Reprinted from Technical Analysis of STOCKS & COMMODITIES magazine. 1995 Technical Analysis Inc., 4757 California Ave. SW, Seattle, WA 98116, (800) 832-4642

Building a Better Mousetrap
John Sosnowy
Of SIMCO

There seems to be a connection between engineering and investing. Like Jack Hutson, the publisher of STOCKS & COMMODITIES, John Sosnowy of the Sosnowy Investment Management Co. (SIMCO), Cameron, TX, was an engineer before he turned to the world of finance. He changed careers in 1969, leaving the engineering field to work as a stockbroker for a major brokerage firm before starting up his own investment advisory concern in 1984. We interviewed John Sosnowy via telephone on January 4, 1995, covering the concept of tactical asset allocation, how to design a market model and what indicators to use, the funds he particularly likes, determining the amount of risk an investor is most comfortable with and the secret to making a profit in the market.

How did your career as a money manager begin?

Well, I didn't start out in money management. After I finished graduate school, I went to work for Union Carbide as an engineer. I was interested in investing my own money, so I joined an investment club. When you join a club made up of a bunch of engineers, you can imagine the different things we looked at to try to build a better mousetrap! That was my first exposure to investing.

Did you stay in engineering very long?

No. After a few years as an engineer, I became more and more interested in the markets and investing. Simultaneously, I reached a point as an engineer that to advance within the company, I would have had to relocate to New York City.

But that didn't appeal to you?

No, I wasn't very excited about the prospect! So I started looking for an alternative. About that time, I realized how much I was interested in investing, so it was then that I decided to change careers.

When was that?

That was in 1969. I joined a large brokerage firm as a trainee and became a stockbroker. During that time, I continued my academic study of the stock market and ultimately came to some interesting conclusions.

Such as?

I came to the conclusion that probably 60% to 70% of why any stock went up or down had to do with overall market direction and not what the company's individual prospects were.

What about the performance of the industry group that the stock's in?

The performance of the industry contributes to a small degree, but it still comes down to the trend of the market itself. So there I was, with an undergraduate degree in mathematics and a master's degree in engineering, and I asked myself why I would want to be a stockpicker when most market activity results from the general market trend.

So what was the answer?

That’s when I started to develop a market model that led me to what I refer to today as a tactical asset allocation program. I thought that this approach was the correct way to optimize investment results.

Was the idea of adjusting the amount of money allocated to different assets well received?

No. Back in the late 1960s and early 1970s, the idea was heresy!

Why?

Because the stock market had gone almost straight up since the end of World War II into the very early 1970s. It wasn't until the bear markets of 1973 and 1974 that I could find any real believers. The bear markets validated for me and my clients that the concept had merit.

Were you still a broker at that point?

Yes. In fact, later on I was also hosting an evening radio program on finance and investing. It was a program that people could call in and ask questions about their investments. Someone called in and asked me about my outlook for the market, so I said that my market model just told me to get completely out of stocks and that I had advised my clients to do so.

Sounds innocent enough.

Well, it didn't turn out that way. The next morning, a local newspaper carried an article stating that my firm had advised getting out of stocks!

And I take it your company had a different outlook?

Right. So the next day, I had to explain to my branch manager that what I had really said was that my market model had said so, and the newspaper was wrong about the attribution.

So what happened after that?

Well, that led me to the conclusion that I would be better off being an investment advisor than a stockbroker. After that, I started my own business. I've been managing money based on this concept of tactical asset allocation for more than 20 years now.

How is tactical asset allocation different from other forms of investing?

To me, a money manager will use one of three different investment philosophies. Those three tend to differ primarily in the frequency and degree of changes of investment in different asset classes.

Give me a breakdown.

Okay. A traditional asset allocator bases the investment decision on a combination of the client's attributes - for example, their age, their financial resources, their risk-taking profile. These attributes would be considered for a long-term investment strategy. The money manager would advise you to put 65% of your money in stocks and 30% in bonds and keep 5% in cash or whatever. Then you could have an annual meeting with that manager and there may or may not be a change to your mix from time to time. Typically, as you get older the mix would be adjusted.

And what about the tactical asset allocator?

