Recency Bias: Why Investors Chase Last Year's Winners

Key Takeaways

• Recency bias treats the most recent data as more predictive than long-run base rates justify, often turning short stretches into permanent regimes.
• Dollar-weighted fund returns trail time-weighted returns by roughly 1–2 percentage points per year, largely due to performance chasing.
• Extrapolating a single strong year into a multi-year forecast is the most common and expensive form of recency bias.
• Any strategy calibrated only on 2009–2021 data has been tested in one regime and has not been stress-tested across multiple market cycles.

What It Is

Recency bias is a cognitive shortcut where the most recent data dominates the forecast. Instead of averaging across a long sample, the mind treats the latest observation as a better predictor of the next observation than it actually is. CFA Institute classifies related behaviors under availability and extrapolation errors, both of which contribute to the recency effect.

In markets, recency bias routinely drives buy-high sell-low decisions. Fund flow data shows retail investors pouring into asset classes after strong performance and exiting after weak stretches, a pattern that persistently erodes dollar-weighted returns relative to time-weighted returns.

The Intuition

Think of recency bias as the opposite of averaging. A stock has returned 10 percent annually over 30 years but dropped 25 percent over the last six months. A long-run view says both numbers matter and maybe the drawdown creates opportunity. A recency-biased view says the last six months are the new regime, and the 30-year average is a historical curiosity.

The intuition has a real grain of truth. Markets do go through regimes, and the most recent data is sometimes the most informative. The problem is that recency bias treats every six-month stretch as a regime change, which it rarely is.

How It Works

Recency bias shows up in three patterns that repeat across cycles.

Performance chasing. Investors buy funds and asset classes after strong recent returns. Studies from Morningstar and others show that the dollar-weighted return on the average equity fund trails its time-weighted return by roughly 1 to 2 percentage points per year, largely because new money arrives after peaks and leaves after troughs.

Extrapolation. Forecasts for next-year returns correlate too strongly with last-year returns. Surveys of retail investor expectations consistently show peak optimism near market tops and peak pessimism near market bottoms, the exact opposite of what the base-rate data would suggest.

Compressed memory. The 2022 bear market pushed the 2008 financial crisis into distant memory for many investors. The more time passes since the last serious drawdown, the less the average portfolio behaves as though drawdowns are possible.

A common antidote is to widen the lookback window. If a decision is driven by the last 12 months of returns, force yourself to also look at the last 10 and 30 years. If those tell a different story, your prior is being dominated by recent noise.

Worked Example

In 2021, the real estate sector of the S&P 500 returned about 46 percent, making it one of the top-performing sectors. A recency-biased investor reviewing their allocation at the end of 2021 tilts heavily into real estate for 2022.

In 2022, the sector returned roughly negative 26 percent as rates moved sharply higher. The same investor, now facing a drawdown, cuts the position near the lows, locking in the loss.

The mistake was treating 2021 as a forecast. A longer lookback would have shown real estate's long-run return cluster, the interest-rate sensitivity embedded in the sector, and the fact that single-year leadership rotates year to year across sectors.

Common Mistakes

1. Confusing recency bias with momentum. Momentum, as a risk factor, is a real documented effect in the data. Recency bias is the overweighting of recent outcomes beyond what momentum-style evidence supports. You can follow a disciplined momentum rule without being recency-biased, and you can be recency-biased without owning any momentum strategy.

2. Extrapolating a single strong year into a multi-year forecast. One-year returns are noisy. Treating them as signal is the most common and most expensive form of the bias.

3. Forgetting prior crises after calm periods. Volatility regime shifts happen unpredictably. Long bull markets reduce the felt probability of a serious drawdown to zero in most investors' minds, which is exactly when position sizing should stay disciplined.

4. Using only post-2009 data for strategy design. Any framework calibrated on one regime, especially the low-rate period from 2009 to 2021, has not been stress-tested. Test across multiple regimes, including 2000, 2008, 2020, and 2022.

Frequently Asked Questions

What is recency bias in simple terms? Recency bias is the tendency to weight recent events more heavily than long-run statistics justify. In markets, it drives money toward last year's best-performing fund and away from last year's worst, regardless of either fund's actual long-run record.

How does recency bias affect investment decisions? It produces buy-high, sell-low patterns in fund flows. Dollar-weighted returns on the average equity fund trail time-weighted returns by roughly 1–2 percentage points per year because new money arrives after peaks and leaves after troughs.

What is a real-world example of recency bias? In 2021 the real estate sector of the S&P 500 returned roughly 46%. A recency-biased investor tilts heavily into real estate for 2022, which then returned approximately negative 26% as interest rates moved sharply higher. The 2021 return was one data point in an interest-rate-sensitive sector, not a forecast.

How can investors counter recency bias? Force a wider lookback window. If a decision is driven by 12-month returns, also look at 10-year and 30-year figures for the same asset class. If those tell a different story, your prior is dominated by recent noise rather than base-rate information.

How is recency bias different from momentum investing? Momentum, as a systematic factor, has documented positive excess returns and is measured, tested, sized, and rebalanced on fixed rules. Recency bias is the unsystematic, emotionally driven version, following recent strength without a defined process for entry size or exit criteria.

Sources

1. Schwab Asset Management. "Recency Bias." https://www.schwabassetmanagement.com/content/recency-bias
2. CNBC. "Recency bias: What it is and why it causes poor investment choices." July 2023. https://www.cnbc.com/2023/07/21/recency-bias-what-it-is-and-why-it-causes-poor-investment-choices.html
3. Morgan Stanley. "Behavioral Finance in the Markets: Identify Bias." https://www.morganstanley.com/articles/behavioral-finance
4. Northern Trust. "From Behavioral Bias to Rational Investing." April 2016. https://www.northerntrust.com/europe/content/dam/northerntrust/pws/documents/commentary/investment-commentary/behavioral-bias.pdf

Disclaimer

This article is educational content only and is not financial advice. Nothing here is a recommendation to buy, sell, or hold any security. Consult a licensed advisor before making investment decisions.