Beyond Efficiency: How Behaviour Shapes Market Patterns

On the surface, it may seem that markets tend to act rationally — prices move quickly to reflect new information, and easy opportunities disappear fast. But that’s not always the case. Some patterns keep reappearing — around the turn of the year, after strong price trends, or following earnings surprises. These patterns are too regular to dismiss as coincidence.

To understand why they persist, we need to look beyond the idea of markets as purely rational. Investor psychology — how people perceive risk, process news, and act in groups — can leave traces in prices that show up as recurring anomalies.

Table of contents

• What counts as a market anomaly?
• Behavioural explanations
• Why anomalies may not disappear
• Implications for the Efficient Market Hypothesis
• How investors should use anomaly evidence

What counts as a market anomaly?

A market anomaly is a repeatable event that cannot be fully explained by conventional risk, cash-flow, or interest-rate models. For example, the “January effect” (the tendency of stock prices, especially those of small caps, to rise early in the year), momentum (recent winners continuing to outperform in the near or medium term), value and quality premia, IPO underpricing with subsequent underperformance, and the tendency of prices to drift after earnings surprise, are all widely studied instances.

These patterns are not identical in every market or every decade; they vary with regulation, data dissemination, and institutional participation. Nevertheless, their persistence across geographies and time suggests that these drivers are linked to human behaviour and in the frictions that limit arbitrage.

The practical importance is straightforward. If such effects are durable after costs and capacity limits, they may inform portfolio design. If they are transient or crowded, they may become potential traps for late adopters.

Also Read: Behavioral Finance: Meaning, Types, and Its Importance

Behavioural explanations

Behavioural finance helps explain why markets do not always behave in line with the purely rational assumptions of the Efficient Market Hypothesis. It highlights the role of psychology, cognitive biases, and institutional pressures in shaping investor decisions — and how these can create persistent patterns such as momentum, reversals, and the disposition effect.

One driver is underreaction and limited attention. Investors and analysts may not fully incorporate new information immediately, particularly when the news is complex or buried in filings. Prices adjust gradually, creating momentum and post-announcement drift.

A second driver is overreaction, often fuelled by representativeness and availability. Salient narratives and striking recent events loom large, leading to overshooting after streaks of positive or negative news. Reversals over longer horizons may follow as expectations normalise.

Loss aversion and anchoring contribute to the disposition effect: investors sell performers too early to “lock in gains” and hold underperformers too long, hoping to “get back to even.” This behaviour increases the supply of outperformers and reduces the supply of underperformers, reinforcing momentum.

Herding and career concerns amplify both sides. Professionals who deviate too far from peers risk standing out if they are wrong, so they follow popular trades. The clustering of flows may move prices independently of fundamentals, especially in smaller or illiquid names.

Why anomalies may not disappear

Even if sophisticated investors recognise a mispricing, seeking to exploit it may be costly or risky. Shorting expensive securities involves borrowing fees, recall risk, and asymmetry of losses. Illiquidity and wide spreads make it expensive to trade precisely when dislocations are largest. Funding constraints and risk controls may force position cuts during drawdowns, long before convergence occurs.

Crowding is a second constraint. Once many investors pursue the same anomaly, the edge may dilute, and the trade’s risk may change in character—returns may become more correlated and exit doors narrower. The anomaly may persist in the data but may be unattainable at a meaningful scale.

These frictions explain why behavioural patterns may coexist with broadly efficient markets: small pockets of inefficiency remain because the costs and risks of eliminating them are non-trivial.

Read Also: The Role of Behavioural Nudges in Retirement Planning

Implications for the Efficient Market Hypothesis

The evidence does not require abandoning market efficiency. In liquid, well-covered securities around major announcements, prices typically incorporate information quickly, matching the semi-strong form of EMH. Behavioural finance complements this view by showing when and why prices may deviate: when attention is scarce, when narratives overpower analysis, or when arbitrage is constrained. The two perspectives are treated as baseline and can complement instead of contradicting each other.

How investors should use anomaly evidence

Investors may treat anomalies as hypotheses that must survive out-of-sample testing, realistic trading costs, and capacity limits. Try to ensure that any strategy based on a pattern has an economic or behavioural rationale, not just a back-test. Implementing through diversified, rule-based portfolios that avoid single-name concentration and define drawdown limits is also recommended.

Manage crowding risk by monitoring flows, correlations, and liquidity. A trade that once provided independent return may evolve into a pro-cyclical exposure when many investors chase it simultaneously. Thus, re-estimate expected returns after fees and slippage annually rather than assuming historical spreads will persist unchanged.

Finally, integrate governance that reduces behavioural mistakes within the investment process itself—fixed decision calendars, pre-committed rebalancing bands, and post-mortems—focusing on process quality rather than short-term outcomes.

Also Read: Impact of Behavioural Finance on Market Conditions

Takeaway

Recurring market patterns may be understood as the intersection of human psychology and real-world frictions, but not as proof that markets “do not work.” Awareness of these forces may help investors avoid blindly chasing seasonal effects or fashionable factors and encourage disciplined, capacity-aware implementation. In practice, a potentially resilient approach may be one that combines an efficient, low-cost core with selective, well-researched exposures to anomalies that are economically sensible, implementable at scale, and governed by risk limits.

At Bajaj Finserv AMC, we recognise that emotions are the cornerstone of investor behaviour – not just for investors but for investment professionals too. That’s why, behavioural finance is at the heart of our investment philosophy, InQuBe, which combines the Information Edge, Quantitative Edge and Behavioural Edge. By understanding, tracking and monitoring market sentiments and our own investment biases, we seek to make mindful and strategic investment decisions. Get the Behavioural edge by investing with Bajaj Finserv AMC. Read more about InQuBe here.

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