The tactical asset allocator or risk manager--which is the category I consider our firm to be in-could be 100% in stocks or 0% in stocks and we could be anywhere in between at any given point. But our frequency of adjustments would be much lower than the market timer, because we're looking for what I refer to as intermediate-term moves in the market.

What do you call "intermediate-term"?

On average, we may be in or out of a position six months or a year at a time. Certainly not in or out every day, or every few days. Our goal is to catch the major uptrends and avoid the major downtrends. But we aren't like the passive asset allocator who puts you at a certain percentage and pretty much leaves you there.

Why do you feel this level of activity is best?

When I started, I didn't have any preconceived notions about what the optimum length of time was to be in or out. I tried all sorts of different time lengths of indicators in the model. Obviously, with a lot of tuning of the indicators, you can make the model generate more signals if you want it to do that. You can adjust your moving average calculations and other indicators and design them to be more sensitive. And I tried all sorts of cycle lengths to see where the optimum approach was generating the most return for the least risk, and in a fashion in which you can really manage money.

What did you find?

I found that the optimum is to have a model that won’t generate more than three or four round trips a year on the maximum, and in most years we don’t even have that many. By having less frequency, you aren’t going to have a lot of the whipsaws in the market that cost you a lot of return.

So overtrading is a greater sin than missing moves?

You don't have to have a model that's going to give a signal once every three or four years, but I think it's futile if you intend to manage a lot of money, or if you think you're going to create a big nest egg for yourself by trading actively. I think you can certainly overtrade, and not to your benefit.

In that case, what do you recommend?

I recommend that you look at a longer-term perspective. In addition, in the last few years, there hasn't really been any differential tax treatment for long-term capital gains. We could get into that mode again in the next few years in terms of tax law, where there is a significant differential for getting long-term gains. If you already have a model geared for that time frame anyway, it could give you a natural advantage there also.

What are some indicators of value to designing a market model?

My model's not a pure technical model. When I first started out, I thought that was the way it was going, but after a lot of testing, it didn't end up that way.

So how did it end up?

Our model has three basic categories of indicators. One set is a group of fundamental indicators that you don't see in many systems, certainly not in short-term systems, because they wouldn't have any value. But for an intermediate-term orientation system like mine, you do need to incorporate some fundamental data. This input doesn't have a high weighting compared with the other indicators. If I were developing a trading model to predict tomorrow's market, fundamentals would have zero weight. If I were looking at a five-year forecasting model, I would probably have fundamentals being 50% of the model, or something like that.

FIGURE 1: EXPECTED RETURN LINE. The expected return line connects two points: the risk-free return (beta=0), which could be a money market account, and a market index return (beta=1), which could be the S&P 500 total return index. To determine your own risk-adjusted return, compare the weekly returns of your mutual fund to the weekly returns of the market index using a linear regression, which will give you your beta value. If you are using a successful trading model, you should maintain high returns while lowering your risk compared to a simple buy-and-hold scenario.

What about in your case?

In my case, fundamentals account for about 20% of the weighting in my model. I use the fundamental indicators to determine the current value of the market. I want to measure the degree that the market is undervalued or overvalued or fairly valued at any point in time.

What indicators do you use for that?

I use the traditional things--the price/earnings ratio, the dividend yield and the number of stocks below book. That type of data.

What’s the next group of indicators?

I remarked at a luncheon presentation a few weeks ago that sometimes I compare the stock market to an Indianapolis 500 racecar. You can have a lot of money in a racecar, but that's not enough to win Indy. That car isn't even going to get out of the garage if you don't put some fuel in it. In my opinion, the fuel in the market is the monetary side. So the first step in my model is to determine value. Then I look for the fuel level, which in the model is the monetary conditions--the Ml, the M2, the direction and level of interest rates. I also look at institutional cash positions.

Why is the institutional cash position part of the fuel in your analogy?

To see how much money is out there that could go in the stock market and whether it's likely to go in. Or whether it's likely to go into some alternative investment at the moment. My thinking in developing the model was, "Okay, let's say we have a market with good value and we've got a lot of fuel in the tank. We've got good monetary conditions. Are those two things enough to make it jump tomorrow?"

Are they?

