How I Became Wealthy

My definition of wealth: "financial assets sufficient to allow one to spend their time as they see fit, without concern for survival". Notice that my definition is about time, not about the acquisition of objects (houses, boats, etc.).

I "retired" at 50 years of age. I put that word, "retired" in quotes because what I really did was quit my job and become self employed. I am now 52. I work about 25 hours per week, from home, and earn about the same as I did when I was in that job, working about 50 hours per week.

I have virtually no stress now, and no long commute on traffic-congested highways. I have plenty of time to do what I want to do, when I want to do it, and I enjoy the work that I am doing. I have achieved wealth (according to my "time-centered" definition of wealth). But I have not acquired expensive objects. My house is not the house of a rich person, neither is my car. I don't have any expensive hobbies. Rather, I have achieved my freedom from the rat race in large part by avoiding the purchase of expensive things.

My work now consists of me working on a laptop computer. My desk is the wooden TV tray that my laptop sits on. My office is wherever in the house I decide to put the TV tray on any given day. I do "signal processing" research and development in the field of wireless communications. I guess you could say that it is applied mathematics, or engineering, but it is not like "normal" engineering because it involves no hardware. Anyway, it has trained my mind to be more rigorous and logical than the average citizen.

My retirement from the rat race has freed up time for study of stock market investing. There are a very large number of systems for making money in the stock market. Various stock screens filter all the stocks in the U.S.A. markets, winnowing them down to the few that you should invest in. These systems are described in various books and articles.

Remember that my R&D experience involves rigorous analysis. So in the last couple of years, I read many of these investing schemes, but felt uneasy that the authors' analyses of their performance was unconvincing. You see, when one develops an investing strategy, a method of evaluating it involves "back testing". Back testing applies the strategy retrospectively to prior years to measure the returns that would have been gained if one had used that strategy. The problem is, there are a large number of ways to wittingly or unwittingly screw up the back testing. Some of those mistakes can be quite subtle.

As a skeptical engineer, I did not trust these authors' results. I needed to do the back testing myself, so that I could evaluate all the strategies on an equal footing and avoid biasing the results. A friend of mine turned me on to a suitable back testing program, which came with 12 years of historical data and a subscription for daily updating of the database as well. This was about 2 months ago. I purchased the program and did back testing of about a dozen of the most promising strategies, and about 3 of the 12 gave excellent results.

I tested the strategies over 1 year time periods. The first trial started January 1, 1997 and ended December 31, 1997. The second trial was also 1 year long, but started one month later. There were 115 trials altogether, with the last one-year period ending yesterday. These strategies did not involve the use of margin (investing with borrowed money). They did involve shorting stocks (a strategy that benefits when a stock's price declines) during bear market periods, as well as buying stocks long (the normal method of investing that benefits when a stock's price increases) during bull market periods.

The program I use is pretty sophisticated. It has numerous features that allow one to avoid most of the simplifying assumptions that typically lead to back testing errors. For instance, it simulates buying a stock at the average price of the stock during the next trading day after the buy decision is made, and it accounts for commissions. If you are interested, you can find out more at www.vectorvest.com. Of course, I have no financial interest in the company.

I just discovered today another subtle way in which one can fool oneself with back testing. I found out that my back-testing program uses a database that omits the history of any stocks that are no longer in existence. That makes the back-testing results look better than they should, since in the simulation, only the survivors are purchased. I found out that this is called the "survivor bias".