Breaking Average

As a child I spent allot of time in front of my cherished Apple II. Writing programs, playing games, and wishing for that coveted second disk drive. During my late teens, I upgraded to an Intel 386 DOS based computer.

Using it mostly to write programs, I made one exception. A stock trading simulator. This game gave the user a streaming list of symbols and prices. You entered the symbol and quantity to purchase or sell. When buying, it deducted the cost of the stock from your available funds. When selling, it increased the amount of available funds from the proceeds.

The price fluctuation was random. Prices moved up and down similar to the actual market, just at a much faster rate. However, it did not take long to discover a working strategy due to a flaw in the program. There was a price floor of one dollar.

When a stock in the game was priced at one dollar. The strategy was to buy the maximum possible with the funds available. At some point, the price would go back up since it could not go down and would must change within every few minutes. This made game easy to win.

Despite knowing how to beat the simulation, I enjoyed watching as my funds increased dramatically. This began a lifelong obsession with trying to beat the market. The problem was and is, that prices do not have floors. However, was there an exploit that one could employ on real markets to accomplish massive gains?

Around 2000, a new game got my attention called Dope Wars. This was a drug dealer simulation. It was completely graphic free. Looking similar to the business applications of the day, the game was played by clicking buttons on a windows form.

The interesting part was not the subject matter. It was the buying and selling of products across multiple geographic regions. During breaks from work my co-worker and I would play. He had what everyone agreed was a high score of over 8000 US Dollars.

Deciding to make it more interesting, we bet $50 that I could beat his score within the next 30 days. At the time my high score was around 3000. The reason for the 30 day time frame was to study how the gamed worked.

To start, I made several experiments. Concluding that it was most profitable to remain in a single geographic region. Traveling in the game was costly and despite better pricing achieved, the cost ate into profits. Next, I found that cocaine was the most profitable. Once those factors were established I moved on to discovering the best location to transact business.

After a week of experiments, I began to play. It did not take long to beat the 8000. Quickly moving past the goal to 12,000 then 20,000 then 30,000 and up to 50,000 before I paused to get my friend. He concluded I must of hacked a configuration file or altered the application in some way. After allowing him to inspect my computer to his satisfaction I continued. Ending the game at over 90,000.

He paid the bet. I then opened my first online trading account. Remembering my days of playing the stock simulator, I focused on low cost stock that could be purchased in larger quantity than the blue chip. At the time, Kmart was hovering around $1 per share. As history suggests, you probably already know the outcome of that one.

Buying Kmart was a play on the average. It was a big company and someone would buy it, making that $1 go to $2 or $3 or even $10 per share. Instead, something else happened. Kmart did the unthinkable. It reincorporated, removed its stock from trading, and issued new shares. Meaning all those dollars spent on stock were now worthless.

My investment was based on similarities with past events. The problem with basing decisions on the past is that the past is not a perfect representation of the future. It is full of discontinuities. Even similar situations from one year to the next can have wildly different outcomes due to changes in political, environmental, economic, and social conditions.

The next strategy considered was index funds. The S&P 500 has earned an average of 11% per year since its beginning. What strategy could I create to earn more than this? It seemed to make the most sense just to buy an index fund and hold onto it.

An index fund based on the S&P 500 was my next investment. However, its performance was far less than anticipated. The broker insisted I just hold onto the fund and continued with the expected 11% annual average return.

Upon further inspection it appeared the broker was using arithmetic mean instead of geometric. For those that slept during statistics class, this may be a seemingly small nuance. However, the use of arithmetic mean over geometric hides allot of truth.

For example, if the fund halves, and then doubles, it is a zero gain. The geometric return is 0%. But my two annual returns are -50% and +100%. So according to arithmetic returns, I just earned a 25% per year average return.

Currently, the 11% quoted for the S&P 500 average return is based upon arithmetic mean. This means the actual geographic return is closer to 9.7%. The other issue is this measure does not take into effect inflation. Meaning a 2% return with a 2.5% increase in cost is not a profit at all. Adding inflation to the S&P 500 geometric mean makes it close to a 4% average annual return.

The average investor is reported to achieve a 6 to 7% annual average rate of return from their retirement account. That is based upon arithmetic mean and not accounting for inflation. Including all factors, these investors may be earning slightly better than a savings account.

The sobering truth is the quoted gains of portfolio theory do not tell the whole story. Average is not average. To break average you must ensure that the measure used takes into account all required variables.

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