and 9 year products if desired. Hartford filed for 5, 7 and 10 year periods and Pacific Life filed for 6, 8 and 10 years; both Hartford and Pacific Life have an MVA. The only GLWB specs I could find were on the Pacific Life annuity and it is competitive. Even though the FIA designs are basic, they can be competitive – there’s nothing wrong with them. Whether any of the three come to market will depend on the interest rate environment.
Effect Of Low Returns On GLWBs (9/11)
When index annuity GLWBs were first introduced the roll-up rates were modest – 4% to 5%, but the race escalated so that by 2008 several were guaranteeing 7% to 8% annual payout increases, for each year withdrawals were delayed, for up to 20 years. At age 65 most of the carriers used 5% or 5.5% single payout factors and a 6% payout at age 70. However, these higher roll-up rates when combined with strong payout factors amplified the longevity risk to the carrier if long-term returns were poor.
Low returns have a moderate effect if withdrawals begin soon after purchase
Many retirement models try to get the money to last until age 95 – 30 years of payouts for a 65 year old. Realistically this wasn’t a problem for a GLWB where payments began immediately because taking 5% when earning as little as 3% means money lasts 31 years – even at 2% the money lasts 26 years or until age 91.
But high and long payout growth guarantees are strongly affected
Say the original 5% payout is guaranteed to double in 10 years – a 7.2% compound or 10% simple growth approach. A 55 year old putting in $100 could take out $10 at age 65 ($200 x 5%), but how is the carrier affected if the original premium only earns 3%? At 3% net the annuity cash value (ignoring any surrender charges) is worth $134.39 after 10 years. If the annuity continues to earn 3% with the annuityowner taking our $10/year the money runs out in 18 years or age 83. If the annuity only earns 2% from age 55 on, and $10 withdrawals begin at age 65, the money runs out at age 80.
Rider fees have increased from 0.4% to 0.9%
The problem is made worse as the payout growth guarantee period increases. If the annuitybuyer was 45 and put in $100, using the same 7.2% growth and 5% payout assumptions at age 65 the guaranteed payout would be $20 ($400 payout account value x 5% payout factor). At a 3% return the annuity cash value would be $180.61, and keeping at a 3% return the money runs out in 11 years or age 76.
How to solve this?
Cut Roll-up Rate – if you drop the guarantee from 7.2% to 6% (or from 10% to 8% simple interest) the payout at age 65 drops to $9. If you only take out $9/yr and earn a steady 3% the money lasts to age 86 instead of age 83.
Cut Payout Factor – if you still guarantee 7.2% (10% simple), but cut the payout factor from 5% to 4.5%, and earn a steady 3% the money also lasts to age 86 instead of age 83.
Cut Both – a 6% growth rate and a 4.5% payout means a 3% return makes the money last until age 89. By cutting back either the payout or growth percentage you can get to where the customer’s annuity doesn’t run out of money until after age 95 as long as 4% is earned. And, when you take into account the number of GLWB buyers that won’t use the benefit or die early, combined with the rider fee that has roughly doubled to nearly 1% on average, my scratchpad math says the carriers is still okay as long as around 3% is earned on the annuity with either cutback.
Shift More Risk To The Annuityowner – When Lincoln Financial Group and Lincoln Benefit Life came out with their original GLWBs they did not get involved in the roll-up race, but instead increased the payout factor based on the number of years withdrawals were delayed. What this meant was if the annuity returns were poor the two Lincolns generated lower payouts than most other GLWBS, but if returns were in the 5% or 6% range they did very well (the new Allianz 360 Annuity compared on the next page is a descendant of this approach). The “but” in the increasing factor approach is if the annuity actually earns 5% or 6% for 30 years you won’t need the insurance carrier’s money.
Historic Odds Say Future Returns Should Be Better
Using the Advantage Composite Bond Index you find today’s bond portfolio yield is 4.6%. When you subtract out carrier costs and agent commissions there simply isn’t much left over to buy the options to get higher index annuity caps. Could we have a 30 year period where bond yields stayed this low? Yes.
