Financial Market

Overconfidence bias and representativeness bias in equity investing decision

The past two to three decades are pronounced reminiscent of financial market volatility.

The decades witnessed the erosion and resurgence of the financial fundamentals in a stochastic manner. With the advent of transformative new technology and digital disruptions in the financial industry, markets remain highly volatile and vulnerable to exogenous and endogenous shocks. Despite the persistence of volatility in the domestic and world market, investments at the retail levels are gaining significant momentum.

It may be due to the advent of the financial industry’s astronomical shift, digital awareness, new investments and trading platforms, and the integration of global financial markets. One can attribute the above reasons to retail investments becoming more lucrative, toxic, and volatile. However, investors are more fragile and susceptible because investor sentiment, heuristics, biases, and herd behavior can enormously influence the future investment decisions of the investors.

Fundamentally, heuristics and biases are mental shortcuts that facilitate probability judgments and immediate problem-solving in investment decisions. Over-emphasis on these judgments leads to irrational and inaccurate investment decisions.

Today, let us understand the nuance of how overconfidence and representativeness biases significantly affect future investment decision-making. What are the remedial measures to avoid the same biases while investing in capital markets?

What is overconfidence Bias and Representativeness Bias?

Overconfidence bias is a radical human judgment error as humans are prone to psychological biases. Psychological research demonstrates that overconfident investors trade irrationally and excessively in markets that induce a lower rate of future expected returns. The belief of overconfidence may sub-optimally distort the retail as well as corporate investment decisions. This bias is considered a dangerous and prolific bias in the area of behavioral finance and capital market investments. It comes into three distinct forms, over-precision, over-placement, and over-estimation.

In financial markets, investors with overconfidence underestimate the risk, ignore the asymmetric information regarding the stocks, and often trade on non-fundamentals with exorbitant costs yielding low profits and underperformed stocks and creating divergence in the asset prices. This bias is remarkably prevalent in the financial markets as the basic sentiment intuition. The early correction of this bias is desirable to avoid substantial future losses in the financial markets.

Representativeness bias falls in the category of heuristics readily accessible shortcut mental process that facilitates problem-solving with a given similar situation. The representativeness heuristic is a behavioural bias which is an intuition that, under uncertainty, investors are prone to believe that a recent history of a remarkable performance of a given event is “representative” of general performance that the event will continue to generate in the future.

Such heuristics plummet the rational investing decision among investors. As primarily, investors violate the Bayesian principle of investments and give significant weightage to the recency effect and detriment of the past information. The voluminous psychological research pronounced the role of representative heuristics and highlights that these bias influences human judgment and creates systematic errors in investment decisions and portfolio rebalancing.

The novel prize winners and psychologists Kahneman and Tversky (1972) intuitively documented and subsequently adopted by the behavioural finance proponents that the heuristics bias such as representativeness creates overreactions and explains the stock market anomalies. In the stock markets, the investors who are subjected to these heuristics interpret that past performance, such as winners (losers), will be continuously gaining (losing) as winners (losers) in the current and future scenarios.

Prone to these biases, investors start their judgments and consider the firm’s consecutive earnings and profits in the future based on past performance. Along similar lines, investors do not choose the losers’ stocks with the assumption that the stocks will generate near-term losses. In this context, investors neglect the rational random model behavior in the stock markets, which is pertinent and exists worldwide.

How to avoid overconfidence bias and representativeness bias in equity investing decisions?
Markets’ functionalities are driven by basic theoretical principles such as fundamental analysis, forecasting the future, present value analysis, trend analysis, charts, patterns, etc. To avoid overconfidence and representativeness bias which are innate behavioral biases prevalent in the financial markets, one has to go by the real-time analysis of the markets based on market fundamentals, news, technical analysis, and critical evaluation of the economy, industry, and the company in which the stock is trading. Further, to eliminate the unwarranted and illogical faith created by these biases’ investors have to rationally use their abilities to predict the markets based on theoretical principles.

Essentially to avoid the representativeness bias, investors should not form investment decisions based on firms’ past years’ growth trajectory and decide that the firm will continuously grow in the near future. Moreover, past winners’ firms can be current looser firms and vice-versa.

To conclude, the investment process is a science and requires a sound theoretical analysis. Primarily, the investment strategies are formed, and portfolios are rebalanced. Hence, investors should use wishful thinking, due diligence, and market fundamentals to eliminate the components of overconfidence and representativeness bias.

Jyoti Kumari Rao is an Assistant Professor at the Department of Finance, IBS Hyderabad, Hyderabad. Her area of research includes Behavioral Finance, Asset Price Dynamics, Corporate Finance, and Capital Markets with a primary focus on the interactions among asset prices, corporate finance, investors sentiment, and volatility in the capital markets. 

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