Not necessarily. Because if it were an Indianapolis racecar, you would have the engine and the chassis and the fuel and the latest gadgets--but somebody would still have to turn the engine on.

So that means the market's engine—

Turning the engine on is market psychology. It's the investors who think the market's cheap and they have the money to invest. Are they motivated to buy them? If none of them are, it isn't going to go up. You have to have buyers to move the market. That's crowd psychology.

How do you measure psychology?

I use sentiment indicators and momentum indicators. In our model, because of the intermediate-term orientation, the sentiment and momentum indicators actually have a higher weighting on them than the monetary conditions and the fundamentals do. But if those first two were completely negative, it would take almost perfect sentiment and momentum conditions for us to want to be fully invested in stocks.

Which sentiment indicators do you look at?

We use the same things that a lot of people do. We look at insider trading and activity, advisor sentiment, margin account activity, specialist activity, put/call ratios.

Some people point to high levels of bearish sentiment as being a positive indication for the current market.

I think the sentiment, the negative sentiment that you see today, is generally positive for the market. By our measurement, I would say that this is probably the most bullish aspect of the current market.

The high levels of bearish sentiment represent money on the sidelines ready to come back into the market?

You better believe it! Sentiment is at the levels where major turnarounds have occurred, and it can't get much more negative. On the other hand, you've got some sentiment indicators with a positive correlation with the market, like insider activity. Right now, we're seeing insiders buying more, and that's positive because they're usually right.

So some sentiment indicators have a positive correlation and some have a negative, inverse correlation to the stock market?

That's right.

What do you use for your market index for comparing the performance of your indicators?

I use the New York Stock Exchange (NYSE) total return index.

Where can I find that, Barron's?

No, it's not in Barron's. I use the data supplied by Norm Fosback. It's the total return index that he publishes, and I get it from there. For our purposes, that index is more representative of the performance of the overall market on a total return basis. It's also a good proxy for the type of fund or stock portfolio that we would use when we're invested in the stock market.

Have you always used that?

No, I used to use the Standard & Poor's 500, but if you base your signal on the S&P 500 and then buy an aggressive growth fund, sometimes your fund won't track the S&P. I've found that theNYSE total return index tracks closer to the type of portfolio that I would have when I'm in the market.

You mentioned aggressive growth funds. I interpreted that as meaning you don't do a lot of tactical asset allocation among industries. That you look at the stock market as an asset of its own. Am I right?

Yes. I've done a lot of analysis work with sector funds. I must not be as good as some of these other investors, because I can't make that work as well as some people say they can. I've found that I can do better with my model on the market using a widely diversified, fairly aggressive growth stock portfolio.

What would be a good fund for an individual to consider following when he or she wants to be in the market?

A few have been pretty good. Transamerica has an emerging growth fund that I like, Emerging Growth B. Columbia has a Special Fund, Founders has a Special Fund. Alger has a Small Cap Fund that really tracks our model well while we control the risk.

When someone develops a model, they need to focus both on profitability and the risk of holding these funds, don’t they?

Yes. The risk factor is as important as the profitability. Let me explain this as a money manager thinking in terms of the client. I’ve found that too many people are at one extreme or the other in terms of their approach to the risk issue. For example, you’ve got the one extreme where the people who come to you have the highest possible return in mind.

With the commensurate risk.

Ah, risk. They play lip service to the word, but you can tell that they really don’t understand it. On a much smaller scale, when I have wealthy individuals or the officer of a small to medium-sized company discussing retirement plans, many of these people really don’t understand investing or how much risk they’ve been taking in certain investments. So the first hurdle you have to get over is to really get them to understand risk and how much certain investments really have.

How do you develop an appreciation for risk without just throwing money out the window?

I use what I call the capital market line, or expected return line chart.

What's that?

It's a nice tool to use to sit down with potential investors and show them different risk levels and explain what a reasonable return would be, given a certain level of risk. Then I take the investments that they've been invested in so we can sit down and see how much they've made and then really how much risk they've been taking.

How's that work out?

Very often, a person falls 'way out there on the high risk side. While their return may look decent in absolute numbers, it may turn out to be not very good when you consider how much risk they’ve taken. Once the investor understands that it’s the highest risk-adjusted percentage that you can get, given the level of risk you should be taking or that you feel comfortable taking, you’ve taken care of the most important part.