From 1935 until 1965 there were 26 years where composite bond yields were 4.6% or less. However, the average portfolio bond yield from 1919 though now was 6.5%. Looking back 90 years bonds rates were high enough to support 5%, 6% or much higher caps 72% of the time. At even a 5% cap the long-term hypothetical average index annuity return is 3.22%, meaning that the carrier can support current GLWB promises.
GLWB product changes in 2011 assume that the current low interest climate stays with us for the long, long term. This is prudent since the carrier is insuring the longevity risk and needs to still be in business in 2046. Changes in fees, factors and roll-up rates are meant to ensure the carrier can insure even in worse case scenarios. However, history says that bond yields should increase at some point, meaning that index annuity participation will also go up, meaning annuity returns will also increase. This could result in much higher GLWB payouts than are currently anticipated.
Black-Scholes Is A Lie (5/11)
The argument is option traders use rules of thumb developed over many years. These rules work, but because academia didn’t create these rules they pretend they don’t exist, and then create their own theories. When presented with evidence that theories like dynamic hedging don’t work (such as the failure of “portfolio insurance” in the crash of 1987) they ignore the evidence.
The first myth is Black-Scholes made proper option pricing possible. However, De La Vega and De Pinto over 200 years ago developed option hedging techniques. Indeed, a recent study concludes, “traders in the 19th century appear to have priced options the same way that 21st century traders price options.” The authors cite many, many cases where rules for proper option pricing have been in place for many, many years. The second myth is traders use Black-Scholes to “value” options. The reality is traders “price” options, and the difference between “valuation” and “pricing” in the option world is akin to the difference between a real estate appraisal and the actual selling price of the house. The article basically accuses Black-Scholes-Merton and their proponents of either being liars or stupid. I can’t wait to see the responses.
Why Wall Street Gets It Wrong (1/11)
Wall Street thinks finance is a science and that people are always rational, but neither is true.
Almost three centuries ago the cousins Nicolas and Daniel Bernoulli came up with a theory. What it said was people will choose the outcome that provides the maximum utility for their situation, taking into account their tolerance for risk and that the decision is based on the information they have – which may not be perfect – but that rational people will decide to choose the greatest benefit based on the information they have. This expected utility theory was strengthened by a book written by Frank Knight in 1921 and almost codified by von Neumann and Morgenstern in 1947 who concluding that a person’s decisions were always completely rational as long as some basic rules were followed.
Today’s Wall Street is built on modern portfolio theory, the capital asset pricing model and others but ignores the fatal flaw revealed by behavioral economics which is people don’t always act as the model says they should.
However, folks noticed the theory didn’t always work because there were many situations where people did not choose the best outcome. As an explanation for these contradictions Leonard Savage in 1954 offered a modification saying the reason decisions were not completely rational at times is that people create their own probabilities of an outcome, which may not reflect the true odds and may be subjective. His subjective utility theory concluded that rational people make rational decisions, but they may rationally apply different subjective odds, so two people could come up with different decisions, but both would still be rational, therefore people still made fully rational decisions. Savage tried to offer a rational reason why people are sometimes irrational.
Around this time Harry Markowitz came up with something called modern portfolio theory that said since investments have different return distributions and different levels of risk it was possible to model and compare these on bell curves and find the optimum mix of assets at a prescribed level of risk. The assumption behind this was that people would always make rational decisions to maximize returns at their accepted risk level. This led to the capital asset pricing model created by Treynor, Sharpe, and others that says we can determine the systematic risk, or beta, and then look at the additional potential return of an investment, or alpha, above a risk-free security, and thereby compare totally different assets. And this was followed by a flood of financial formulas including the Sharpe Ratio (risk premium), Black-Scholes model (option pricing) and many others.
Wall Street believed by creating better financial math models they could create above-average returns forever by applying scientific methods to reduce financial risk, and so for the next quarter century Wall Street spent their time and money hiring science grads and creating more formulas...but it didn’t always work (Asian Financial Crisis, Internet Bubble, Real Estate Bubble, Subprime Mortgage Crisis) and the reason was because people weren’t always rational and didn’t always try to maximize utility.
