Mark Hing | Automatic Investor

By Mark Hing (originally published in the March 2000 Issue of Computer|Sense Magazine)

The bulls are running in the streets. Not like they do in Pamplona, Spain, mind you, instead they represent a sustained rising stock market. Stocks have been advancing for over a decade, and show no sign of abating. I think Superman best summed up this technology-fueled run when he said, “Up, Up, and Away.” Some of the more optimistic among us cling to the words of another great hero, Buzz Lightyear, and join his shouts of, “To Infinity and Beyond.” Unfortunately the bulls won’t last forever, they’ll eventually tire. Then the bears will have some fun.

In the meantime, however, people from all walks of life are jumping on the stock market bandwagon. And why not? With a forgiving market and annual returns of over 100% within reach, what’s not to like? In a market where a trained monkey can make money, smiles abound. However it’s a wise person who plans ahead. Knowing what to do before jumping on the bull can mean the difference between investing and gambling – wealth and bankruptcy, or at least making a few bucks and having to meet a margin call. The trick is to know how to manage your risk.

Rather than trying to make a quick profit, you should be looking to minimize your downside risk. The key concept, that bears repeating again and again, is the preservation of capital. No capital. No investment. No profit.

Of course in heady times such as these, it can be difficult to remember such concepts. So far, all downturns (or corrections) have resulted in a buying spree that serves to send stock prices right back up again. It wasn’t always so in the past, and it won’t always be so in the future.

Therefore it makes sense to assess yourself. Your strengths, your weaknesses, and your tolerance for pain – or risk as they like to say in the financial world. If your stock portfolio dropped 70% next week, and stayed down for the foreseeable future, how would it affect you? Would your lifestyle be affected significantly? Would you have trouble sleeping at night? Would you sell at a loss and vow never to invest in stocks again?

These questions will help you determine whether you’re sufficiently diversified amongst the various asset classes (i.e. stocks, bonds, real estate, money market funds, etc.). Your answers will also tell you whether you should be in the stock market at all.

If you’re still game, the next step is to formulate an investment plan. If you’re in for the long haul, a “seat of the pants” strategy is not going to work. Granted, it may work in today’s investment climate. But long term? Forget it.

Once you have a well thought out strategy (and you’ve objectively assessed yourself), stick with the plan – day in, day out. Be consistent and logical. And watch out for the dynamic duo of killer emotions: greed and fear.

By Tom Veale

The Idiot Wave name actually started as a play on words. In the 1980s, Robert Prechter popularized the Elliot Wave Theory. I guess it was just too good a fit. Since I’m gauging market risk, it seemed natural to say “Well, I wonder what the idiots are doing to the market today?”

Value Line Investment Survey has been one of my most reliable sources of information since the early 1980s. It’s available at most public libraries in their “1700 Stock” version. The Index section contains some very good screens. My favorites are “The Best/Worst Performing Stocks (Last 13 weeks)” on page 33. Here, at a glance, you can see 82 different stocks and how they’ve performed over the last quarter. I noted that market speculation seemed to be nicely displayed by these two charts. If the “Best” were soaring while the “Worst” weren’t too bad, it usually meant the market was getting to be over-bought. The opposite is true when the “Worst” are just awful and the “Best” aren’t doing much exciting. This became the first piece of the Idiot Wave.

Elaine Garzarelli gave a talk once about the correlation of interest rates and price/earnings ratios. She claimed there was a sort of “magic number” equal to 20. It was the long-term average value. If P/E plus the interest rate was greater than 20, by very much, then the market was over-bought and visa versa. She felt that + or – one point was the neutral range. When I tried this with the 52 week U.S. Treasury rate and Value Line’s P/E, I was amazed by how well it worked. That was the second piece.

One of my favorite books on the market is Norman Fosback’s “Stock Market Logic.” Almost every market statistic is explained and in many cases improved upon. One of my favorites is his “NYSE Hi/Low Logic Index.” It states that if everyone is in general agreement about market direction, then the number of new highs or lows will be very small. If the market is confused about its next move, there will be large numbers of new highs and lows simultaneously. This has proved to be a good way to confirm other high and low risk market events. I applied his formula to the NASDAQ Composite to see how it would do and have been pleased with the results. My only problem with the data is that there’s a seasonality factor near the end of the year – during “Tax Selling Season.” Then it seems that the “bad” get worse and the “good” get better. However it was good enough to add to the Idiot Wave, and component three was born.

