Hi LC
A while back I did a comparison: A constant ratio plan at 50% ratio, a constant value plan that starts with half in stocks. Today I compared them to AIM BTB.
Here is the stock prices I used, $10, $7.5, $5.0, $$7.5, and $10.
AIM works well under mean reversion. That scenario however is just one of many.
Prices might rise and then continue to rise further.
Prices might fall and then continue to fall further
Prices might rise and then decline back down.
Prices might decline and then rise back up.
Prices might rise and then stay up/flat
Prices might fall and then day down/flat.
Japan 1990 to present is one example of a down and stay down/flat case.
The whole thing about six sigma/black swan etc. is easily explained. Stock price changes over time can be simply modelled using two random generators. One fires regularly and at each trigger results in a relatively small move either up or down. The other fires less frequently but triggers a larger move up or down. A characteristic of the second larger random trigger event is that having fired it is more likely to fire again sooner rather than later (periods of high volatility cluster around similar points in time).
For each particular add/reduce style the one where the particular share price motion best fits the add/reduce method used will result in that method providing the better reward.
AIM does a reasonable average job across all cases. The constant value method however is also good - even better where low/inverse correlated holdings are tracked.
The Permanent Portfolio for example has very linear capital value, typically with low draw-downs so the value of the set remains relatively constant in real terms. The individual components however, particularly stocks and gold have high volatility. Which implies that as one is down, the other three counter balance those 'losses' and keep the total fund value around similar levels. Which in turn means that when funds are moved from the others into the one that is down then the maximum amount of rebalance is added to the one that is down.
e.g. if $10,000 is invested in four pots ($40,000 total) and later one has declined to $3000 and the other three have collectively risen to $37,000 in value, then the set is still valued at $40,000 total and the rebalance results in $10,000 exposure in each of the four pots.
AIM in contrast can exhaust cash (reach a point where 'rebalances' no longer can be made until a particular event occurs). AIM however scales its trades in a manner that sort of AIM's the particular sequences that have previously occurred. For example if a down, down sequence has been encountered then it stakes more on the next sequence being up side biased.
Rebalance benefits are however generally small, much smaller for example than the potential rewards from having bought stock relatively cheaply.
The amount initially paid for stock is critical. Buy at too high a price and longer term rewards can be less than inflation. Buy and sell at fair prices and the rewards are ok (real (after inflation) gains achieved). Buy at a relatively low/cheap price and later sell at a relatively high price and rewards can be outstanding.
A more important factor therefore is not which particular rebalance settings/style are used, but more that you don't overpay for stock in the first place. This is where AIM's cost-averaging coupled with the likes of vWave performs a reasonable job.
Best. Clive.
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