The market is about to get crazy.

Over the next month, stocks both large and small are going to be volatile. They’ll bounce around 10%, 20%, even 35% or more in a single day.

This “volatility season” was built into the financial system over 80 years ago by the U.S Securities and Exchange Commission (SEC), and there’s nothing you can do about it. It’s inevitable.

It’s more commonly known as earnings season.

Earnings are the true drivers of stocks, and I have good reason to believe a lot of companies are going to report lackluster results. For the next few weeks, we’re likely to see one-day stock moves of 5% to 15%-plus more frequently. This can result in quick losses or gains — depending on how you’re positioned.

If you could accurately predict whether a company will beat or miss earnings estimates before its quarterly report, then you could profit from the post-report move.

Over the years, I’ve developed a proprietary earnings algorithm that helps me do just that.

With it, I have been able to predict — with good odds — whether a company’s earnings will beat or miss the consensus.

For instance, in mid-October, my earnings algorithm predicted dividend darling Kinder Morgan (NYSE: KMI) would fall short of analysts’ estimates. The company’s bottom line was feeling the pinch from cheaper energy prices and shares looked expensive on a price-to-earnings (P/E) basis.

Sure enough, on Oct. 21 after the close, Kinder Morgan reported third-quarter earnings that fell short of expectations and shares plunged 5% in the next session. Within a week, they were down almost 12%.

Casino operator Wynn Resorts (Nasdaq: WYNN) is another example. When I ran it through my earnings algorithm in June, all of its readings were negative. Not only was it flashing all four “tells” I look for, but my technical indicators were extremely bearish as well. Shortly after my earnings algorithm flagged it as a dud, shares started dropping like a rock.

My system has also accurately predicted earnings-related moves in Apple, Amazon.com, Yelp, Keurig Green Mountain and hundreds of other stocks.

My System For Accurately Picking Earnings Surprises
Investors often take analyst recommendations — whether we should buy, sell or hold — at face value. But in the past 18 years, I’ve learned that there are overlooked details to these reports that tell a much different story. If you know what to look for, these details can spell big opportunity.

What makes my system different is that I analyze the analysts. Rather than sift through thousands of pages of data myself, I let the analysts do the work and then examine their actions leading up to earnings season.

My system essentially looks for patterns of bullishness or bearishness from the most accurate analysts and takes into account just how dramatic their shifts in sentiment are.

For example, if an analyst with a strong track record of making good calls lowers his earnings estimate by 20% below the consensus just days ahead of a report, you can bet he’s got a darn good reason. If other analysts are doing the same, even in subtle ways, they likely have information that’s going to impact the earnings report. That’s a warning I want to heed.

Basically, I figure out the “tells” of good analysts, compare them against a series of technical indicators and figure out which companies are likely to beat or miss earnings.

Earnings surprises offer the chance to make huge profits in a short amount of time. Readers who heeded my call on KMI made 50.6% in eight days. That’s an amazing 2,308.1% annualized. And those who listened to my WYNN warning netted 30.4% in just nine days, or 1,234.3% annualized.

As Q3 earnings season gets into full swing, I plan to make many more trades like this. And there is something about this earnings season that could make it especially lucrative for traders in the know — and incredibly painful for traders who are not.

If you’re interested in trading alongside me this “volatility season” for the chance to make some truly eye-popping profits, I have put together a free presentation with the details of my algorithm, which you can view here.