Finally, a peculiar market condition in 1993 brought about the addition of the forth and final component – Zeal. The Idiot Wave had been very good right up to 1993. However, in that year we had a massive IPO surge. The NASDAQ Composite Index added about 800 issues to its usual count of 4200 in just one year! My “Speculation” index went flat, even though I knew there was lots of speculating going on. My Idiot Wave was not measuring it.

The solution was there, all I had to do was apply the data I already had. I started to measure the percentage of change in the number of issues on the NASDAQ and NYSE over about a 10 to 13 week period. If the number was increasing rapidly, this showed speculation in a way missed by my other measures. If it was decreasing, money was then concentrating in the remaining issues and showed low speculation.

Decreases were bullish and increases were bearish. The range is very small. A percentage less than 0.0 is bullish while an increase of more than 2.0% is bearish. In 1993 Zeal peaked at 8.6% and the following year was a consolidation DOG.

Thinking back, I find it hard to believe that I’ve collected so much data! When the four components are united as either being bullish or bearish, the Idiot Wave is a great device for confirming what AIM is doing.

When it’s a mixed bag and the Idiot Wave is in its own Average Risk range, there’s not as much to be learned from it. I scaled the grand total by weighting each component so that the Idiot Wave would correlate to what a rational Cash Reserve might be for the market conditions.

Everyone loves cash. The problem is that it’s the one thing that seems to slip away as soon as you have it.

Whether it’s a set of dining room chairs, a new car, or the weekly groceries, cash is usually in short supply and heavy demand. And it doesn’t stop with the consumer goods. Stock market investors face the same situation.

Indeed, many investors are quick to jump into the market with both feet (some even use margin, the equivalent of jumping in headfirst). If a stock they’ve been following looks particularly enticing after a recent drop, some find it hard to resist the sweet strains of, “buy me, I’m cheap! buy me, I’m cheap!” However is it really a good idea to plunge right in? Perhaps not.

No matter how good an opportunity seems, there’s usually a better one around the corner. If your hot stock just dropped 10%, who’s to say it won’t drop another 10. If you bought less, and kept some cash on hand, you may pick it up at a cheaper price tomorrow. Or another quality offering may be down the next day. If all of your money is tied up in hot stock 1, you may have to miss out on hot stock 2 – or sell hot stock 1 at a loss. How many times has that happened to you?

The trick is to do things in moderation. Rather than betting everything at once (that’s greed talking to you), it’s usually better to spread your investments around. That’s called diversification and it’s a cornerstone of good investing. And what better way to diversify than to keep some cold hard cash on hand. Of course in the heat of the moment, that can be difficult to understand (and that’s why you need a good investment system).

In addition, cash in an interest bearing account is pretty darn safe. So you’re not only earning guaranteed interest, but you’re also reducing your portfolio’s market risk.

You’ll sleep better and be able to jump on opportunities that your fully invested neighbor can only dream about.

Jesse L. Livermore was born in 1877 and began his career at the tender age of 15. Over the course of his life, he developed a set of trading rules that are just as relevant today as when they were first created.

Although Livermore was a trader, rather than an investor, his words certainly have significance in the investment realm. Indeed, the actions of some of today’s “investors” sometimes resemble trading more so than investing.

Regardless of where you fit in, however, the following rules should help you in your quest for higher returns.

1. Never act on tips.

2. There is only one side to the stock market; and it is not the bull side or the bear side but the right side.

3. If a stock doesn’t act right don’t touch it.

4. If a man didn’t make mistakes he’d own the world in a month. But if he didn’t profit by his mistakes he wouldn’t own a blessed thing.

5. A man will risk half his fortune in the stock market with less reflection than he devotes to the selection of a medium-priced automobile.

