Sent: 19-05-2009 13:09:01
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Are Average Returns Yesterday's Scraps?
A few weeks ago I wrote a column about modelling commonly used in financial planning.
In Australia we tend to use an average return which is designed to show the return of a range of investments over a period of time. The theoretical argument for this approach will be that over long periods returns become predictable and revert to the mean.
US financial planners tend to use "monte carlo simulation" which is defined in my dictionary as "a technique in which a large quantity of randomly generated numbers are studied using a probabilistic model to find an approximate solution to a numerical problem".
On 5 May 2009, the US-based Financial Planning's daily news email carried a story that said US planners were rethinking monte carlo simulation tools because the technique tends to ignore findings which are beyond plus or minus two standard deviations of the mean and recent market extremes were often not on the radar.
Financial Planning's article concludes that "Monte Carlo simulators should be updated to include a larger number of scenarios that assume greater volatility, say critics, including the Retirement Income Industry Association."
So if thousands of iterations are not acceptable (perhaps because the initial data is not acceptable or deemed inadequate) where does this leave the use of single average returns?
At the end of April, Knowledge@Wharton, a publication of the The Wharton School of the University of Pennsylvania ran an article titled, "Why Stock-price Volatility Should Never Be a Surprise, Even in the Long Run". The article is an interview with the academic Robert Stambaugh a finance and economics academic at Wharton who produced the paper, "Are Stocks Really Less Volatile in the Long Run?" with Lubos Pastor which you can download for free from a number of websites.
As Stambaugh points out in the Wharton interview, "when we think about volatility in the stock market, we think about the value of the market fluctuating, typically around some sort of trend or long-term expected rate of return. Our work makes the point that uncertainty about that trend itself adds to the uncertainty that investors face and should be perceived by them much like volatility -- much like the fluctuations around the trend. That uncertainty about the trend itself becomes more important the further into the future you project investment outcomes. So our paper basically makes the point that to an investor with a long horizon, stocks actually are riskier per period. That is, the rate at which risk grows over the horizon such that it makes the investment riskier over the long run. This is basically in contrast to what we think of as more conventional wisdom that says over the long run, fluctuations in the stock market will to some degree cancel each other out and, therefore, make risk to an investor in the long run look [smaller] per period than [it would] to a short-run investor."
It is interesting to note that all of the calculators which ASIC offer on their consumer website (Fido) also use either single number average returns or single numbers for different risk characteristics.
How much longer will this be considered acceptable?
One could also add to this is issue of longevity.
On another note, it has been reported that the Henry Tax Review is beginning to believe that the super tax concessions are too generous.
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