Minimum buy orders still matter. If you eliminate this factor, the AIM algorithm has you trading as soon as price changes greater than the SAFE value. With no minimum trade size, this could result in trades that are insignificant. Here's an example.
Using the standard AIM method, the next buy recommendation is at $9.08 for 1 share, and next sell recommendation is at $11.13 for 1 share. For the full 10% price drop to $9.00 the buy order is still only 6 shares, or $54 transaction on $5,000 invested. Hardly worth the effort, don't you think?
Now, add a 5% minimum trade size to the calculation, and the minimum order is 25 shares at $8.69 or $11.77 for buy and sell price, respectively.
A 10% minimum trade size bumps this to 50 shares at $8.33 or $12.50.
I initially thought I could eliminate the minimum trade size when designing my AIM spreadsheet, but realized it's a necessary part of the algorithm, even with no transaction costs these days.
I suppose that instead of subtracting the SAFE value, one could simply use it as the trigger point to make a trade. If SAFE was set at 10%, then the purchase would be 10% of the share value at the point where price moved 10% in either direction. Perhaps that's how you're doing it.
Today, with commissions being very low or even nonexistent, I’m not sure minimum buy orders matter as much anymore.
I still use StockCharts' "Zig Zag" to help determine (in retrospect) the overall round trip that has been good for both trades and profits. (More trades with less profit/trade can sometimes be better than fewer trades with a greater round trip profit) That helps me determine what the Hold Zone should be. I then structure the SAFE and minimum trade size to approximate that hold zone size.
For instance, on my "income" type investments I generally use a larger minimum trade size than on "growth" type investments. I don't want to shed income shares, so I further use a cash reserve upper limit as well. Most are capped at 20% or 30% max cash. I then use vealies to keep the income invested portion at or near that maximum cash level in a long upward trend. Yes, this adds some complexity, but it is really just a 'look and decide' type of thing. If I see that the cash is 29% with a 30% upper limit, when AIM's suggesting a sale of 10% of the position, I have a choice, 1) make the trade and over-shoot the cash max 2) maybe sell just 5% of the position instead of 10% and therefore not over-shoot the cash cap by as much or 3) do a 'vealie" to move the sticks for the Next Buy and Next Sell targets and keep near that max level of cash. I've nearly never run out of cash during drawdowns, so the holding delivers good yield with just occasional AIM trades.
(30% ZigZag equates closely to 10% SAFE + 5% min trades in both directions. It also could be 10% Buy SAFE, Zero Sell Safe and 10% Minimum Trades.)
It was AIMer, Don Carlson, who first showed me the Zig Zag feature on StockCharts. It's been good for helping to pick what historically has been the right combination of round trips and profit/round trip. Too many round trips at too small a profit might not be as good as fewer round trips at a juicier profit/round trip.
This board continues to bring interesting ideas to the general AIM discussions and some nice refinements to Mr. Lichello's business model.
I have found through my extensive backtesting that for lower volatility investments, the smaller nuggets approach provides the best return. In higher volatility investments, the shovel is bigger for larger nuggets. I had the Grok AI do extensive modeling of the AIM model to determine optimal settings based solely on volatility. This was based on 10,000 Monte Carlo simulations at each volatility level, assuming a 50/50 split, and no drawdown curve or black swan strategies. If the model ran out of cash, it was stuck with no activity until price recovered.
This model generally agrees with what my backtesting shows, but the cash management strategies do have an impact. So I'm currently doing extensive backtesting of ETFs with the same conditions for each test. 12 ETFs with 3 backtests each of the various settings, and plotting returns to see my crossover points for selecting the optimal setting mix. Halfway done, and many hours remaining, but I think it will be more accurate for my methods than the general model the AI produced, which I'm posting again. Using optimal settings to squeeze out an extra point or two in annual return can add up significantly over the years.
Overall, I get the impression that Mr. L’s philosophy was more about consistently picking up small “gold nuggets” along the way rather than trying to hit a home run.