6. There is profit in studying the human factors–the ease with which human beings believe what it pleases them to believe; and how they allow themselves–indeed, urge themselves–to be influenced by their cupidity or by the dollar-cost of the average man’s carelessness. Fear and hope remain the same; therefore the study of psychology of speculators is as valuable as it ever was. Weapons change, but strategy remains strategy, on the New Exchange as on the battlefield. I think the clearest summing up of the whole thing was expressed by Thomas F. Woodlock when he declared: “The principles of successful stock speculation are based on the supposition that people will continue in the future to make the mistakes that they have in the past.”

7. An investor looks for safety, for permanence of the interest return on the capital he invests. The speculator looks for a quick profit.

Tom Veale has an interesting day job. He makes his living investing in the stock market — an 800-pound Gorilla at the best of times. That in and of itself is nothing unusual. After all, millions of people make a comfortable living doing just that. However not many are successful in leaving their “day jobs” to make a living managing their own money. Add to that the fact Tom Veale isn’t a licensed broker, trader, or financial analyst and it becomes even more incredible. In fact, he’s a regular guy who found an investment technique that works and isn’t afraid of doing his own research.

Since 1988 he has been using Robert Lichello’s Automatic Investment Management, or AIM, system (editor’s note: Automatic Investor is based on the AIM techniques) to manage his investments with stellar results. He’s also provided enhancements to Mr. Lichello’s basic system in order to improve performance. He’s the undisputed expert in the field and is always willing to talk about AIM.

We caught up with Mr. Veale and asked him to share some of his experiences.

AUTOMATIC INVESTOR: How did you get started investing with AIM?

TOM VEALE: In the 1970s my account was usually 100% invested. After watching my favorite stocks fall to very low prices, I’d always be saying, “If I just had some free cash available, I’d buy a bunch more of these stocks.” In the 1980s I started to listen to myself. I sold off a portion of my portfolio to raise a “rainy day fund.” This got my portfolio growing because of the volatility, where before it had been just riding the roller coaster. I liked having some control over the account.

Some time in the mid-1980s I happened upon Mr. Lichello’s book. It suggested a method not too different from what I was doing, but with much more structure. Both AIM and I were using a cash reserve to “buy the dips.” I contemplated AIM for a while, then built an imaginary AIM account using my true holdings.

Starting in January of 1987 I mirrored my own activity in the fictional AIM account to see who was winning. I was ahead all the way through the mid-summer peak in the market. See how much smarter I was than AIM? Then when the market started to unravel I began to realize how powerful AIM was in a bear market. I was buying much sooner than AIM. I exhausted my cash reserve faster than AIM.

In fact, I had used up almost half of my reserves by the time October 19th, 1987 arrived! AIM hadn’t yet spent its first nickel. I penny pinched my purchases all the way to the market bottom in December where AIM made bigger and bigger buys as the prices declined.

So, January 1st, 1988 I took my personal oath to use AIM. It was AIM’s superior purchasing activity that convinced me.

AI: You now support a family completely with your investments (managed by AIM). When did that happen? What made you decide to do this?

TV: Yes, I use AIM with essentially all my equity investments.

There came a point where my “day job” was taking all my time, but my investments were starting to make me more money. I’d spent about ten years selling capital equipment in the aluminum casting and metal treating markets as well as into the chemical and food processing industries. At that time factory utilization in the casting industry was very low and capital equipment sales were slow. High interest rates also didn’t help. It was time for me to shift gears. That was August of 1986.

This freed my daytime for doing better investing research as well as developing a strategy for keeping the money I was making in the market. I also didn’t have to travel with this new “job” which was nice as my family was very young.

AIM will always do the best it can with the material provided. It will always accumulate shares when prices are down and liberate some when prices are up.
AI: How has it worked out so far? Were there times when you thought you might have to return to the traditional work force?

TV: Generally I’m an optimist. However, there have been a couple of times that I thought I’d have to re-join the “Fifty and Two Club” (Work 50 weeks, get 2 off!). The 1987 “Crash” and the following recovery didn’t leave me with much time to think about going back to work. The 1990, “Interest Rate and Gulf War” correction again was so quick that I didn’t worry too much. It was actually heading into a rising interest rate period in 1994 that was the spookiest. It was slow and painful as the market churned about. The churning was using up my cash reserve faster than it was replenishing it. The NASDAQ Composite was up just 4.6% that year, my personal account was down nearly 12%, and my Retirement account lost money for the first time. In the meantime my Cash Reserves were sliding towards zero.