After the last financial crash almost pushed the world into a depression – although the math models said that could never happen – a few folks at Wall Street are finally admitting that maybe there are other factors influencing decisions, therefore in the last couple of years there have an increasing number of articles saying that behavior may be a factor in decisions, and topics such as loss aversion, mental accounting, herding behavior, confirmation bias, and others have been appearing in the financial press. Wall Street acts as if knowledge of a behavioral factor in decision-making is a new discovery, but economists have been writing about behavior since the beginning of financial theory.
During that 18th century time when the Bernoullis were creating utility theory, economist Adam Smith was writing that loss aversion affected rational decisions and thus needed to be taken into account. Although Frank Knight’s 1921 book said that maximizing expected utility would be the decision process in a rational world, he also admitted that a psychological variable is a part of the decision process but that he didn’t know how to study it so he decided to ignore it. Even so, Knight said our “instincts” may account for the difference between rational decision outcomes and actual outcomes.
Finally, during the last half century as Wall Street modelers kept insisting on a rational world, their theories failed to explain results such as the Allais Paradox (1953), the Ellsburg Paradox (1961) and the kink in the utility curve demonstrated by Kahneman and Tversky’s Prospect Theory (1979). The knowledge that people’s decisions contain both rational and emotional elements has been known for 250 years, and the research amassed over the last 30 years has convinced even the biggest doubters that people’s decisions are seldom completely rational. Wall Street has been forced to talk about the behavioral factor because of the repeated failures of their computerized math formulas.
The problem is if Wall Street accepts that all of their financial models are flawed because human behavior is an unpredictable variable, meaning the rational decision will not always be made, then Wall Street would be forced be admit that they can do little more than guess about the future, but one doesn’t pay millions of dollars in annual advisory fees for “guesses”. And this is why the role of annuities will increase in the years to come as consumers move to a retirement vehicle based on guarantees and realize they do not want to base their retirement income on Wall Street’s guesses.
Serial Annuity Exchanges (8/09)
What I’ve attempted to do is look at the effects of these policy exchanges on an annuityowner by seeing what the annuity value becomes over time when the annuityowner stays with the original annuity and when policies are exchanged for new annuities with bonuses. To do this I’ve made several assumptions:
The assumptions reflect the issues in annuity yields and exchanges, and are not intended to be an exact mathematical model; however, the real world is not far off. The initial surrender charges of many products do approximate the amount of the up-front vested premium bonus plus the first year agent commission and they typically decline over time, but real world surrender charges may also be calculated on 90% of accumulated value or on the premium only. Another difference is the real world charges tend to remain level longer while mine decrease each year.
I played with different surrender charge assumptions doing multiple comparisons, but they did not affect the ultimate conclusion so I tried to be simple and consistent in my treatment. Regarding MVAs, altho the idea behind an MVA is that the annuityowner receives a higher yield because they are sharing some of the risk of interest volatility I have never seen any proof of this on renewal rates, so I ignored MVAs. While it is true that an MVA has, at times, reduced or eliminated surrender charges because interest rates have fallen since the policy was issued, this could also mean the old annuity is backed by existing bonds with higher yields and the new annuity would be backed by lower yielding bonds, resulting in less interest paid on the new annuity. In addition, there are offsetting times when an MVA results in higher charges than the surrender schedule listed.
I am also comfortable assuming that all insurance companies have the same amount available on a gross product yield basis. Having looked at annuity carrier investment yields over many years I find that they clump in a narrow band, and even ones with higher than average yields in one year tend to have lower than average yields in another, so it all seems to even out. If a carrier could show that they had discovered the annuity philosopher’s stone that would enable them to offer consistently above average yields, then this would be a legitimate reason to transfer to this insurer. Alas, no carrier is making this claim.
The annuity is out of both the surrender period and the deduction for the upfront charges (in this instance only the commission) in two more years and will earn 5% thereafter.
instance only the commission) in two more years and will earn 5% thereafter.
