Explore how the presentation of information influences investor decision-making, with real-world examples and mitigation strategies.
Have you ever found yourself making two completely different decisions based on how a question was asked? For instance, maybe you once jumped at the chance to buy a stock when someone said, “It has an 80% chance of going up,” but you hesitated when someone else said, “Well, there is a 20% chance it might drop.” Both statements actually convey the same probability—just framed differently. That’s what we call framing.
In this section, we explore the powerful effect that “framing” can have on investment selections. We’ll look at how certain marketing messages, product presentations, or even the names of strategies can drastically alter how we perceive risk and reward. We’ll tie these insights back to broader behavioral finance concepts—especially Prospect Theory, which helps explain why a positive or negative frame can push investors into making less-than-rational choices. By the end, you’ll see that framing is not just an academic concept but a critical real-world factor in portfolio management.
Framing refers to how the presentation or “frame” around a piece of information influences decisions, even when the underlying data remain constant. Sure, it sounds simple, but the ramifications are huge. In portfolio management, a risk can appear more or less severe based solely on the words or structure used to describe it.
When a scenario is presented in a “positive frame,” the emphasis is placed on what you stand to gain. On the other hand, a “negative frame” focuses on potential losses or undesirable outcomes. Because investors tend to be loss averse (that is, they feel the pain of losses more strongly than the pleasure of gains), negative framing often induces a different—sometimes more cautious—approach compared to positive framing.
Prospect Theory, developed by Daniel Kahneman and Amos Tversky, is the foundation for understanding how framing intersects with decision-making. Traditional finance might say, “A rational investor makes choices purely based on expected utility.” But Prospect Theory highlights that people weigh gains and losses differently and are influenced by reference points or how a question or outcome is framed.
In formal terms, traditional expected utility might be written as:
where \( p_i \) is the probability of outcomes and \( x_i \) are the payoffs. Under Prospect Theory, however, the utility function becomes asymmetrical, emphasizing that losses hurt more than gains of a similar size feel good, and that framing can shift the reference point that defines what counts as a “loss” vs. a “gain.”
• Positive Frame Example: “This mutual fund has outperformed its benchmark 80% of the time.”
• Negative Frame Example: “This mutual fund has failed to exceed its benchmark 20% of the time.”
Both statements say exactly the same thing, numerically speaking. However, many investors feel more comfortable hearing the positive framing because it highlights their potential success.
Similarly, compare “If you invest in this bond, there’s a 95% chance you’ll receive all your principal plus interest” with “There’s a 5% chance this bond will default.” You might get spooked by the second version, even though it provides the same information. That’s framing in a nutshell.
Let’s say a financial advisor markets a retirement plan with the tagline, “Secure your golden years—your principal is protected in most market conditions.” Potentially, that’s a bright, confidence-building message. But if the same plan was advertised as “Under severe conditions, your principal could still decline,” you might be more skeptical. This phenomenon is why marketing campaigns often focus on positives: they know that how you frame a product can invoke enthusiasm or fear, and that can determine whether an investor commits.
On a personal note, I (the author) once nearly passed on a seemingly attractive hedge fund strategy. The word “loss” was sprinkled throughout the marketing materials—albeit in a factual context—so it felt risky. When the same strategy was presented with an emphasis on “capital preservation,” I suddenly felt more at ease, even though the underlying strategy was identical. It was a revealing moment about framing’s power to shape one’s perception.
Framing rarely operates in isolation. It often interacts with other cognitive biases:
• Loss Aversion: Investors already hate losses more than they enjoy equivalent gains. When you frame the same outcome as a potential loss, it can heighten a loss-averse response.
• Confirmation Bias: People might select the framings that confirm their preexisting attitudes. If they’re bullish on a stock, they seek out the “80% chance of success” messaging. If they’re bearish, the “20% chance of failure” resonates.
• Anchoring Bias: A positively framed anchor, like “average 15% annual returns,” could anchor an investor to overly optimistic expectations, even if the strategy’s probability distribution is more nuanced.
When constructing or rebalancing a portfolio, how an advisor frames the potential risk-return trade-off can nudge an investor into more (or less) conservative allocations. A “fear-based” presentation of certain equities might skew them to overweight conservative assets like Treasury bills, while a “growth-oriented” pitch might encourage heavier equity exposure.
Framing can also affect the perceived severity of risk events. A manager might downplay the potential drawdowns by focusing on the long-term average returns. Conversely, focusing on short-term volatility might scare off an investor who otherwise would have benefited from a riskier but higher-expected-return asset.
