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Over the past month, the media have had a field day referring to the 200-day moving average. As in:

"The S&P index just crossed its 200-day moving average. This is a very bullish sign."

" Microsoft ( MSFT) crossed its moving average, so we should expect to see a nice upwards move over the next week."

I was skeptical. It doesn't seem to make sense to me that this would be a bullish event. Most of the time when I read or hear about the 200-day moving average people are talking about the entry -- or the crossover of the average -- but never the exit, so it was hard to formulate a successful trading strategy.

Also, I was never sure what people meant by the word "bullish." Does this mean the market goes up forever now -- or just tomorrow?

To make sense of things, I decided to take a closer look at the 200-day moving average, what it signals and exactly how "bullish" it is. In general, my focus as an investor and hedge fund manager is to develop a hypothesis about the markets, whether based on fundamentals or price action, and test, test, then test again. No words of wisdom, or so-called 'truisms', about stock or indices are above being rigorously studied and verified as best one can before investing money.

I ran a few tests to get to the bottom of the 200-day moving average. I attempted to mirror and test the media prognosticators who forecast the change in trend with each move in the 200-day moving average. As you will see later on in this column, I came up with a long-only system -- in other words, it's only good for the long side of the market -- for using the 200-day moving average as a countertrend indicator that has worked well in both bull and bear markets.

But first things first: What is the 200-day moving average?

Simply put, it's the prices of a stock, or market index, the prior 200 days, added together and divided by 200. As can be seen in the following chart of the 200-day moving average -- the brown line -- most of the time when we are in a bull market, the closing daily price of the S&P is above the 200-day moving average. And most of the time when we are in a bear market, the closing price of the S&P 500 is below the 200-day moving average.

S&P 200-Day Moving Average
The 200-day in relation to bull/bear markets.

The real question is, when the daily price of the S&P closes over the 200-day moving average, are we also moving from a bear period to a bull period?

To see if this trend-following assumption is true I ran three tests, labeled A, B and C. Here are the tests and results:

Test A: Buy the S&P when the close crosses over the 200-day moving average. Sell when the S&P crosses below the 200-day moving average. I felt this most closely mirrored what the media is forecasting when they mention this average.

Result: It's hard to qualify this as "bullish," but the results do yield positive returns. The winners are often huge wins and the losing trades are relatively tiny. However, only 28% of the occurrences of this system have resulted in a positive trade. In other words, if the S&P closes above its 200-day moving average, then there is a 72% chance it will be lower by the time it goes below its 200-day moving average. That said, doing this trade on every occurrence since 1950 would've made an investor money in the long haul:

Of the 142 occurrences since 1950: Forty successful, 102 unsuccessful, with an average return per trade of 3.23%, including the losses. If you put a $10,000 put into this system in 1950, it would be worth $55,000 today. If you put a $10,000 put into a buy-and-hold strategy, however, it would be worth $494,000.

There have been many false starts to this indicator -- particularly since Jan. 1, 2000, with 17 occurrences and only two successful. This includes the most recent occurrence, which opened April 21 and hasn't closed yet. So when someone says "we just crossed over the 200-day moving average so now we are in a bull market," it's best not to believe it.

Buy Above the 200-Day, Sell Below
Only 28% of the trades in this test resulted in a positive outcome.
Source: James Altucher

Click here to see larger image.

Test B: Buy the S&P when the close crosses the 200-day moving average, and sell one day later. The idea here is: Maybe people get so excited about the event of the crossing that they rush to buy.

Result: Mildly positive, but not statistically significant and does not beat commissions and slippage. Of the 147 occurrences (not 142 like before?) since 1950, 74 were successful and 73 were unsuccessful, with an average return of 0.11% -- equivalent to 1 point in the S&P today.

However, the results get a little better when you buy the 200-day crossover and hold for one month. Under these circumstances, you have a 72% success rate with an average gain of 1.65% as opposed to the 0.68% average monthly return since 1950. The last trade in this system started on April 17 and ended on May 16, for a gain of 5.68%.

So perhaps it is bullish when the S&P 500 crosses its 200-day moving average and you hold for a month. Basically, you get double the return per trade of random buy-and-holding for a month.

Holding for a quarter doesn't improve the results: You would get 2.67% per trade as opposed to an average quarterly return of 2.04% since 1950.

Test C: What happens now if you run the "one-month" system described in test B on a basket of your favorite stocks? Buy a stock when it crosses its 200-day moving average, and sell one month later.

I ran the test on the stocks in the S&P 400 mid-cap index over the past eight years. I ran it as a simulation where each trade took up 1% of equity and tabulated the results. Results were marginal: an average return of 0.62% per trade with the following yearly returns demonstrating that you would've survived the worst of the bear market but still taken a big hit in 2002.

S&P 400 Mini-Cap Index
Buying a stock when it crosses the 200-day and selling a month later offers marginal results.
Source: James Altucher

In general, although conceptually it does seem bullish when the indices cross their 200-day moving averages, it does not seem like there is a worthwhile trading strategy that results. Tests A, B and C bore little fruit.

One More Try

I decided to try one more approach. A contrarian one that depends on the concept of mean reversion -- i.e., when the price of the S&P hits an extreme low relative to its 200-day moving average, one should buy. Specifically:

Buy when the S&P closes 20% below its 200-day moving average (e.g., the crash of 1987 or on Sept. 20, 2001) and sell one month (20 trading days) later. Very simple.

Result: Since 1950, if you made this trade in all 79 occurrences, 65 of which were profitable (82%) and 14 unprofitable (17%), for an average return of 6.43% per trade as opposed to a return of 0.68% if one randomly buys any month. Not bad.

It gets even better when you measure more recent history. If you look at the data for the S&P 500 index since 1975, this system would've resulted in 34 out of 34 successful trades with an average return of 10% per trade. The last trade started on Oct. 10, 2002, ended on Nov. 7, 2002 -- and returned a nice 12.28%. That's enough to pay the bills and have a nice glass of wine to celebrate.

Arguing about the trend of the market based on the 200-day moving average might be fun at cocktail parties (depending on your definition of fun) but won't really make anyone money. Instead, buying when the trend is absolutely, unequivocally down and the market is plummeting vis a vis its 200-day moving average is usually the best time to take a trade on the long side. By the time the talking heads are debating a new trend when price closes above the 200-day moving average you are long gone out of the market, hopefully on vacation.
James Altucher is a partner at Subway Capital, a hedge fund focused on deep value and arbitrage opportunities, where opportunities are identified using proprietary software. Previously, Altucher was a partner with technology venture capital firm 212 Ventures and was CEO and founder of Vaultus, a wireless and software company. He holds a B.A. in Computer Science from Cornell and was a Ph.D. candidate in Computer Science at Carnegie Mellon University.