Second Annuity Annuity is $110,236 reflecting the $2,250 surrender charge. The $110,236 is credited with a 5% bonus resulting in a new accumulated value $115,748. The following chart reflects the accumulated and surrender annuity values for the original 20 year period.
Annuity is $110,236 reflecting the $2,250 surrender charge. The $110,236 is credited with a 5% bonus resulting in a new accumulated value $115,748. The following chart reflects the accumulated and surrender annuity values for the original 20 year period.
The bonus provides a higher accumulated value (Ex2 AV) for the next 5 years, but with a lower surrender value. By the end of the second annuity’s surrender period (Ex2 SV) the second annuity’s value is $8,420 worse than the Base Annuity, or $171,335 versus $179,755. At the end of the 20 year period the base annuity value is $252,933 and the second annuity value is $241,086.
The bonus provides a higher accumulated value for the next 4 years, but with a much lower surrender value. At the end of the 20 year period the base annuity surrender value is $252,933 and the third annuity value is $221,826.
Doing 1035 Exchanges cost the annuityowner $56,164 in lost account value
It may be argued this is not a fair comparison because it does not reflect the effect of income payout growth guarantees. However, if the exchange is not made the payout produced by the 20% income payout bonus in this comparison is exceeded by the actual account value of the first three annuities within one or two years. If all offer the same age based payout factors the value of the 20% income bonus is quickly matched or exceeded.
CD Rates And Market Movement Both Affect Fixed Annuity Sales (2/09)
Both stock market movement and CD rate levels strongly appear to have a direct cause and effect relationship on fixed annuity sales
I also said this correlation pattern was consistent and showed causality, meaning that falling or rising bank rates or stock market movement were causing the changes in annuity sales. I can build a strong case for causality going back a dozen years, especially for index annuities, but the evidence saying either CD rates or market movement affect annuity sales is much sketchier if I go back another decade
Part of the problem for the earlier years relates to differing definitions of what a fixed deferred annuity is and how sales should be counted. Some sales data I found separated group and individual annuity sales, others broke the world into flexible and single premium, and included group and individual sales on both sides. In many cases I was seeing three different totals with each labeled “total fixed annuity sales.” What I think I see f rom the mid ‘80s to the mid ‘90s is there was no apparent correlation between fixed annuity sales and either CD rates or the stock market. For example ,from 1984 thru 1990 the stock market rose and faltered and CD rates were higher than the previous year half of the time and lower the over half. Regardless of what was happening, annuity sales edged up.
cases I was seeing three different totals with each labeled “total fixed annuity sales.” What I think I see f rom the mid ‘80s to the mid ‘90s is there was no apparent correlation between fixed annuity sales and either CD rates or the stock market. For example ,from 1984 thru 1990 the stock market rose and faltered and CD rates were higher than the previous year half of the time and lower the over half. Regardless of what was happening, annuity sales edged up.
I think the reason is because individual annuity sales were so tiny – $12.5 billion in 1985 and still only $19.3 billion in 1990 – that any correlation was undetectable. So chastened, I will now restate my theory and say that both stock market movement and CD rate levels do have a direct cause and effect relationship on fixed annuity sales, but that the effect of CD rates is stronger. I’ll let you know if the future data supports my theory.
GLWB – Pricing Considerations & Reinsurance (5/07)
How well does the account value perform?
A more dynamic pricing exercise should include consideration of:
Reinsurance support is available as a risk management tool for the direct writers of these benefits. The most classic use of reinsurance for a direct writer is to substitute certainty for uncertainty, and this is of course the case here. Reinsurance of the GLWB is available in the marketplace. The direct writer can achieve a known and guaranteed cost of providing the benefit. reinsurance is less than the retail charge for the benefit, leaving a balance with the direct writer to cover expenses and contribute to profit.
reinsurance is less than the retail charge for the benefit, leaving a balance with the direct writer to cover expenses and contribute to profit.
benefit, leaving a balance with the direct writer to cover expenses and contribute to profit.
to cover expenses and contribute to profit.
