Investor Bias Grows When Reliable Data Disappears

Investors rarely make decisions with complete information. Financial statements describe the past, analyst forecasts depend on assumptions, and market prices can move before an individual understands why. The result is an environment in which judgment must fill the gaps left by uncertain or unavailable evidence.

A new study¹ published in Acta Psychologica suggests those gaps can make cognitive biases more influential. Based on responses from 620 individual investors participating in the Pakistan Stock Exchange, the researchers examined how anchoring bias, framing bias, and risk perception relate to investment decisions under different levels of information asymmetry.

The central finding was not simply that investors can be biased. It was that the surrounding information environment appears to determine how much those biases matter. When participants reported low information asymmetry, the indirect relationships between the two biases and investment decisions were not statistically significant. At medium and high levels, the relationships became significant and progressively stronger.

This suggests that transparency is more than a matter of regulatory compliance. Reliable information may function as a behavioural safeguard by giving investors evidence against which they can test their initial impressions.

How Anchoring Bias Distorts Investment Decisions

Anchoring occurs when an investor gives disproportionate importance to an initial number or reference point. In financial markets, the anchor might be a purchase price, historical high, analyst target, recent index level, or expected return.

Suppose an investor buys a stock at $80 and it falls to $55. The original purchase price can remain psychologically important even if the company’s fundamentals have deteriorated. Rather than asking whether the stock is worth $55 today, the investor may focus on whether it can return to $80. That anchor can encourage the investor to hold a weakening asset because selling would turn the difference into a realized loss.

Anchoring can work in the opposite direction as well. A stock that once traded at $20 may appear expensive at $40, even if improved earnings justify a much higher valuation. The historical price feels informative despite no longer representing the underlying business.

The study found a positive association between anchoring bias and risk perception. It also identified a small but statistically significant indirect association between anchoring and investment decision-making through perceived risk. In practical terms, anchors appear capable of changing how investors interpret uncertainty before they decide to buy, sell, or hold.

This finding complements the broader collection of psychological and structural hazards covered in the Investor Safety Toolkit. A numerical reference can appear objective while still pushing an investor toward a conclusion that the latest evidence does not support.

Why Framing Can Be More Powerful Than Facts

Framing bias arises when equivalent information produces different reactions depending on how it is presented. An investment with a 70% probability of success can feel more attractive than one described as having a 30% probability of failure, even though the underlying probabilities are identical.

Financial information is rarely presented neutrally. Earnings can be described as beating expectations or slowing from the previous quarter. A decline can be framed as a discounted entry point or evidence of a failing investment thesis. Even technically accurate descriptions can direct attention toward either potential gains or possible losses.

Framing had a stronger relationship with risk perception in the study than anchoring did. Its standardized effect was 0.280, compared with 0.147 for anchoring. The indirect association between framing and investment decisions through risk perception was also larger.

That difference matters in markets increasingly shaped by mobile applications, social feeds, creator commentary, and AI-generated summaries. Investors do not merely receive facts. They receive headlines, colours, alerts, rankings, sentiment indicators, and condensed explanations that determine which facts attract attention.

Research into why investors remain cautious about AI stock advice points to a related problem. Faster analysis does not automatically create better decisions if investors cannot understand how a recommendation was produced or determine whether important context was excluded.

Study Results On Bias And Information Asymmetry

The following results are derived entirely from the study. They show that the observed relationships were statistically significant but modest, reinforcing the need to avoid treating cognitive bias as the sole explanation for investment behaviour.

Transparency Functions As A Behavioural Risk Control

The study’s most useful insight is that information asymmetry changed the strength of the relationship between perceived risk and investment decisions. When reliable information was limited, investors had fewer external references with which to challenge an anchor or re-evaluate a framed message.

This helps explain why the same cognitive bias may produce very different outcomes across markets. In a widely followed company, investors can compare audited statements, regulatory filings, earnings calls, independent research, and competing analyst opinions. In a thinly covered security, they may depend heavily on promotional material, rumours, social-media posts, or a single commentator.

