No. of Recommendations: 9
[this should probably be marked "off topic", or on the mechanical investing board, but since you asked here I'll reply here--apologies to BRK purists]
The original suggested way to run the screen (by no means mandatory) went like this:
(1) Buy equal dollar amounts of the top 40 ranks
(2) Hold for two months
(3) Calculate fresh picks. For every current position(s) no longer among the top 45 ranks, sell and replace with the highest ranked pick(s) you don't already own.
(4) Go to step 2.
(* see note at bottom)
This is silent on how often you'd rebalance. The two months is the hold period and trading cycle, but the rebalance cycle may be different.
A "rabalance" involves doing all the small trades needed to get all positions back to equal weight.
On a trade date that was not a rebalance date, you'd usually do this: calculate the total market value of the N positions you're selling plus any dividends received since the last trading day, and put 1/N of that cash total into each new position you're buying. So new positions are equally weighted among themselves, but might be a little bigger or smaller than the average of the positions you are not touching, which may vary amongst themselves. This is what I usually do.
The two typical ways to run an MI screen would be to do a full rebalance every single time (lots of small trades, rarely worth the bother), or to do it only every once in a while, out to (say) once a year. Those are both pretty easy to test, given the right backtester.
In reality, it generally doesn't matter a whole lot. The difference in returns is well within the statistical noise of any backtest, and in any case is small. So a totally acceptable approach is like this: if some position has become noticeably larger than the others, trim it back to the average size the next time you are selling and buying, but otherwise ignore rebalancing. I don't have a feel for what constitutes "noticeably bigger", but personally I wouldn't mess with something until it's at least 40-50% bigger than average. With a 40 stock portfolio, that's still not exactly a concentration risk: average position is 2.5% of portfolio, versus 7.2% for SPY which lots of people consider acceptable. FWIW, I have done no rebalancing in the last six months and my largest position in this screen is currently only 32% above the average. Most of these big boring positions track the index (and each other) relatively closely.
In this specific case of LargeCapCash, the backtests show only very slight differences based on the rebalancing frequency. Assuming a fairly generous 0.4% round trip trading cost, if you are running the version which requires a dividend, then the highest returns are seen in the backtest that rebalances every time (every two-month hold period), but rebalancing every 10 months is almost the same return. I do the latter. If you're running the version which does not require a dividend (which has a worse overall backtest return), then the backtest suggests it's best to rebalance annually, not every two months. There is a good chance these differences are just statistical noise. There is also a possibility that it's meaningful: perhaps dividend paying firms mean revert on a different cycle on average (less multi-season trending) so it's statistically not as worthwhile to let the winners run as long? Beats me.
Jim
* Note
Another good way to run this, not previously mentioned in the context of this screen, is pretty similar. This is called the "dozens" approach on the MI board.
(1) Your first day, buy equal dollar amounts of the top 20 ranks with half your portfolio's cash.
(2) Two months later, buy equal dollar amounts of the top 20 ranks you don't already own, using up the other half of the cash.
(3) Two months later, sell all the picks you've held for four months and replace them with equal dollar amounts of the top 20 ranks you don't already own using up all the cash in the account. Typically about 18 of the 20 positions will be held over rather than sold.
(4) Repeat step 3 over and over.
Thus every position is held four months, but it's like two separate portfolios with their trade dates staggered by 2 months. Once in a blue moon you'd want to check to see that both "sub portfolios" are staying about the same size. Though the backtests of this and the "original" version at the top are extremely similar (well within statistical noise), it weakly suggests this variant has a hair higher returns (0.1%/year) and a hair fewer trades per year (17% fewer).