That was probably the most anxious time for me. AIM proved to be of greater patience and less troubled than I did. The following year my account was up 42% and my retirement account up 32%.

AI: With the exception of Robert Lichello, you’ve contributed the most to the AIM system (split SAFE, Vealie, IW, among others) and are generally viewed as an AIM expert. Do you think there are further improvements that will become accepted within the AIM community? Or are all the improvements already out there and anything else would serve to create a brand new system (i.e. something that’s not AIM).

TV: There are several people who have taken Mr. Lichello’s work to new heights. Jack Park has carried out experiments with having AIM “learn” from its own activity as well as the price patterns of the equity. His method then optimizes the AIM settings from this historical perspective. Santos Torres has explored using the general AIM strategy for very short term trading in a narrow range. Years ago there was a software package called “MyWay” which used AIM parameters but was unique. It had the ability to sell to 100% liquidity. An interesting concept, but it might leave money on the table.

The changes I made to AIM “By the book” were relatively simple and gave effective returns. I think it is important to look at Return On Capital At Risk when making changes to AIM. If we modify it to give better total returns without examining the extension of risk, then we might be shortsighted. After all, AIM’s basic goal is risk management. Since there’s always correlation between Risk and Reward, we have to see both parts.

Since AIM is essentially “Buy Low, Sell High,” it’s hard to imagine a method that will supersede such a basic concept.

Since AIM is essentially “Buy Low, Sell High,” it’s hard to imagine a method that will supersede such a basic concept.
AI: How important is choosing the right stock to AIM’s success?

TV: AIM will always do the best it can with the material provided. It will always accumulate shares when prices are down and liberate some when prices are up.

I guess I’d say that choosing the right Company in which to invest is a major part of overall portfolio success. This could be true for a mutual fund or an individual company. For AIM to succeed in beating Mr. Buy&Hold using the same investment, TIME is probably the most important aspect.

The ultimate AIM Stock is one that has a highly unstable price, but is secure in its business model, finances, and things like that. I’ve found that small, rapidly growing companies seem to work well with AIM. Since their earnings are inconsistent while growing rapidly, they tend to go through massive over-bought/over-sold cycles. AIM loves this.

AI: You were very involved in putting together the first annual AIM user’s convention in May of this year. It was a good turn out, but relatively small compared to other investment conventions. Do you think AIM is a viable system for the majority of people out there? Can you see it moving into the mainstream with thousands of people registering for, say, the 10th annual AIM user’s convention?

TV: My long term friend and broker tells me there are two basic types of clients – Buy and Hold and the Short Term Trader. Mr. Buy&Hold rarely turns over any of his portfolio. The Short Term Trader, on the other hand, will churn his account many times in a good year. I’m one of his most successful clients, but I’m unique. I turn about 25% to 30% of my “inventory” over in a year’s time, but rarely sell out of a stock or buy much in the way of new stocks. I guess you could say investors fit an “inverted bell curve” with Mr. Buy&Hold on one end, AIM in the middle and Short Term Trading on the other end.

Many AIM Users have been around investing for a very long time. Some have tried and tired of Short Term Trading’s demands. Some have found themselves faced with retirement sneaking up on them and didn’t want to trust their savings to traditional money managers. AIM might not have been desirable before the advent of the Personal Computer for many of these folks, but neither was Short Term Trading.

I believe the number of AIM users will continue to grow, from a very small core group, now that there’s the Internet for sharing ideas and good AIM software available for implementing it. After talking myself blue in the face for several years, I found that most folks would say “How Interesting!” and that was as far as they’d go. It’s nearly impossible to convince someone who is “illiterate” with computers to try AIM. The learning curve is just too steep. It will take our extroverted AIM users showing consistently great results through a series of bear markets to get a big following. The raging bull market we’ve had since 1982 has been wonderful for almost all investors, but very hard on AIM! AIM needs corrections and true bear markets to really show its strength. I note that my email increases dramatically during market corrections!

The ultimate AIM Stock is one that has a highly unstable price, but is secure in its business model and finances.
AI: Have you ever corresponded with Robert Lichello? What do you think he’d say about using his system in today’s stock market?