Based on the retail pricing that I’ve observed on GLWBs and reinsurance levels available, most direct writers should be able to reinsure their GLWB and retain an amount to cover their expenses and contribute to their profit.
Index Methods Are Priced To Perform The Same (except when they’re not)
The index annuity “gain payer”, who is usually the seller of the options covering the hedge, uses past index performance history and a guesstimation of how other factors like yields on alternative investments, volatility and such will affect the index movement, and then says what potential upside will be offered on the 4 cents received. The gain payer’s task is to try to ensure that everyone gets the same ‘spin of the wheel’ for their 4 cents.
Just as a casino wouldn’t give better odds on one number at the roulette wheel the index annuity gain payer tries to ensure that the odds on the different crediting methods are also the same
What this means is that one annuity might offer, say, 100% of the point-to-point gain up to a 7% cap, while another gave 80% of the monthly average gain and still another used a 2.5% monthly cap forward-not loss structure to measure performance, because the gain payer believes that over the next year these crediting methods at these rates have the same odds in producing the same return. Does this mean that different methods perform the same each year? No. Different methods react differently to different markets. In 1998 averaging methods produced the highest index annuity interest, while in 1999 annual point-to-point with cap structures best rewarded their annuityowners. What the gain payer is betting on is that if their analysis, for example, showed that an 80% monthly averaging rate and an annual point-to-point with 7% cap produced the same returns over the long haul in the past that this will hold true for the future. The roulette wheel might come up showing 16 four times in a row, but over time the other numbers will come up and it will all even out.
Does this mean all index annuities will perform the same over time? No. Different products have different pricing structures based on carrier profit goals, commissions paid, and length of surrender period. This means one annuity might have 4 cents available from each premium dollar to use for the index-link and another has 3 cents and yet another has 5 cents. Ultimately, it is the carrier that decides how much money is available to fund the index-link. This is why I continue to believe that the most important factor in index annuity returns is not the crediting method, but how the carriers will treat the annuityowner when they reset that cap or rate in the future.
Suppose you find a carrier you can trust with an annuity offering a variety of crediting methods. My advice has been to split up the premium between two or three different methods, and put the policy in the drawer. My hypothetical backtesting models over the years have shown that the carriers set the rates each year so the yield potential odds are the same for each method over time. However, for the last several months when you plug in current rates for different methods and do a long time analysis for some carriers the returns are not all similar.
This chart backtests three actual products from three different carriers that offer multiple crediting methods within the product. I have applied each method’s current rates to calendar year S&P 500 Index movements from 1956 through 2006. Zeros have been substituted for negative years to reflect an annual reset methodology. The returns listed are the average yearly returns for each method at the current rate. I have not shown the specific rates or caps because the intent is not to compare the returns between different products, but to highlight return differences within each product.
In all cases the uncapped methods had average returns that were higher than the methods paying 100% of index gain up to a specified cap. The uncapped point-to-point option had average returns that were 41% higher in the first product and 59% higher in the second than the capped choice. What this says is that if rates stayed the same and history repeated – although both assumptions are unlikely – the straight rate choice would produce a much higher return over time than the capped option. Product returns using averaging methods were grouped more tightly, but the uncapped monthly average return was still much higher than the annual point-to-point with cap selections. Another finding of interest was the monthly cap forward options had returns similar to the annual cap methods and much lower than the uncapped choices.
Today the uncapped methods offer the best potential returns for next year (based on history)...
The difference in rates on different carriers offering identical methods is also higher than it usually is. Normally, products with similar surrender terms, commissions, minimum guarantees, and bonuses offer similar rates and caps when the underlying methods are the same. Today, I am seeing differences in carrier rates that do not seem to be justified by pricing or history. This means even if two products have identical features one could offer significantly higher rate potential for the coming year.
