There is a common saying in the investment markets that In the short run, the markets are a voting machine whereas, in the long run, they are a weighing machine. This saying is often said in order to emphasize the role of long term investment. People with short term goals often fail to perform well in the stock market. Despite all the emphasis on the long term, surprisingly, investors tend to focus a lot on the short term. Not only are their decisions related to forecasts of short-term future events, but these decisions are made on the basis of recent events, i.e., events that have taken place in the short-term past. This is called recency bias. In this article, we will have a look at what the recency bias is as well as how this bias impacts the performance of investors.
What is Recency Bias?
The gist of recency bias has already been mentioned above. However, the formal definition of recency bias states that it is a cognitive tendency of investors to place more emphasis on events that have taken place recently in the financial markets. To understand it better, we must think of the decision being made as a weighted average of our experiences in the past. We tend to give more weight to the event which has happened recently. If another event has happened five years earlier, it will be given less importance. Similarly, if another event has happened ten years earlier, then we tend to give it even less importance. This is in line with the way human memory works. Human beings tend to recall items at the beginning of a list of the ones which have been most recent.
How Recency Bias Affects Investment Decisions?
The biggest misuse of the recency bias is done by mutual funds and other fund managers. This is because these fund managers often use the track record of a couple of years when their funds have produced good returns in order to lure investors into making investments with them. They often don't provide any benchmarks for comparison. For instance, they might tell investors that the return for the past two years has been earned at 19% per annum. However, they will not tell how the fund performed prior to that.
The problem with the recency bias is that it deviates the investors from the cyclical nature of asset returns. In general, assets that have gone up in the past need not necessarily continue to go up in the future. On the other hand, it is quite likely that because of their cyclical nature, assets that have performed well in the past may have a greater likelihood of performing badly in the future since asset prices tend to move in cycles. Investors who have recency bias find assets with significant appreciation in the past to be unduly attractive. This makes them vulnerable to purchase stocks at the highest peaks.
Investors who suffer from recency bias tend to extrapolate current trends and predict the future based on very small sample sizes. For instance, they might only see the performance of the markets in the past two months or so and may extrapolate the trend to conclude how the market is poised to behave over the next decade.
Recency bias causes investors to place less importance on fundamental value and put undue emphasis on recent performance. For instance, in some cases, companies might need to take some short term losses in order to ensure long term gains. In such cases, if there is an undue emphasis on short-term returns from investors, which causes more harm to the company. The problem with the approach here is that it focuses only on the price-performance and not on the fundamental valuation. This is the reason that recency bias can cause principal losses to investors as well.
Recency bias often convinces the investors that the changes may be permanent this time. They tend to forget that over the long term, asset classes do revert to their means. Hence, until there has been a fundamental change in the industry, the situation may not be all that different as compared to the last time.
Recency bias causes investors to place all their eggs in one basket. Instead of having a diversified portfolio, they tend to have all their money in the same asset class, i.e., the one that has been appreciating the most in the past. Given the tendency of these investors to buy investments at the highest valuation, this can be a dangerous strategy. This irrational infatuation that investors may have with an asset class causes their portfolio to be damaged. This is because the behavior done by investors is the opposite of proper asset allocation, which is crucial for long term success.
How Can Recency Bias be Avoided?
The root cause of the recency bias is that the inference is drawn from the data sample, which is too narrow. Hence, in order to avoid recency bias, investors must make sure that they look at different types of data. For instance, they must look at the price-performance data as well as the fundamental valuation data. Also, they must look at various indicators over a longer period of time. The only way to avoid recency bias is to not be myopic.
It is important for investors to ensure that they are not afflicted with the recency bias. As we can see from the above article, the consequences can be quite grave.
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- Advantages of Behavioral Finance
- Limitations of Behavioral Finance
- FAQs About Behavioral Finance
- Prospect Theory
- How Loss Aversion Affects Investment Decisions
- The Sunk Cost Fallacy
- The Endowment Effect
- Regret Aversion Bias
- Self-Control Bias
- Anchoring Bias in Behavioural Finance
- Confirmation Bias in Behavioral Finance
- Herd Mentality Bias
- Mental Accounting
- Recency Bias
- Overconfidence Bias
- Conservatism Bias
- Framing Bias
- Behavioral Portfolios
- Hindsight Bias
- Illusion of Control Bias
- Status Quo Bias
- Sample Size Neglect
- Optimism Bias
- Cognitive Dissonance Bias
- Home Country Bias
- Availability Bias in Behavioural Investing
- The Bias Blind Spot
- The Narrative Fallacy
- The Planning Fallacy
- Base Rate Fallacy
- Contrarian Investing
- Cultural Influences on Financial Decisions
- Behavioral Life Cycle Theory
- The Barnewall Model
- Bielard, Biel and Kaiser (BBK) Model
- Three Dimensional Pscychographic Model
- Categorizing Behavioral Biases
- Lessons Learned in Behavioural Finance