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Back-Testing the Robert Lichello Automatic Investment Management (AIM) System for Timing the Stock Market

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Doug is a Systems and Industrial Engineer with a master's degree. He lives in Gilbert, Arizona.

Explore a test of Robert Lichello's AIM system for timing investments.

Explore a test of Robert Lichello's AIM system for timing investments.

Many have said the most important purpose for investing is to make money. In order to make money, we face two key decisions: when to buy and when to sell. Simply put, we must buy when prices are low and sell when prices are higher than the buy price.

The difficulty is in the implementation. Our emotions work against us; when markets are rising, there’s a jubilation that makes it very easy to join in and buy when prices are high and moving higher. When markets are low, it can seem like there is no bottom and the market will never bounce back, which makes it easy to follow the herd and sell low.

A System to Reduce the Emotion of Investing

Ideally, what we need is a system that will reduce the emotion of investing by automatically telling you when to buy, sell, or do nothing. In the late 1970s, Robert Lichello published a book titled How to Make $1,000,000 in the Stock Market—Automatically, which presents a stock market timing system that claims to do exactly that. In this article, we will briefly explain this system then back-test it to see if there is any credence to these claims.

  • If you are already familiar with the basic AIM system but would like to see a more detailed analysis, go to this article: Sensitivity Analysis.
  • If you want to see how to use the AIM system in a multi-ETF portfolio, go to this article: Multi-ETF Analysis.

What Is AIM?

Robert Lichello named his market timing system Automatic Investment Management or AIM. AIM is an algorithm that provides a logical system for managing your investments. It can be used with a stock or mutual fund portfolio. This system will instruct you when and how much to buy or sell.

To calculate AIM’s buy and sell quantities, you need to know two things: how much money you have invested in the portfolio and the current value of your portfolio. To illustrate, let’s run through a couple of examples.

Example of a Buy Order

  • Portfolio Control (Amount of initial investment) = 1000 shares @ $10 per share = $10,000
  • One month later the stock price falls to $8, Portfolio Value = $8000
  • Add 10% to the current portfolio value = $8800.
  • Subtract 8800 from 10,000
  • Which equals = $1,200

Note, a positive value indicates a buy signal. However, if this value were negative, then AIM is telling us to hold.

Because the value of your investment has decreased, AIM has signaled you to buy 150 shares, the equivalent of $1,200.

One of the interesting features of AIM is each time that you buy more shares, your portfolio control increases by half the purchase value. In this case, the portfolio control would increase to $10,600. This is a built-in risk regulator that will stop you from exhausting your cash reserves when the market is going down or building too much of a cash reserve when the market is going higher.

Example of a Sell Order

  • Portfolio Control (Amount of initial investment) = 1000 shares @ $10 per share = $10,000
  • One month later the stock price rises to $13, Portfolio Value = $13,000
  • Subtract 10% from the current portfolio value = $11,700
  • Subtract $11,700 from $10,000
  • Which equals = -$1,700

Note, the negative value indicates a sell signal. However, if this value were positive, then AIM is telling us to hold.

Because the value of your investment has increased, AIM is telling you to sell 130 shares, the equivalent of $1,700.

In both cases, AIM has you making the correct decision—buying when your portfolio value goes lower and selling when it goes higher. If AIM is strictly followed, it can be used to take much of the emotion out of investing.

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AIM Websites

AIM in the Real World

So, does AIM work in the real world? To answer this question we will use historic stock prices and run the AIM algorithm through its paces. We will use historical prices of one of the most active exchange traded funds (ETF), The S & P Depository Receipts, stock symbol SPY. SPY is an ETF that tracks the Standard & Poors index of 500 stocks.

From January 2000 to July 2016 the SPY price history has ranged from $68.11 to $217.12. During this period there has been two downturns in the stock market, one 5-year period of increasing prices and of course the current price increases since March of 2009. So we can test AIM through a couple buying phases, at least one selling phase, and get a read on the current market.

Now, let’s look at the results of the back-testing which is summarized on the time series graph shown below. All buy and sell transactions are noted with yellow text boxes that show the month/year, quantity bought or sold and closing price at the end of that month. Additionally, buy transactions are denoted with red markers, sell transactions denoted with green markers.

robertlichelloaimsystem

Results of the Back-Testing

The first thing we notice is that the initial purchase of 68 shares on 1/3/2000 is very near where the market peaked in August of 2000. Then as the market fell for the next two years AIM had us accumulating a total of 79 shares over seven distinct buy signals in February, March, August and September of 2001, and June, July and September of 2002. During this buying phase, we used up a most of our cash reserves leaving us with $2,919 in cash "insurance" should the market continue to decline. Additionally, our number of shares has increased by 116% from 68 shares to 147 shares, more than doubling our "potential" increase in equity value when the market trend turns up. Assuming FIFO accounting our average price per share has been reduced from $143.80 to $121.21.

After the market bottomed in 2002, we experience a 5-year period of rising prices. During this period, AIM would have us selling a total of 42 shares at five distinct selling opportunities in January and December 2004, February and October 2006 and April 2007. At the end of this selling phase AIM has us building up cash reserves to $9,989 and we are holding 105 shares. Average price per share is $78.85.

From the market peak in October 2007 there is nearly a straight-line tumble until February 2009. During that freefall, AIM has us accumulating a total of 117 shares over six distinct buy signals from September 2008 to February 2009. At the end of this accumulation phase AIM has almost depleted the cash reserves to $809 and we are now holding 222 shares at an average price per share of $97.86.

Finally, the market picked up from March of 2009 through July 2016. During that period AIM issues 12 sell signals for a total of 124 shares. At the end of this selling phase AIM has us building up our cash reserves to $21,149 and holding 98 shares at an average price per share of $82.76.