TV: Unfortunately I’ve never managed to get in touch with Mr. Lichello. I’ve written through the publisher and also to a “last known” address, but have never had a reply.

I believe he would be very pleased to see the level of activity picking up on his pet project. His book sales must have started to increase after I started blabbing about AIM on Prodigy and then Silicon Investor! I wish there were a good way to let him know just how pleased we all are with his invention.

Today’s market is showing greater volatility than in the past. Part of this is due to “Sector Rotation” and to many other factors in vogue now.

I think Mr. Lichello would cheer this new age as being well suited to AIM. Risk moderation is more important now than at any time since, perhaps, the 1960s. The need for a guide is greater than ever.

AI: Many people who hear the title, “How to make $1,000,000 in the Stock Market, Automatically” are immediately put off. They think it’s a scam. Do you think you’ll make $1,000,000 using AIM by the time you’re done?

TV: I don’t think I’ll change from using AIM as my main business plan. I’ve not yet turned in the 10,000% profit needed to turn $10,000 into a Million, but I’m on my way. One investment of mine is at the 2500% mark and several others are nearing the 1000% gain point. In the meantime I’ve had to content myself with doubling my portfolio’s value every four or five years!

Those who are put off by the title of Mr. Lichello’s book usually won’t take the time to understand the math. My background with industrial machinery taught me that closed loop controls are marvelous things. AIM emulates just this sort of thing. AIM’s genius is the “positive feedback loop” provided through small increases in the Portfolio Control variable after each buy.

AI: From reading some of your messages, it’s obvious you know about technical analysis and other investment techniques, but you choose to use AIM. Is that because you feel it’s the best system out there? Or is it because you feel it may not be the best, but it’s the easiest to maintain (so although you might squeeze a few more points out of an investment, the time required to do so is not worth the effort)?

TV: Technical analysis attempts to make efficient, profitable trades based upon an investment’s own price activity. This is fine. The type of trading tends to be “all or nothing” in that one either owns the investment or is in cash. This can work well – especially in a perpetually rising market. This method ignores the potential long-term benefits of investment ownership and concentrates only on shorter-term “trends.”

AIM acts as my Technical Analysis advisor once I’ve made Fundamental Analysis decisions and invested for the long term.
Fundamental analysis looks into the business of the investment for other information. It takes time and effort to do good analysis. Usually fundamental analysis will include decisions about whether there is good long-term viability in the investment.

I concentrate on the Fundamental Analysis portion first. To get “paid” for my effort takes more than a quick round trip at the brokerage, however. If I’m going to devote the time to Fundamental Analysis then short-term trading doesn’t usually pay. I’m trying to pick investments that I’ll own for 5 years or longer. Technical Analysis doesn’t think in those terms.

AIM acts as my Technical Analysis advisor once I’ve made Fundamental Analysis decisions and invested for the long term. I’ve owned most of my portfolio for more than 5 years. AIM manages the risk of being invested long term by efficient Technical Analysis trading around a core position.

It’s interesting that you mention the amount of time to manage an AIM account. Technical Analysis is very time intensive. Most short-term traders have a serious “Ticker Addiction,” and usually have serious anxiety problems when they are away from their computers, ticker source, or can’t get through to their brokers. It’s hard to “have a life” and be a successful short-term trader.

With AIM, many days I don’t even look at the market. AIM’s in control, so why bother. All I need to do is monitor my list of the “Good ‘Til Cancelled” orders I place with the brokerage to see what’s filled. AIM will tell me when to trade again. I have lots of hobbies, a young family and have time to enjoy all of it. It may be AIM’s single biggest gift to investors – TIME!

I act as a fiduciary for some friends’ money and have for some organizations as well. AIM is a responsible fiduciary method. It’s always doing the proper thing, so it’s pretty hard to go wrong. It’s pretty hard to imagine some conservative philanthropic organization entrusting its funds to a person in a short-term trading salon! AIM, on the other hand is so conservative as to be ideal for use by a fiduciary.

Is AIM “Better” than any other method? It’s always more responsible and given enough time will usually be better as well.

It’s hard to “have a life” and be a successful short-term Trader.
AI: Most people have just recently started investing in the stock market. So they’ve never really experienced a bear market. When the bear comes, do you think many of today’s investors will lose a great deal? What about the AIM investors, how will they fare in a real bear market?