What about the other extreme? Do some people not take enough risk?

There’s probably even a larger number of people on the other end of the spectrum. Those people are so concerned about losing their principal that they end up putting their money into things that don’t have a chance of keeping up with inflation.

Those are the cautious-to-the-extreme investors?

Right. All they can think about is, "If I put in $ 100,000 today, what's the chance that I could ever end up with less than $100,000?" instead of thinking about the risk of maintaining $100,000 worth of purchasing power. So you have to go through the risk-reward scenario again. But you also have to make people understand that it's not gross returns, it's real returns after inflation and after taxes, that's all you can spend. If you don't have anything left after that, you took the ultimate risk.

So you have to find a balance?

A lot of people say that they can stomach more risk than they really can. To me, that's a very key part of the investment counseling process, to correctly assess how much risk an investor is really willing to handle.

What are the steps to determining the risk?

You have to calculate a risk-adjusted performance graph (Figure 1). You want to compare the returns of your mutual fund to the returns of your market index such as the NYSE total return index. The x-axis of the graph is the risk or beta of your tradable. Your market index would have a beta of 1. The y-axis is the annual return. For a low-return, risk-free instrument, you can use the return of a money market fund. You connect the line from the risk-free money market return through the return of the market index at a beta of 1. That's the expected return line.

How do you measure the risk of the mutual fund?

You use a least-squares regression calculation to measure the relationship between the mutual fund and the market index. That calculation will give you your beta for the performance of the mutual fund. Then check out where the return of your mutual fund based on its beta falls in relation to the market index. If you're successfully managing or timing the mutual fund, you should see a return higher than the market but with lower beta or risk.

This should make people more confident about their own models.

It should. For my clients, I can go back as far as I have records on these funds, and I've got 20-plus years of data for some of them. So for whatever period, I can go back and set that risk as a maximum drawdown and put that into a program that I have. Then I'll run through it and kick out all the funds that I follow and it'll rank them by risk-adjusted return, with a historical drawdown at or less than what that client says he or she can stomach.

Not what they could do overall, just what they'd be most comfortable at?

Yes. There's no sense showing them a fund that looks like they could hit a home run on if historically all they've been able to stomach is a 10% hit.

Living with risk is tough for everyone.

That's true. The biggest fallacy that I've found among investors is what I call the fallacy of the mountain chart.

What’s that?

If you look back at all the mutual fund literature, they all have a mountain chart. They say things like, if you'd left $10,000 with us since this fund started, you'd now have a jillion dollars. What that mountain chart doesn't say is how much interim drawdown you would have had to have stomached and hung in there to have realized that jillion dollars. And when you look at the funds with the biggest mountain charts, they can also have the biggest drawdowns.

So you need to measure performance on a risk-adjusted basis. What else?

You also need patience to be successful. People need to realize that no matter what indicator they're going to follow, if they're going to develop their own model or use my model or hire a money manager, they've got to give it time to work at least one complete market cycle. That's usually going to be four or five years or more. What happens all too often is that with Morningstar ratings and Money magazine, and Forbes and everyone else rating different investments and the funds, that encourages investors to chase last year's winner.

That's not the approach to use, I take it.

No, and there are many statistics that will tell you so. For example, Mark Hulbert ran an article in his newsletter not too long ago about that.

What did he find?

That last year's winner is seldom next year's winner. And what you want as an investor is next year's winner. And the year after that and the year after that. As Hulbert says, the most likely way to achieve that is to FIND AN INDICATOR, FIND A MODEL, FIND A MANAGER THAT YOU CAN IDENTIFY WITH, THAT YOU BELIEVE IN--AND THEN STICK WITH IT or them. Don't abandon it. If you believed it was good enough to start with, then stay with it five, 10, 15 years and it'll probably work. There's not just one good system out there. There's a bunch of good ones, but you've got to stick with them, whatever it is. And THAT'S THE SECRET!

Sosnowy Investment Management Company. (SIMCO)
3883 Telegraph Road, Suite 100
Bloomfield Hills, MI 48302
Phone: 800-526-2152
Fax: 248-642-6741
Contact: info@lastingwealth.com

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