...but it is the carrier that ultimately determines annuity performance
Index Annuity Product Feature Bloat (5/06)
In the fall of 1996 Jackson National Life introduced the Equity Linked Index annuity, or ELI for short. Although only one crediting method was used, ELI offered five different surrender periods and five allocation choices, including the first international index. Whether because of, or in spite of ELI’s complexity Jackson National sales steadily rose and they became the top selling index annuity carrier for 1999. ELI was the industry’s first step into the “Swiss army knife” approach to index annuity product segmentation, but definitely not the last.
Does offering more and more features create more index annuity sales or simply dilute?
During the next eight years carriers attempted to outdo the competition by offering products with new bonuses, new crediting methods, new indices, multiple surrender periods, and insurers introduced features borrowed from other annuity lines such as nursing home, terminal illness and unemployment surrender charge waivers. How far can it go? Midland National Life offers an incredible 253 different strategies spread among their now 23 products – and that total does not include choices of different levels of initial premium or annuitization bonuses, and even products with three different commission schedules from which to choose. A producer looking at the Midland lineup has an almost infinite number of ways to configure the choices ultimately presented to the consumer. Most carriers have not stressed product differentiation to the degree demonstrated by Midland. Only one product is offered by fourteen of the carriers, and an additional eight to ten multiple product carriers tell essentially the same story with only minor modifications. However, the reality is the majority of index products do offer a multitude of choices and features that are all designed to make each standout from their neighbor. The question is – Does offering more and more features and variations, also known in marketing circles as “feature bloat” create more index annuity sales?
One method to determine whether the addition of new features cause product sales to jump would be to measure sales before and after the features were added. However, there are usually many other variables in play and I find it impossible to sort out the direct effects of adding a particular feature. For example, if a product adds two new indices and the product sales go up 10%, did the new indices cause sales to increase, or did sales increase because there was more advertising of the new product, or did the marketing support people spend more time talking about the product, or did sales rise because the product’s main competitor coincidently lowered their rates just as the indices were added. To examine the effect of feature bloat on sales I found it necessary to look at academic research.
Feature Bloat Does = More Sales (even when the feature isn’t needed)
Product differentiation is a classic marketing strategy wherein one attempts to create a meaningful competitive advantage on the basis of attributes that are relevant, meaningful and valuable to the consumer. Suppose a potential annuity buyer had a history of health problems that pointed to the strong likelihood of a nursing home stay and the annuity value would then need to be tapped. An annuity offering a nursing home waiver making cash value available without surrender charges would be a meaningful feature. But what if the potential annuity buyer was in good health, already owned long term care insurance, and had sufficient resources so that the annuity value would never be needed – would the nursing home waiver feature still be attractive? Based on my research the answer is yes, even though the feature is irrelevant in this situation it probably is positively valued by the consumer.1
Studies have also found a higher price could often be charged as more irrelevant features were added. The implication is an index annuity customer that only wants and needs a basic index product without bells and whistles would buy a different index annuity because the new product had more features, even though the features would not be used, and even if the potential return was lower. However, this does not mean that complexity in and of itself increases sales. A product viewed as too complex is less likely to be purchased.2
The message that needs to be presented is that the complexity is manageable, or that the product is not too complex when used as directed. In addition, the extra features must be related to the product in some fashion to be valued.3 Letting a consumer choose from amongst three different crediting methods, as opposed to one, is perceived as meaningful. But throwing in a color television with each annuity purchase is unrelated and not valued by the consumer. Many studies indicate that consumers favor products with high levels of features, even when they feel the overall usability is decreased. But after using the product the initial positive feeling fades and dissatisfaction is higher for buyers of the complicated product and lower for buyers of simpler ones. A recent study concluded “Our research suggests that too many features can encourage initial purchase but damage satisfaction and reduce repurchase probabilities”.4
The product with the most features wins...once.
What does all of this mean for index annuity providers? If your goal is repeat business from your annuity customers then you should avoid offering products with so many variations that the consumer will suffer from feature fatigue, or else they will probably select someone else the next time around. However, if the consumer purchase is viewed as a one-time event the product with more features should win against the product with fewer features, but shouldn’t count on repeat business.
