One of the recurring assumptions in financial theory is that investors form return expectations, adjust for risk, filter through their utility function, and then perfectly optimize their portfolio. This sounds great in a textbook. In the real world, it’s nonsense. People are messy. Markets are noisy. And portfolio decisions are usually a half-baked soup of heuristics, habits, and maybe—in the best cases—some coherent forecast.

But what happens if some people actually do put their money where their mouth is?

Christoph Merkle and Martin Weber decided to test this. And unlike most academic studies that rely on either surveys or transactions, this one used both. They surveyed 617 self-directed investors at Barclays Stockbrokers every quarter from 2008 to 2010. Investors provided specific return and risk expectations for the FTSE All-Share Index—and the researchers linked those responses directly to actual trades and portfolio holdings.

This gives us something rare: an opportunity to test whether what investors say lines up with what they do.

Let’s start with trading behavior. If someone becomes more bullish on the market, do they actually buy more?

Sort of.

Return expectations, on their own, don’t strongly predict trading activity. But changes in expectations do. When someone gets more optimistic about market returns, they’re more likely to increase their equity exposure.

So, beliefs do drive trading—but it’s not static levels of belief that matter. It’s the changes. Investors don’t act on where they think the market is going. They act when their view changes.

Risk expectations and risk tolerance? Practically irrelevant when it comes to trading volume or direction. So, if your broker’s risk quiz is the cornerstone of your asset allocation strategy… good luck with that.

Now here’s where things get interesting. While beliefs only weakly drive trades, they have a much stronger impact on portfolio risk.

When expected returns go up, investors increase portfolio volatility. When expected risk goes up, they dial it back. That might sound obvious, but it’s nice to see actual evidence of it. What’s more, these shifts aren’t just noise—they persist over time and hold up across multiple risk metrics (volatility, component volatility, etc.).

This is as close as retail investors get to tactical asset allocation. They’re not running optimizations, but they’re changing their mix of risky and less risky assets depending on their beliefs.

Also notable: beta didn’t matter. Investors weren’t adjusting their market sensitivity—they were loading up on higher-volatility names instead. This isn’t “market timing” in the Sharpe ratio sense. It’s more like they’re tilting toward risk when they feel lucky.

Want to know if someone’s optimistic? Don’t look at what they say—look at what they buy. Specifically, whether they start buying more volatile stocks.

The study finds that when people get bullish, they don’t just buy more equities—they rotate into riskier ones. When they get nervous, they do the opposite. The difference in volatility between what they buy and sell is statistically significant and economically meaningful.

This is your classic behavioral tilt. Instead of resizing the portfolio, investors just reach for higher- or lower-volatility instruments. It’s like turning the stereo volume up or down rather than switching the song.

And surprisingly, it mostly doesn’t matter.

Risk tolerance was captured using the usual kind of self-reported scale (“How much risk are you comfortable taking?”). And it turned out to have minimal predictive power when it came to actual portfolio decisions—especially in the moment.

Interestingly, lagged risk tolerance did have some relationship to portfolio risk, which suggests people might eventually align their behavior to their stated preferences, just not immediately. But overall, if you’re building portfolios based purely on a risk quiz, you’re probably using the wrong tool for the job.

One important theme across the paper is that investors don’t respond immediately. There’s lag. There’s inertia. People don’t dump their portfolios and build new ones every time their view changes. Instead, they make incremental adjustments over time. If return expectations go up, risk creeps up. If they get scared, they pull back—but maybe not all at once. This matters for anyone building models that assume investors re-optimize constantly. They don’t. They nudge.

This study is useful because it shows a few real-world behaviors that most models miss. Beliefs matter, but not in the ways textbooks suggest. Investors don’t act on absolute levels—they act on changes. Self-reported risk tolerance is mostly useless in predicting behavior. Risk adjustments tend to happen through asset selection (volatility targeting), not beta optimization or rebalancing. Retail investors aren’t as irrational as some think—but their decision rules are rough, slow, and imperfect.

If you’re a professional, this is good news. It means there’s still inefficiency in the way people trade. Retail traders are reacting to beliefs—but they’re doing it in crude ways. That opens the door for smarter allocation models and more nuanced signal-based trading.

If you’re building systems for clients, don’t expect them to update perfectly on new information. Build models that account for behavioral drag. Use their change in sentiment, not the level.

And if you’re a trader managing your own book? Well, at least know what you’re doing. Beliefs are fine. But make sure they’re part of a broader, diversified process—not the one bet you place after watching a bullish segment on CNBC.

Markets aren’t efficient. But they’re not idiotic either. This paper reminds us that people often do the right things—but only partway, and usually a bit late. The smart money doesn’t avoid this reality. It builds around it.

If you want to invest like a scientist, you’d better understand the behavior of the lab rats.

And sometimes, the rats are us.

Disclaimer

The FTSE All-Share Index is a stock market index that represents the performance of all eligible companies listed on the London Stock Exchange’s (LSE) main market, and it is considered one of the most comprehensive measures of the UK equity market.

This document does not constitute advice or a recommendation or offer to sell or a solicitation to deal in any security or financial product. It is provided for information purposes only and on the understanding that the recipient has sufficient knowledge and experience to be able to understand and make their own evaluation of the proposals and services described herein, any risks associated therewith and any related legal, tax, accounting, or other material considerations. To the extent that the reader has any questions regarding the applicability of any specific issue discussed above to their specific portfolio or situation, prospective investors are encouraged to contact HTAA or consult with the professional advisor of their choosing.

Except where otherwise indicated, the information contained in this article is based on matters as they exist as of the date of preparation of such material and not as of the date of distribution of any future date. Recipients should not rely on this material in making any future investment decision.