More information is not automatically the solution. A flood of repetitive content can create the illusion of confirmation without adding independent evidence. Ten accounts repeating the same bullish claim are not ten distinct sources if all obtained it from one press release.

What matters is access to information that is timely, verifiable, balanced, and sufficiently independent to challenge the prevailing narrative. Investors can improve that process by:

• Recalculating value without using the purchase price as an input
• Comparing both upside and downside versions of the same thesis
• Tracing repeated claims back to their original source
• Defining evidence that would invalidate the investment thesis

These practices convert vague caution into a repeatable decision process. They also reduce dependence on whatever price, headline, or forecast first captured the investor’s attention.

Digital Platforms Can Reduce Or Reinforce Bias

Trading platforms occupy an unusual position. They can narrow information gaps by distributing research, real-time data, risk metrics, and educational material to millions of users. At the same time, interface choices can frame opportunities and influence which reference points users notice.

A platform that prominently displays an asset’s all-time high may encourage a different judgment than one emphasizing valuation, drawdown, or long-term volatility. Notifications describing an asset as trending can create urgency without improving the information available. Social features can expose users to new ideas but can also make popularity appear equivalent to quality.

The growth of retail algorithmic trading adds another layer. Automation can help enforce predetermined rules and reduce emotional interference, but an automated strategy still reflects the assumptions and data selected by its creator. Technology can discipline a sound process or accelerate a biased one.

The most constructive platform design would provide multiple time horizons, balanced risk scenarios, source transparency, and prompts that encourage users to test rather than merely confirm a position. Such features may not maximize immediate engagement, but they could strengthen trust and improve decision quality over time.

Investing In The Evolution Of Retail Brokerage

For investors seeking exposure to companies developing this financial infrastructure, Robinhood Markets (HOOD ) (NASDAQ: HOOD) offers a relevant example. The company has expanded beyond basic mobile trading into research, market information, retirement accounts, advisory connections, advanced trading tools, social features, and AI-assisted investing.

Robinhood’s scale makes information presentation commercially important. In its second-quarter 2026 results, the company reported record revenue of $1.3 billion, record net deposits of $22 billion, and 4.8 million Gold subscribers. It also said that it added nearly one million funded customers during the quarter.

Its opportunity is to make sophisticated financial information accessible without overwhelming users. Its challenge is that research tools, AI-generated insights, social activity, and interface design can all affect how customers perceive opportunities and risks. As these features grow, balanced presentation and transparent sourcing may become product advantages rather than compliance obligations alone.

Investors considering Robinhood should still account for its exposure to trading activity, interest rates, regulation, competition, cryptocurrency markets, and changing retail sentiment. The company is pertinent here because it operates where investor psychology, market information, and financial technology meet, not because the study tested Robinhood or its users.

What Investors Should Take From The Research

The study does not show that anchoring or framing directly causes poor returns. Its cross-sectional design captures associations at one point in time, and all principal variables were self-reported. Participants were recruited primarily through brokerage houses in Faisalabad, limiting how confidently the findings can be generalized to other countries, institutional investors, or app-based traders.

The model also explained only 6.1% of the variation in investment decision-making. Financial literacy, experience, income, risk tolerance, previous gains and losses, market conditions, professional advice, and other biases likely account for much of the remainder.

Nevertheless, the conditional pattern is valuable. Bias mattered less when participants perceived the information environment as reliable and became more influential as information asymmetry increased. That supports a practical conclusion: the best defence against distorted judgment is not confidence in one’s objectivity. It is a process that introduces credible evidence, alternative interpretations, and explicit reasons to reconsider the initial view.

In markets filled with increasingly persuasive interfaces and automated analysis, access to information alone will not define investor advantage. The ability to distinguish independent evidence from repetition, presentation, and psychological anchoring may prove considerably more important.

References:

^{1. Ashraf, A. A., Naveed, F., & Ishfaq, M. (2026). Cognitive biases, risk perception, and investment decision-making under information asymmetry: A moderated mediation study. Acta Psychologica, 270, 107632. https://doi.org/10.1016/j.actpsy.2026.107632}