TV: Many of the investment models that are in vogue right now almost guarantee losses by selling when the price drops to protect principle. Assuming the investor has been in the market for some period of time he should have a profitable account. So, he won’t lose “everything” but might give back some of his unrealized gains.

During the “crash” of 1987, an acquaintance called me. He was less than a year from retirement. His retirement account was very profitably invested in a good mutual fund. He wanted to know on October 19th if he should sell to protect what was left of his profits. I told him not to and to ride it out. He replied that “do nothing” was not an option, he had to do something.

I suggested that if he had to do something, then maybe he should just sell half and let the rest go. Then he’d only be half wrong no matter what happened next! Well, he ended up selling it all on the 19th, which just happened to be the lowest price for his fund that entire year! He didn’t “lose” anything but paper profits, but it sure felt like it for him, being just a year from retirement. A year later he would have been ahead too.

He never spoke to me much after that year. I never said “I told you so!” but I think his conscience did!

AI: Thank you.

Most investors intuitively see the logic behind diversification. However many don’t practice this important technique or they don’t know how to implement an effectively diversified portfolio. Over the long term, this is a huge mistake.

Diversification is the primary tool investors can use to spread their risk between countries, currencies and markets. It allows us to take advantage of opportunities when they unexpectedly appear and protects us from unseen crises situations. In short, diversification reduces risk and, when properly applied, can increase returns.

How many investors do you know who wouldn’t want to decrease risk and increase returns? Probably none. It follows then, that if investors really sit down and think about it, they will diversify. Those who don’t most likely haven’t thought about it, are gambling rather than investing, or think they know something the rest of the world doesn’t. Experience and research shows that all of these reasons are extremely dangerous to investors’ portfolios.

But how do you diversify properly? What investments should you include? How many different investments should you have in your portfolio? What percentage should each contribute to your portfolio’s overall make up?

These questions must be answered accurately before a portfolio can be properly diversified.

Of course the investments you place into your portfolio must meet your criteria and nobody else’s. You need to accurately assess your risk tolerance, the time left before you will need the money from your investments and a number of other factors. Once you’ve completed your homework, you can then begin to diversify.

Diversification always involves a trade off between risk and return. Let’s say we have two investments: sunglasses and umbrellas. The sunglasses investment pays off for every day that is sunny. It pays nothing on days that aren’t sunny. The umbrella investment pays off for every day that is not sunny. It pays nothing on sunny days. It stands to reason that you would always choose to invest in sunglasses if you were absolutely sure that every day over the next year would be sunny. Similarly you would invest completely in umbrellas if you were certain that each day over the next year would not be sunny. Using this strategy you would realize the maximum possible return on these investments.

However, as we all know, predicting the weather is not 100% accurate. All we know is that at some point within the next year we will have sunny days and we’ll have days that aren’t sunny. Furthermore, we don’t know which days will be sunny and which ones won’t. However we could study the historical weather patterns for our area and come to a fairly accurate prediction on how many days (over the course of a typical year) will be sunny and how many won’t be. As it turns out, this is very similar to the stock market. Short-term, we can’t predict anything with great accuracy. However our accuracy improves over the long-term.

For example, if you were to try to predict IBM’s return over the next year, you might be well off the mark. However if you were to try to predict its return over the next 20 years, you’d probably be a lot closer. Therefore it isn’t unreasonable to use a stock’s history to try to predict its future – as long as you’re doing this over the long-term. (Keep in mind, however, that past performance does not guarantee similar performance in the future.)

And since diversifying correctly requires that you make some predictions, your outlook needs to be long-term.

The rest of this article assumes you’ve decided on the general type of investments that will go into your portfolio (e.g. bonds, mutual funds, small cap equities, large cap equities, and such) as well as the specific securities (e.g. IBM or UOPIX). It further assumes you’ll be investing in equities (and perhaps bonds) rather than other investments such as real estate or treasury bills (although you could use the same techniques to manage any investment). A final note is that a properly diversified portfolio won’t gain anything more by holding more than 40 or so equities. Usually 20 to 40 individual stocks is a good number – but you can get by with less when using mutual funds which are already somewhat diversified.

