Why I'll Never Buy and Hold a Stock Again

Everyone knows Amazon.com Inc. (NASDAQ: AMZN). The shares are up more than 2,000% in 10 years. It's the nation's largest retailer; dozens of companies list it as a significant threat to their business model in their annual reports.

Since Dec. 30, Amazon stock is up 20.9%, from $1,501.97 to today's opening price of $1,816.11.

And that's an okay return. Nothing wrong with that at all.

But... there are a few simple "behavioral rules" of when to move that you could've used to outperform that modest return by 67%.

I'm going to show you how - but before I do, know that I'm not talking about options, or buying a stock and waiting. And Amazon doesn't have a dividend, so scratch any rules like reinvestment from the equation.

And I'll spare you all the talk about standard deviations, terms like momentum, or reversion, behavioral bias... I won't make a peep about Trump's Twitter feed.

What I will say is that my eight years of graduate work in finance and behavioral economics, my time working on Wall Street, and my stint "in the shadows" of the Chicago Board of Trade led to the creation of a different type of tool. It can dramatically improve the predictive nature of stock movements - up, down, and flat.

What I'm going to show you is incredible...

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Remarkable Profits from a Regular Old Stock

Amazon.com isn't going away anytime soon. But over the next year, the stock price will ebb and flow across a variety of ranges, gaining and losing favor with various types of investors.

For example, during the week of Dec. 30, 2018, Amazon was trading at $1,501.97 per share.

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My signal said that it was time to buy that stock. It steadily increased for three weeks.

Then, during the week of Jan. 27, it said to sell those shares for $1,670 - an 11.1% gain.

At that point, you could have shorted Amazon, but the options were too expensive, given the volatility of the stock. Selling would have been better, because over the next four weeks, AMZN stock fell by 2.3%.

This movement proved to me that the stock was moving in a kind of behavioral loop - what I call the "Quantum Loop" - following the rules I'd derived from my research.

Sure enough, after a few weeks passed, it moved back into favor.

The proprietary factors that create what I call the Quantum Loop said it was time to buy again during the week of Feb. 24.

This time, Amazon shares sat at $1,631, or below where you would have initially sold the stock.

They would quickly take off again like a rocket... until May 5, a week before last, when the sell signal flashed again. Shares had jumped in five weeks to $1,950, or another 19.5% return.

But if you held Amazon past the day of the sell signal, you'd now have seen your investment decline by 6.8% from its high-water mark in almost a week.

By earning $168.03 on the first transaction on Amazon, missing that 2.3% decline in February, and buying back on Feb. 24 and riding the stock to $1,950... you'd have earned $526.03 on every Amazon share you own since the beginning of the year.

But if you bought and held the stock from Dec. 30 until today, you'd be up just $314.46.

In other words, the Quantum Loop would have produced 67.3% more money than a buy and hold strategy on the same stock over the same period of four months...

You Can See the Quantum Loop in Action Yourself

And that, folks, is why I won't buy and hold stocks. And I don't plan to ever again. It's how I used my own money to trade for so long and create so much wealth. It's why I'm a 38-year-old self-made millionaire.

Again, this technology is the result of eight intensive years of graduate work in quantitative methods and behavioral finance - work that led to monumental discoveries and massive gains.

But it's not just stories like Amazon. You've seen what it can do, and right now, I want to give you the chance to see exactly how this works...

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About the Author

Garrett Baldwin is a globally recognized research economist, financial writer, consultant, and political risk analyst with decades of trading experience and degrees in economics, cybersecurity, and business from Johns Hopkins, Purdue, Indiana University, and Northwestern.

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