Flaws in the Traditional Theory

The traditional theory is hopelessly flawed. It leads to unnecessary and costly mistakes. It can lead to busted retirements.

Traditional Strategies

Before the bubble burst, the theory held that the S&P500 is the best possible portfolio (on average). Early researchers asserted that there is no way to exploit valuations. You are only able to observe them. This led to the 4% rule.

The 30-Year Safe Withdrawal Rate, it was asserted, is the lowest 30-Year Historical Surviving Withdrawal Rate. The best stock allocation, which maximizes the lowest 30-Year Historical Surviving Withdrawal Rate, is very high, almost 80%. Or so it was claimed.

None of this holds up to close scrutiny. We have shown that Safe Withdrawal Rates are sensitive to valuations. At today’s levels, a fixed 80% stock allocation has a 30-Year Safe Withdrawal Rate close to 3.0%. In contrast to the assertions, a fixed 50% stock allocation does better. It has a 3.5% 30-Year Safe Withdrawal Rate.

Better yet, a mechanically varying allocation based on valuations lifts today’s 30-Year Safe Withdrawal Rate above 4.5%.

Modified Traditional Strategies

Slice and dice became popular when the S&P500 failed to live up to expectations. Once again, researchers asserted that there was no way to exploit valuations. You can only observe them.

Slice and dice isolates market segments. The magical solution is to rebalance among slices to maintain fixed allocations. Once again, the theory delivers less than desired.

We discovered that rebalancing almost always gives up a huge upside potential while offering very little in the way of downside protection. We discovered that, since the different slices have predictably different returns, slice and dice drags down the overall portfolio. The rebalancing bonus is only a mirage. It is meaningful only if all returns are identical. They never are.

We can do better. Even with individual slices, we gain by exploiting valuations.

Why the Theory Failed

Apparently, the theory failed because of data availability. Researchers placed more emphasis on the number of data points than on the information that the data contain.

More specifically, researchers erred because they used monthly data.

Using monthly data removes almost all of the effects of valuation. I discovered this in my investigations into Managing Downside Risk in Financial Markets (using the Sortino Ratio).

Makings matters worse, many researchers pay little attention to timeframes. I see short term projections, trading strategies, but not investment strategies. I see single year returns. Seldom do I see projections ten years into the future.

The effect of valuations is weak in the monthly data. It is dominant at Year 10.

There are other flaws as well.

We need to see confidence limits routinely placed about projections. Showing statistical significance is one thing. Including the range of probable outcomes is another.

Sensible people would ignore most refinements to an estimated total return if they were aware that the outer confidence limits. A refinement of 0.2% or 0.3% makes little difference if the confidence limits are plus and minus 6%. Yet, those are the Year 10 outer confidence limits (if you include the effect of valuations, wider if not).

Opportunities

By focusing on valuations, we have been able to identify opportunities. We have found that intermediate term timing based on valuations makes sense. In addition, we have found that dividend strategies make a lot of sense. Dividend based strategies allow us to increase our income well above 4% (plus inflation) without needing to be concerned about living beyond our finances. Exceeding 5% (plus inflation) is straightforward.

Have fun.

John Walter Russell
February 28, 2007