To begin, I’ll introduce a unique way of looking at investment portfolios.

In 1953, Harry Markowitz developed an ingenious approach to managing investment portfolios that has since been dubbed Modern Portfolio Theory (MPT). Rather than trying to predict individual stock price movements using fundamental or technical analysis, he concentrated on looking at the performance of a portfolio based on the combination of its components’ risk and return.

Unfortunately the underlying calculations required to implement his theory were onerous and not conducive to solving by hand. Therefore it wasn’t until the late 1970s, when computers started to show up everywhere, that MPT took off. Markowitz went on to win the Nobel Prize for Economics in 1990 for his contribution of MPT.

Attesting to its validity is the fact that a large number of professional money managers now use MPT to help them with their work.

While the technical details of MPT are very complex, the good news is that there are software packages currently available that allow you to bring the full power of MPT to bear on your portfolio without having to know how the calculations are performed. This means that you can use the same techniques used by some of the top financial minds on your own portfolio – and reap the rewards without having to pay the fees large financial minds usually demand.

Let’s look at how MPT works. Going back to our sunglasses and umbrellas example, we can see that each investment is fairly risky. On any given day you might not make any money. However a portfolio that contains both sunglasses and umbrellas will always pay off – whether the sun shines or not. By adding one risky investment to the other, you’ve effectively reduced the overall risk of your portfolio. (What’s more, if you vary the portion of your sunglasses and umbrellas investment according to the number of days you predict will be sunny or not sunny, your returns might be greater. In essence, you’ve reduced your overall risk and increased your returns.)

The important insight of MPT is that the risk of an individual asset is not too important. What is of prime importance is its contribution to the portfolio’s risk as a whole. And that’s why MPT uses diversification as its primary mechanism.

The first step in using MPT is to predict each investment’s expected return over the long-term (recall that we can generally come up with a good prediction if we’re dealing with long periods of time).

The next piece of information we need is the risk associated with our portfolio. Risk can be defined in a number of ways, however most investors use the standard deviation. For the purposes of this article, we’ll also define risk to be the standard deviation of our particular investment.

The final piece of information we’ll need is the correlation between each investment in our portfolio. Correlation information is usually given as a matrix of correlation coefficients.

All of this information can be obtained from an investment’s historical data. Once we have these data, we can begin our MPT calculations. Our goal is to diversify our investments, in very specific portions, in order to come up with a portfolio that provides a given return at the lowest risk level or the best return for a given level of risk.

MPT assumes that investors will always want the highest return at the lowest risk. In essence it asks, “why would an investor choose an asset that returns 4% a year with a 50% chance of losing some money over an investment that returns the same 4% a year with a 0.001% chance of losing some money?”

The answer, of course, is that a rational investor would not do this. Instead he would choose the investment that returns 4% with the 0.001% risk level. Of course some investors might choose an investment that returns 5% with a 50% risk of losing money over the 4% return, 0.001% risk level investment. And that’s okay with MPT. It doesn’t make assumptions in those cases. If investors are willing to accept greater risk, then they must be compensated with greater returns (no matter how little or how much greater).

In this article, we’ll only look at stocks because studies have consistently shown that they are the most profitable investments over the long-term (however you can use the techniques described with many other investment classes).

In the United States, between 1926 and 1994, small cap stocks have returned 12% annually with a standard deviation (i.e. risk) of 35%. Large cap stocks have returned 10% annually with a standard deviation of 20% over the same period.

Other investments have returned less, but have also been less risky. For example from 1926 to 1994, long-term government bonds returned 5% with a standard deviation of 9% and Treasury bills returned 4% with a standard deviation of 3%.

From these examples, we can see that the larger returns come at the expense of greater risk.

So how does diversifying reduce our risk and increase our returns? It does so by utilizing the way individual investments move with one another. If two investments both return 10% on a sunny day and nothing on a rainy day, then these investments are perfectly correlated (i.e. correlation coefficient is 1). In this case there would be no point in diversifying since owning both would provide exactly the same return as owning just one. (Note that it is a good idea to diversify within investment classes – i.e. investments that are highly correlated – so we eliminate specific, or non-market, risk. However we’ll ignore this in our examples.)

