How Smart Investors Actually Pick Stocks: What the Data Says

When you invest, what are you really trying to do? You’re trying to maximise return while managing risk. Simple in theory. But in practice, investors often fall prey to fads, emotions, and noise.

Instead, what if we could base our strategy on actual academic evidence? That’s where decades of financial research—some of it dry and buried in academic journals—can suddenly become your secret weapon.

Let’s decode that research. And let me show you how I’ve used it over decades of hedge fund management to separate hype from substance.

The Power of Diversification: Where Modern Investing Began

It all starts with Harry Markowitz, who introduced Modern Portfolio Theory (MPT) in 1952. His basic insight? You shouldn't pick stocks in isolation—you should build portfolios that balance risk and return.

Figure 1: Markowitz Portfolio Selection

In this chart, each point represents a possible combination of assets. The curve is the efficient frontier—portfolios that offer the best possible return for a given level of risk (measured by standard deviation). Point M is the market portfolio, the optimal mix under certain assumptions.

So why does this matter? Because this was the first mathematical proof that diversification isn’t just wise—it’s quantifiably optimal. And today, we still use the backbone of this model to construct ETFs, retirement portfolios, and hedge fund strategies.

Adding the Risk-Free Asset: The Capital Market Line

MPT tells us how to combine risky assets, but what happens when we also include a risk-free asset—say, a government bond?

That leads us to the Capital Market Line (CML), derived from the Capital Asset Pricing Model (CAPM), one of the most important models in finance.

Figure 2: Capital Market Line

This straight line shows the highest return you can achieve for any level of risk when you can combine a risk-free asset with the market portfolio.

Now let’s look at points A and B.

• Point B is a diversified portfolio that combines some risk-free asset with the market.

• Point A is riskier—leveraging up by borrowing at the risk-free rate and investing more into equities.

The lesson? The best portfolios lie on the Capital Market Line, not below it. If you’re sitting below that line, you’re not getting enough reward for your risk.

Too many investors hold portfolios below that line without knowing it.

So What About Individual Stocks? Let’s Talk Beta

The CAPM introduced the concept of beta, which measures a stock’s sensitivity to market movements. A beta of 1 means the stock moves in line with the market; greater than 1 means more volatile; less than 1 means less.

So the theory goes: higher beta → higher expected return.

Let’s see if that holds true.

Figure 3: Beta and Average Return for Portfolios Formed on Size

Here, portfolios sorted by size and beta appear to follow the classic CAPM prediction: higher beta portfolios earn higher average returns.

This supports the idea that beta matters. You can “dial up” or “dial down” your portfolio’s expected return by choosing high- or low-beta assets.

But real life isn’t so neat. Enter Figure 4.

Reality Check: When Theory Meets Messy Markets

Figure 4: Beta and Average Return for Portfolios formed on Size and Beta

This is where things get interesting.

In this scatterplot, we see no clear relationship between beta and return. Some high-beta stocks underperform. Some low-beta stocks outperform. It’s noisy. It’s messy. It’s real life.

So what do we take away?

Beta alone doesn’t explain returns. And that’s what decades of research have confirmed: markets are more complex. Factors like company size, value vs. growth, momentum, and quality all play major roles.

That’s why I don’t just buy the highest-beta stocks. Nor do I blindly trust the CAPM. What I do trust is evidence-backed multifactor investing.

What This Means for You: Lessons for Smarter Investing

So let’s tie this all together.

1. Diversification Still Wins

Don’t try to pick the one magic stock. Use diversification to reduce risk without necessarily sacrificing returns. This is MPT 101, and it still works.

2. Use the Capital Market Line as a Benchmark

If your portfolio lies below the Capital Market Line, you’re not optimising. Combining low-risk assets with the market portfolio can be more efficient than any single stock pick.

3. Beta Is a Starting Point, Not the Whole Story

Yes, beta has some predictive power—but it’s not enough. Don’t build portfolios based solely on it.

4. Factor Investing Is the Future

Investors should consider additional proven factors:

• Value (cheap vs. expensive stocks)

• Size (small companies may outperform)

• Momentum (stocks that have done well tend to keep doing well)

• Quality (strong balance sheets, high return on equity)

Fama and French’s three-factor and five-factor models are based on exactly this logic.

How I Use This at Campaign for a Million

At www.campaignforamillion.com, I aim to help 1 million people become smarter investors by sharing the principles hedge funds rely on—minus the jargon and management fees.

I look for stocks and ETFs that sit on the efficient frontier, or as close to it as possible. I also screen for:

• Low volatility relative to return

• Exposure to multiple return-driving factors (not just beta)

• Assets that lie on or above the Capital Market Line

Because here’s the kicker: the average investor has access to the same tools the pros do. The only difference is that most retail investors don’t know how to use them.

Theory Is Good, Results Are Better

Markowitz. CAPM. Beta. Efficient frontiers. These aren’t just academic terms—they’re tools. But like any tool, they only work if you know how to use them properly.

What matters most is how you apply them to your portfolio.

So the next time you hear someone brag about their one hot stock tip, show them Figure 4. Then ask them: is your portfolio on the Capital Market Line?

Because investing isn’t about guessing. It’s about understanding risk, probability, and strategy.

Sources:

• Explaining Stock Market Returns – Literature Survey (IFA)

• Fama, Eugene F., and Kenneth R. French. "The Cross-Section of Expected Stock Returns." Journal of Finance, 1992.

  
  

  RISK WARNING: All investing is risky. Returns at not guaranteed. Past performance and case studies are no guarantee of future results.

  
  

  Disclaimer: The content provided on this blog is for informational purposes only and does not constitute financial advice. The opinions expressed here are the author's own and do not reflect the views of any associated companies. Investing in financial markets involves risk, including the potential loss of your invested capital. Past performance is not indicative of future results. 

  
  

  You should not invest money that you cannot afford to lose. Mentions of specific securities, investment strategies, or financial products do not constitute an endorsement or recommendation. The author may hold positions in the securities discussed, but these should not be viewed as personalised investment advice. 

  
  

  Readers are encouraged to conduct their own research and seek professional advice before acting on any information provided in this blog. The author is not responsible for any investment decisions made based on the content of this blog.

  
  

  Alpesh Patel OBE

  www.campaignforamillion.com