1. Carpenter, Glazer, and Nakamoto (1994), “Meaningful Brands from Meaningless Differentiation: The Dependence on Irrelevant Attributes,” Journal of Marketing Research, 31 (August), 339–50
2. Mukherjee and Hoyer (2001), “The Effect of Novel Attributes on Product Evaluation,” Journal of Consumer Research, 28 (December), 462–72
3. Simonson, Carmon, and O’Curry (1994), “Experimental Evidence on the Negative Effect of Product Features and Sales Promotions on Brand Choice,” Marketing Science, 13 (Winter), 23–40
4. Thompson, Hamilton, Trust (2005), “Feature Fatigue: When Product Capabilities Become Too Much Of a Good Thing,” Journal of Marketing Research, 42 (November) 431-442
American-style Option – may be exercised at any time before it expires.
Asian Option – options that use averaging in determining either the strike or final price.
At The Money – the interest value is at the exercise price.
Basket Option – an option for which the underlying is more than one index. Example, an option that pays out based on the performance of the FTSE 100, Russell 2000 and S&P 500 would be a basket option.
Best-of Option – an option exercisable against the best performing indices. Example, a best of option on the Nasdaq and S&P 500 would pay out on the index that rose most during the term.
Call Option – gives the option buyer the right to buy an underlying security or index at a specified price on or before a given date.
Digital – one that pays out a fixed amount if the underlying index is above (or below) a specified level on a given date, usually the maturity date of the product.
European-style Option – may only be exercised on its expiration date
Everest – a structure that typically returns principal plus a bonus equal to a fixed amount plus the worst-performing gain from a given basket of underlying indexes.
Himalaya – the return is calculated as the average of the performances of the best index in each specified period during the term of the product. Once selected; however, the best performer is removed from the basket for subsequent periods.
Hindsight Option – a type that pays out at maturity the difference between the strike price and the highest (or lowest) level of the underlying index during the term. Also called a look-back option.
Intrinsic Value – the degree the option is in the money.
In The Money – the market value of the optioned interest is above the exercise price of the option.
Knock-Out – an option that matures early if the underlying index rises to a specified level during the term.
Option – a contract which conveys to its buyer the right, but not the obligation, to buy or sell something at a specified price on or before a given date; after this given date the option ceases to exist. Insurers typically buy options to provide the index linkage for the excess interest potential.
Out Of The Money – the interest value is below the exercise price
Put Option – gives the buyer the right to sell an underlying security or index at a specified price on or before a given date.
Rainbow – an option basket whose best-performing indices are weighted more heavily than those that perform less well.
Strike Price – the specified share price or index value at which the shares or interest may be bought or sold. If the strike price of a call option is less than the current market price of the underlying security the call is said to be in-the-money. Conversely, if the strike price of a call option is greater than the current market price it is out-of-the-money and would not be exercised.
Time Value – the cost or premium of the option above the intrinsic value.
Worst-of Option – a call option that is exercisable against the worst-performing index in a basket of indices.
Comparing Crediting Methods (7/05)
The index annuity buyer participates in the crediting method—not the index
No one method is inherently better or worse than another method. An Oldsmobile, Plymouth or Studebaker will all get you from point A to point B although each one rides and handles a little differently during the journey. There are no bad methods, only perhaps, a bad understanding of how a particular method really performs. The method that most closely mimics that of the actual index is Annual Point to Point multiplied by a participation rate. How does it work? If the index goes up 10% measured from the start of the contract year to the end, and the participation rate is 55%, the annuity would credit 5.5% interest. If the index went up 20% the annuity would credit 11% interest. That’s it – no caps, no spreads, no averaging. However, only two carriers offer annuities using this crediting method.