Conclusions

In spite of the initial purchase being close to a market top, the overall portfolio performance is not bad. As of 7/31/16 the hypothetical portfolio consists of 98 shares of stock and $21,149 in cash reserves for a total of $44,164 or a gain of 120.8%. Employing a buy and hold strategy would have resulted in a total of $31,839 or a gain of 59.2%.

AIM appears to do a good job of inventory management and control as exhibited by our cash reserves increasing by 111.5%, our share ownership increasing by 44.1% and the average price per share of $82.76 which is a redution of 44.2%. However, one risk came out during the second accumulation phase, we very nearly ran out of cash in April 2009. We had only $809 (4% of the total portfolio value) to buy more shares, nearly exhausting our cash reserves.

During the two market downturns AIM caught both bottoms with buy signals, on the up side AIM missed selling at the 10/2007 peak.

Overall the AIM system appears to do a good job of identifying key buy/sell points. If you are disciplined enough to act only when AIM tells you to buy/sell much of the emotion of investing can be eliminated.

If you are interested in obtaining the source data for this analysis in spreadsheet form, send an email to dougburkeaz@gmail.com with the words “AIM Back-Test” in the subject line.

Assumptions for Back-Testing AIM

It is always necessary to make some basic assumptions when doing an empirical analysis. Here is the list for this analysis:

  1. Initial amount to invest in the stock is $10,000
  2. Cash reserve of $10,000 for future purchases
  3. AIM decisions are based on the closing price of the stock on the last trading day of each month
  4. Buy or sell price is the open price of the stock on the 1st trading day of each month
  5. Buy or sell order not executed unless the order is +/- 5% of the equity value
  6. Stock trading commission is $10.95 per trade
  7. Rate of return on Cash reserve is 2% APR
  8. Dividends distributed into cash account, not reinvested

This article is accurate and true to the best of the author’s knowledge. Content is for informational or entertainment purposes only and does not substitute for personal counsel or professional advice in business, financial, legal, or technical matters.

Comments

Eric on August 29, 2020:

I have had amazing success with leveraged etfs. Wondering if adding to portfolio control on sells would be beneficial. I was thinking 10% of the sale. Trying to keep cash no more than 50% PC and needed to do a vealie which got me thinking that adding a percentage of a sell would be the same. Your thoughts?

Sunil237 on February 03, 2019:

Thank you for the great article. I am new to AIM and playing around with UPRO with AIM 50/50. thanks for everyones insightful comments

Mark C Thomsen on April 25, 2018:

I read AIM many years ago and have used it but not recently. I am interested in comments from Jeff about using LEAPS with AIM. I also would like to hear what ETF's have been used successfully.

Leveraged Investo on April 14, 2018:

Forgot back tested results.

https://www.portfoliovisualizer.com/backtest-portf...

Leveraged Investo on April 14, 2018:

Here is a $10,000 back tested portfolio of TQQQ/TMF for the last 7 years. Quarterly rebalancing and adding $3000 quarterly. You are buying cheaper shares on the way down of a volitable ETF. TMF protects the leveraged ETF from large drawdowns. The US Mkt Correlation number is the key and you can adjust this by the amount TMF in portfolio. It compares favorably to the 2 bear markets of 2001-02, and 2007-08. Some investors go to higher bond % when below 200 day moving average. I prefer not to sell, except if necessary for re-balancing for tax purposes. I can borrow at a very low margin rate at Interactive brokers if money is needed. You get about 2.3 leverage on the upside with protection on the downside. Works well on UPRO 3 x SPY also. Perhaps incorporating your system might give better returns? Any comments would be welcome

ThinkSmartNotHard on March 31, 2018:

I posted this on another board, but I think it's worth repeating. I've looked at the various equity/cash thresholds, but they all don't address the fact that over time, the portfolio control will grow to have a positive sell bias because it's underweighted from ignoring the expected growth in the market.

It seems an obvious choice might be to make a subtle tweak in the algorithm itself by adjusting the Portfolio control. There are a couple of thoughts, but the simplest might be to adjust the portfolio control by increasing the value monthly [or based on whichever time frame is selected] to factor in an annualized average market increase. Let's say that average is 9.8% per year.

Every time you run the algorithm, you would increase the portfolio control by adding the adjusted annualized increase of the initial equity investment. So for example, if you put in 5K the first month. The second month, the average annualized increase should be roughly 5040. So when comparing the stock value, you would compare it to the updated portfolio control. The following month, the portfolio control would be updated to 5081 and so on. If the stock is a dividend yielding stock, you could reduce that percentage by subtracting the annual dividend yield.

Of course, you could adjust the annualized percentage to fit the average return for that sector in the market. There also could be a few more complicated options that factor in original, historical, medium, and short term averages. Another option is peg the Portfolio control to another algorithm based on PE ratio for that stock. Again, the PE ratio could be a historical average for the stock, sector, or overall market and could be modified to factor in long, medium, & short term trends.

You could consider a weight of say 1/3 historical, 1/3 3-year, & 1/3 1-year performance for the annual rate of return and/or the PE ratio used to adjust the portfolio control. This way, you could benefit from trends in an up market and reduce risk in a down market while keeping the portfolio control at a reasonable value that doesn't lose it's significance over time.

Jeff Weber on February 22, 2018:

I have been using AIM with long-term options (LEAPS) on Dow Jones stocks like CAT, MRK, AXP, and it works great. A 10 Dow Jones portfolio of LEAPS is up 344% in the last 49 months or $60,000 ($30,000 cash, $30,000 LEAPS) is up to $266,000. AIM works! I even wrote my own AIM book Here Are the Customer's Yachts available on Amazon. I ever added a Bear Strategy for AIM for both stocks and LEAPS. And I write a monthly AIM newsletter that is free for people who buy my book.