Stockbroker Fred Schwed asked the question in the title of his 1940 classic book, Where Are the Customers’ Yachts?

Fast-forward 80 years, and the question remains the same.

Many investors spend countless hours poring through fundamental research produced by Wall Street’s investment banks.

This focus on company fundamentals, however, masks a new, broad and deep-rooted trend: Computer-driven strategies are transforming the way Wall Street invests.

And this transformation has profound implications for how you invest your hard-earned nest egg.

The “Good Old Days” of Investment Management

Being a portfolio manager was a lot more fun 20 years ago than it is today.

I was an emerging markets portfolio manager in the 1990s. The investment banking analysts I saw in London generated reports on the fundamentals of companies. They would bring these companies’ management teams around a few times a year to provide us with regular updates.

My job was to make investment decisions based on these reports and meetings.

Luckily, my job also included visiting companies to “kick the tires.” So I got to travel to Istanbul, Tel Aviv and Moscow to visit factories and production plants.

None of us questioned this approach. As both portfolio managers and financial analysts, this is what we were trained to do.

Even Warren Buffett applied what he learned from Benjamin Graham and David Dodd’s Security Analysis (written in 1934) to identify cheap and ignored companies.

We were simply applying those same skills to our little corner of the investment world.

The New Analysts of Wall Street

The world of investing has changed much since then.

Twenty years ago, you needed an MBA or CFA to become an analyst or portfolio manager on Wall Street.

But those skills alone don’t cut it anymore. Instead, many of today’s leading Wall Street analysts have become data miners.

They pore through reams of data and identify “factors” that help a particular group of stocks beat the market.

Traditional financial analysis teaches you none of those skills. Today, knowing a programming language like C++ trumps the ability to analyze a cash flow statement.

I see three reasons for this change.

No. 1: The Rise of ETFs and Passive Investing

Computing power has expanded the number of investment strategies accessible to retail investors.

Two decades ago, investing in only the Dividend Aristocrats was almost impossible in practice. You’d have to track, buy and sell 50 or so stocks regularly. The commissions alone would have eaten up your profits.

Today, you can buy an ETF like the ProShares S&P 500 Dividend Aristocrats ETF (CBOE: NOBL) at the click of a mouse.

No wonder demand for knowledge about ETFs has exploded. Bank of America even set up a team to track ETF strategies for investors.

No. 2: The Explosion of Data

Back in the day, Buffett-style fundamental analysis gave an experienced financial analyst an edge. That is no longer the case.

Today, you can identify the world’s cheapest stocks on dozens of free websites with a few clicks of a mouse. And you have more information on the smartphone in your pocket than Bill Clinton had as president 20 years ago.

To add value, analysts use artificial intelligence and machine learning to glean fresh insights from data. They also sift through new sources of information like satellite imagery and credit card data.

Not surprisingly, investment banks’ research departments have changed what they offer to clients. UBS Evidence Lab collects, cleans and sells data to clients. Morgan Stanley’s AlphaWise, a unit of about 100 data scientists, coders and analysts, does the same.

No. 3: No Opinions, Please

Sure, CNBC’s bread and butter is market analysts who give their opinions. And Jim Cramer’s nightly rants attract millions of viewers.

But today Wall Street’s smart money views such predictions as entertainment, not analysis.

Just 10% of trading on Wall Steet is based on traditional stock picking. The smart money does not base its investment decisions on an analyst’s latest predictions.

It relies on its rocket scientist coders instead.

How has this trend in investment management affected my trading and investing?

It has changed it much more than I would have ever expected. A computer generates all the new recommendations for my Oxford Wealth Accelerator Tactical Portfolio.

And the Strategic Portfolio is made up exclusively of data-driven “smart beta” ETF strategies. The same applies to the Income Portfolio.

Today, I don’t visit a Coca-Cola bottling factory in Ukraine to make my investment recommendations. Instead, computers generate all of my investment portfolio recommendations.

Welcome to the new world of investment management.

Good investing,

Nicholas


Interested in hearing more from Nicholas? Follow @NickVardy on Twitter.