Why don’t more carriers offer this simple method? Based on my talks with producers it is because most producers say it is difficult to sell 55% participation. If that is so, let’s get an idea of the potential participation that is being sold. I calculated the annualized return for ten-year periods ending during the 1980s (71-81, 72-82...80-90) and 1990s (81-91...90-00) by applying a 55% participation rate to calendar years wherein the S&P 500 rose and crediting a 0% return in calendar years that fell. I then added up the ten 10-year period returns, divided the total by ten, and came up with average annualized returns for the ‘80s and ‘90s. I then worked backwards using the average returns produced by the 55% participation rate for each decade and determined what caps, rates or spreads were needed by the different crediting method to reach the same identical returns. If you applied a 55% participation rate annual reset method to the S&P 500 the annualized return for ten-year periods ending in the 1980s averaged 6.38%; the average for ten-year periods ending in the 1990s was 7.83%. The chart shows what other crediting methods needed to be to equal these returns.
What Does This Mean?
The illusion of higher potential returns
It also means that if your monthly average method had a cap of less than 13.5% or your monthiversary method kept a rate of less than 123% – looking at both the ‘80s and ‘90s – your effective participation rate is less than 55%. In fact, you would be hard pressed to find an annuity that would have given you as much as 55% effective participation in these two decades when you plug in today’s current rates. At today’s rates and under most back-testing “what ifs” index annuities would deliver 40% to 60% of index performance. If consumers get roughly half of the index return is that bad?
Consumers Need Realistic Expectations
What if consumers are being lead to expect “stock market like” returns from their index annuity? Then most of those doing the leading should pray for a really rocky market period, because if the future confounds the past and the stock market soars, the only high many index annuities might see are new lawsuits filed. The preponderance of the statistic forecasts and analysis I’ve conducted (guessing via computer) show index annuities performing like fixed annuities, which is what they were designed to do, and not like equity investments. Could index annuities generate “stock market like” returns if we had a repeat of the ‘90s? Yes, but long-term bond rates would need to significantly increase and those increases would need to translate into higher renewal participation on issued contracts.
Alternatively, a couple of currently offered term end point crediting method products that do not lock in index gains until the end of the surrender period (to be specific, ING MarketSmart and Jackson National Life Elite 90), could offer 75% or more of actual index gain in a ‘90s scenario if there was even a modest increase in long-term bond rates. The flipside is term end point methods also perform like the index in down times, so a ‘70s market scenario would mean returns for these products near the minimum guarantee.
I heard Mr. Tucker present this elegant and usable concept and asked him if he would allow me to share it with my readers. I encourage those involved in hedging on both sides of the annuity aisle to contact Rich Tucker at 973-783-3168 or Rich@ruarkonline.com. – Jack Marrion
Proponents of index annuities and variable annuities are typically mutually exclusive. Strongly held beliefs are found among distributors of each camp and these beliefs tend to migrate upwards to the insurance company manufacturers. The results are insurers that focus only on their particular world of variable annuities or carriers seeing only their own universe of index annuities. However, a look at possible synergies from a broad perspective and joint management of index annuities and variable annuities can create cost savings.
On the one side you have carriers creating variable annuities. Variable annuities are being enhanced to offer additional guaranteed benefits such as guaranteed minimum death benefits, guaranteed minimum income benefits, and guaranteed minimum withdrawal benefits. All of these guaranteed benefits are “put-based” benefits, meaning they produce value if the underlying funds decline. Insurance companies typically use reinsurance or hedging strategies to manage the financial risks of these variable annuity guaranteed benefits.
On the other side you have insurance companies manufacturing index annuities using “call-based” derivatives to manage the index participation formula. Call-based means they produce value if the index increases.
Reinsurance can be a mechanism to create this balance immediately. Companies with a heavy concentration in indexed annuities could assume reinsurance of variable annuity benefits, or companies with a heavy concentration in variable annuities could assume reinsurance of index annuities. I have found that this powerful risk management technique is not being utilized by the insurance industry today and could provide a win-win scenario for both variable and index annuity manufacturers.
|Copyright 1998-2013 Jack Marrion, Advantage Compendium Ltd., St. Louis, MO (314) 255-6531. All information is for illustrative purposes only, does not provide investment or tax advice. No index sponsors, promotes, or makes any representation regarding any index product. Information is from sources believed accurate but is not warranted. Advantage Compendium neither markets nor endorses any financial product.|