During times of market stress (like a market correction or a sudden geopolitical crisis), the framing of what’s happening in the market can shape immediate tactical decisions. An investor confronted with “There is a 25% probability of losing more than 10% of your portfolio in the next three months” will likely make different decisions compared to hearing “There is a 75% probability you will lose less than 10%.”
Below is a short snippet of Python code showing a simple simulation of how decision-making could shift under different frames, even though the probabilities remain the same:
1import numpy as np
2
3np.random.seed(42)
4num_scenarios = 10
5
6prob_success = 0.80
7prob_failure = 1 - prob_success
8
9decisions_positive_frame = []
10decisions_negative_frame = []
11
12for i in range(num_scenarios):
13 # In a real world situation, more data would shape these decisions
14 # For demonstration, we'll randomly choose an acceptance threshold
15 threshold = np.random.uniform(0.5, 0.9)
16
17 # Positive framing decision
18 if prob_success > threshold:
19 decisions_positive_frame.append("Invest")
20 else:
21 decisions_positive_frame.append("Reject")
22
23 # Negative framing decision
24 if prob_failure < (1 - threshold):
25 decisions_negative_frame.append("Invest")
26 else:
27 decisions_negative_frame.append("Reject")
28
29print("Decisions with Positive Frame: ", decisions_positive_frame)
30print("Decisions with Negative Frame: ", decisions_negative_frame)
In reality, context is everything—desired return, volatility tolerance, and so forth. Nonetheless, you’d be surprised how the lens of “80% success” vs. “20% failure” can shift the decision.
Below is a simple Mermaid diagram illustrating how framing leads an investor from the same situation to two different decisions:
flowchart TB
A["Information Presented <br/> (Same Underlying Data)"] --> B["Positive Frame <br/> Highlights Gains"]
A --> C["Negative Frame <br/> Highlights Losses"]
B --> D["Investor Perceives Lower Risk <br/> => More Likely to Invest"]
C --> E["Investor Perceives Higher Risk <br/> => More Likely to Avoid Investment"]
Observe that from node A (the same raw data), we branch to either a positive or negative framing, leading to distinct psychological perceptions of risk and, potentially, distinct action.
Within the broader context of behavioral finance, especially for those pursuing the CFA designation, understanding framing effects is critical in both theoretical exam questions and real-case, scenario-based item sets. You may be asked to:
• Recognize the presence of framing in a provided investment recommendation and identify how it might mislead the client.
• Suggest strategies for ensuring balanced communication in an Investment Policy Statement (IPS).
• Calculate or discuss how different frames can alter the perceived risk of identical investments.
• Evaluate how to mitigate biases using scenario analyses and standardized jargon.
Remember that the CFA exam often tests your ability to detect subtle biases in practice, so pay attention to how numerical data is phrased or anchored.
• Framing Effect: A cognitive bias where people make different decisions depending on how the same information is presented.
• Prospect Theory: A behavioral model that describes how individuals evaluate potential losses and gains and make decisions under conditions of risk and uncertainty.
• Positive Frame: Presenting information in a way that emphasizes potential gains or benefits.
• Negative Frame: Presenting information in a way that highlights potential losses or risks.
Framing is one of those deceptively simple concepts that has far-reaching implications in finance. Sure, we might think we’re fully aware of “80% vs. 20%,” but in practice, that shift in endpoints can meaningfully affect whether someone invests in a hedge fund, holds onto a stock during a downturn, or locks in an annuity for retirement. By recognizing framing cues, using scenario and break-even analyses, and demanding balanced presentations, investors and managers can make more informed, less biased decisions.
At the end of the day, the “same data” can lead to very different actions—so keep an eye on how it’s packaged. With an awareness of framing, plus the standard rock-solid analytics of risk and return taught throughout the CFA curriculum, you’re better positioned to avoid snap judgments and steer portfolios toward rational, well-grounded choices.
Important Notice: FinancialAnalystGuide.com provides supplemental CFA study materials, including mock exams, sample exam questions, and other practice resources to aid your exam preparation. These resources are not affiliated with or endorsed by the CFA Institute. CFA® and Chartered Financial Analyst® are registered trademarks owned exclusively by CFA Institute. Our content is independent, and we do not guarantee exam success. CFA Institute does not endorse, promote, or warrant the accuracy or quality of our products.