Instead we want to look for investments that aren’t perfectly (or even highly) correlated. Ideally we’d like to find two investments that are perfectly negatively correlated (i.e. correlation coefficient is -1, by the way, no such investments exist – but if they did, we’d be millionaires many times over in a short period of time), however in reality we usually have to settle for low, positive correlation coefficients.

Therefore many savvy investors diversify by investing in foreign markets as well as different industries and investment classes. The key point is to choose investments that aren’t highly correlated. This happens to be the case with domestic securities and foreign ones.

Once the data are fed into the MPT algorithm, a curve (called the efficient frontier) is plotted. The efficient frontier is the set of portfolios with expected return greater than any other with the same or lesser risk, and lesser risk than any other with the same or greater return.

The efficient frontier is usually plotted on a graph where the x-axis represents the risk level and the y-axis represents the expected return. Each point on the graph represents one particular portfolio that has a specific expected return and a specific level of risk.

This portfolio is composed of the individual investments put together in various portions (each individual investment can range from 0% to 100% of the portfolio).

For example, the point labeled Sample Portfolio (shown below) lies on the efficient frontier and might be composed of 0% T-Bills, 15% EK, 15% IBM, 25% MSFT, 30% AMZN and 15% ICGE. (Note that this is only an example and does not represent an actual portfolio.)

All portfolios that lie on the efficient frontier are called efficient portfolios.

Portfolios that lie below the curve are called inefficient portfolios (i.e. for a given risk level you can obtain a greater return using another portfolio – e.g. the one lying on the efficient frontier – and for a given return you can obtain a lower risk level by using another portfolio).

Portfolios that lie above the curve are not attainable (e.g. you cannot receive a 100% return with no risk).

MPT, therefore, quantifies risk relative to expected return and provides a mathematical model that shows you the best portfolio (i.e. how best to combine the individual investments in your portfolio) to use for a given level of risk or return.

The question naturally arises, “can we do better?” In this case the answer happens to be “Yes.” To see how, let’s introduce Automatic Investor into the equation. Automatic Investor uses an algorithm based on Robert Lichello’s AIM. It balances cash and equity in order to reduce risk and increase returns. This makes it a natural fit for use with MPT. After all, MPT is concerned with returns and risk – as we’ve seen.

By using Automatic Investor to manage each of the individual investments in your portfolio, you’re essentially reducing the risk and/or increasing the return for that investment compared to simply buying and holding that investment. So if the underlying investment has a high volatility (i.e. standard deviation), when Automatic Investor manages it, its volatility goes down significantly. Its return can also be expected to increase.

This causes that investment point to be shifted to the left (i.e. reduced risk) and/or up (i.e. increased return). If you plot the Automatic Investor managed point for each investment, and then calculate the efficient frontier, the curve will be shifted up and to the left.

In effect you’re now able to choose portfolios that were previously unattainable because for a given level of risk, your returns are higher and for a given return, your risk level is lower.

In essence, you are using MPT to manage your entire portfolio (the macroscopic view) and using Automatic Investor to manage each individual investment within your portfolio (the microscopic view). Automatic Investor filters the risk of the underlying investment so that it becomes less volatile at the macroscopic level.

Keep in mind that Automatic Investor thrives on volatility (or a relatively high standard deviation). Therefore using standard deviation as a risk measure at the microscopic level is counter-productive because Automatic Investor manages this risk to wring out higher returns.

However at the macroscopic level, standard deviation is an excellent measure of risk. While you don’t want your entire (macroscopic) portfolio to fluctuate wildly, you do want the individual (microscopic) investments within that portfolio to fluctuate (so that Automatic Investor can produce higher returns with less risk).

A side effect of this is that you can invest in equities that are slightly more risky than those with which you’d normally be comfortable. Since these “riskier” equities are being managed by Automatic Investor at the microscopic level and diversified according to MPT at the macroscopic level, your overall portfolio risk is within your tolerance – and your expected returns can be higher.

Therefore by using MPT in conjunction with Automatic Investor, your returns can be significantly increased and your risk significantly reduced compared with using either MPT or Automatic Investor by itself.

This article was first presented at the AIM 2001 conference in Las Vegas by Mark Hing.