According to the efficient market hypothesis it's impossible to "beat the market."
It argues that all information about a company is reflected in the stock's current price, so it's impossible to have any sort of market-beating edge. Dr. Eugene Fama, who came up with the theory, even won a Nobel prize in economics for his work.
Good thing he was wrong, because I've made my a career out of taking advantage of inefficient markets.
So have other well-known investors like Warren Buffett. He uses value as his edge, and was able to outperform the market for decades. Here's what he says about the theory:
"I'm convinced that there is much inefficiency in the market… In fact, market prices are frequently nonsensical."
And the traders best-able to profit from "nonsensical" prices aren't large institutional investors, it's retail investors like you and me. Big money investors, while powerful, are extremely slow to take action. It takes them weeks to buy and sell positions… their size is their disadvantage.
That's why I created the Alpha Rotation system — it's designed to take advantage of market inefficiencies to generate market-crushing returns.
The system has delivered a 2,436% return since 2010 — beating the market by a factor of 13x.
When I said the system was designed to beat the S&P 500, I meant that literally. The strategy revolves around creating a position — which I call a cluster — that is an optimized version of the S&P 500. We do that by going long the sectors in the S&P 500 (using ETFs) most likely to outperform over the next two weeks and short a sector that's likely to lag.
The ETFs are picked by a proven formula. It looks at volatility, relative strength, liquidity and market cycles. Because it looks at so many factors and has a built-in hedge, the system works in any market.
The end result is a ranking of which sectors will likely be the strongest and weakest over the next 14 days. I go long the cream of the crop sectors which are likely to outperform, and short the weakest sector.
Let me show you the trades we're in right now:
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