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**Images Tell Stories**
Authors: Joshua Ronen, Tavy Ronen, Mi Zhou Original Source: Financial Analysts Journal, Vol.81 Issue2
**Introduction**
In ancient times, our earliest ancestors left hand-drawn traces on the dark cave walls, and these images were not only the beginning of art, but also a medium through which they tried to convey thoughts and experiences to future generations. With the development of civilization, painting and sculpture gradually became important means of expressing emotions and concepts. Artists used brushes and chisels to tell their inner feelings, sometimes whispering softly, sometimes shocking people. Art has never been just decoration, but a deep form of communication.
In today's society, the influence of images is no longer limited to galleries and museums. Corporate executives and decision-makers are also well aware of the power of visual language. They use charts, logos, advertisements, and even images in slides to convey strategic intentions, shape brand images, and influence public perception. Images, as a universal form of expression that transcends language barriers, have always been telling stories, influencing cognition, and connecting the past and future.
Professor Joshua Ronen of NYU Stern School of Business and others, in the process of reading a large number of annual reports of listed companies, deeply explored the importance of images in the investment decision-making process and their impact mechanisms. This article not only reveals how images influence investor behavior and decisions through emotional and cognitive channels, but also demonstrates the potential of generative AI in image generation and analysis, providing new perspectives for future research and practice.
The dual-channel theory proposed in the article - that images influence investment decisions through both emotional and cognitive aspects - is one of the core contributions of this paper. The emotional channel focuses on how image characteristics (such as color and asymmetry) trigger emotional responses from viewers, thereby affecting their investment behavior; while the cognitive channel focuses on how to supplement or strengthen textual information with image content, promoting more effective information processing and memory. This dual perspective helps us comprehensively understand the role of images in financial communication.
The authors introduce seven key visual characteristics: asymmetry, color richness, simplicity, quantity, self-similarity, clarity, and softness, and through empirical research prove the positive correlation between these characteristics and crowdfunding project funding amounts. This indicates that carefully designed images can not only attract attention but also inspire positive emotional responses, driving investor emotions and thereby improving project success rates.
While images inspire emotions, they may also lead people away from rationality.
When the bullet whistled past Trump's right ear, an Associated Press photographer captured the moment of him with blood on his right ear, raising his fist, with a determined gaze, surrounded by Secret Service agents, instantly igniting social media. Without complex policy explanations or fact-checking, this highly symbolic visual language constituted a set of highly inflammatory irrational narratives, with transmission efficiency and emotional mobilization capabilities far exceeding any carefully prepared campaign speech or policy platform, becoming "the most persuasive campaign material," fully demonstrating the powerful energy of image media.
Meanwhile, the rationalism of central banks is becoming a victim of this trend. The era when "the Federal Reserve Chairman only needs to shift his tone from positive to negative at a press conference to impact the S&P 500 index by as much as 200 points" has passed. Today's Powell can neither convince Trump nor his colleagues, nor can he convince bond investors. The rational logic of central bankers has been defined as "elite lies," and the influence of authoritative institutions' carefully constructed rational, complex, data-based narratives is inevitably weakening.
With the advent of the AI era, social media and algorithmic dissemination have further accelerated the reconstruction of communication power structures. Viral spread of fragmented, emotional, visual, and even fictional content will become mainstream.
Nobel Economics Prize winner Robert J. Shiller, in his book "Narrative Economics" published during the COVID-19 pandemic, provided profound theoretical explanations for this phenomenon. Shiller astutely pointed out that the deep forces driving major economic behaviors and violent market fluctuations (such as the expansion and bursting of asset bubbles, the spread of economic recession) are often not cold mathematical models or "rational person" calculations, but highly contagious "narratives."
**Abstract**
Images can enhance the interpretation of textual materials and improve decision quality. We summarize the latest research on how images influence decisions, which typically occurs through two channels: emotional and cognitive. Image characteristics that reflect visual expressiveness, such as color richness and clarity, primarily work at the emotional level; while image content that reinforces or supplements textual information to some extent works through cognitive channels. Research shows that specific image indicators can bring higher crowdfunding investment amounts, smaller analyst forecast errors and disagreements, and lower market risks. Finally, we explore the role of generative AI in image generation and analysis, using content from GE Aerospace's 10-K annual report as an example.
**Keywords:** Analyst forecast accuracy; Analyst forecast disagreement; Content reinforcement; Generative AI; Images; Machine learning; Visual characteristics; Visual expressiveness
**Dual Channels of Image Influence on Decisions**
What are the reasons and ways images influence investment decisions? Emotion (feelings or sensations) and cognition (thinking processes) constitute two channels through which images influence investment behavior and decisions.
First, let's analyze the emotional channel. Emotions are closely related to perception, and emotions subtly convey information about the expected consequences of actions. Emotions shape how people perceive the environment and how they act. Research results in psychology and neuroscience emphasize the role of emotions in decision-making processes. Perception closely related to emotions determines how specific images or parts of images attract attention.
Images also influence decisions by regulating cognition. The presence of images significantly affects cognitive structures such as memory, opinions, and intentions. For example, research shows that in news media, images have a much greater impact on opinions than text. Images are easier to remember because they are processed through different neural pathways. Images can also be better remembered because they have more distinct features than text.
**Image Effects Through Emotional Channels**
Ronen et al. (2023) proposed seven key image visual characteristics that influence investor behavior: asymmetry, color richness, simplicity, multiple elements, self-similarity, clarity, and softness. The authors integrated these characteristics into a single visual expressiveness indicator and found that this indicator positively correlates with crowdfunding amounts.
**Image Characteristics**
**Asymmetry:** This indicator refers to visual imbalance in image composition, structure, or element distribution. Specifically, this indicator quantifies the degree of uneven distribution of image content along the central axis.
**Color Richness:** Color richness is closely related to emotional behavior and cognitive perception. Research shows that higher color richness can enhance preferences and positive emotional effects in various scenarios.
**Simplicity:** Image simplicity is characterized by low information density, clear layout, and streamlined elements. Such images are more favored by investors because they can reduce cognitive load and quickly convey key information.
**Quantity:** Quantity refers to the number of elements presented in an image, affecting perception, cognition, and decision-making.
**Self-similarity:** If an image shows the same repeated visual patterns (or shapes) during scaling, it has self-similarity.
**Clarity:** Image clarity (without blur) enhances detail visibility and improves perceptual accuracy and cognitive processing capabilities.
**Softness:** Image softness affects emotional and cognitive decision-making processes through softened textures and diffused edges.
**Impact of Expressiveness on Crowdfunding**
Ronen et al. (2023) confirmed that visual characteristics positively correlate with crowdfunding amounts by studying the impact of these seven image characteristics on funds raised by crowdfunding projects. More importantly, "visual expressiveness" - as a comprehensive indicator constructed by aggregating seven characteristics - also positively correlates with funding amounts.
**Image Effects Through Cognitive Channels**
The information conveyed by images can reinforce content in accompanying textual materials (reinforcement), or introduce new information to supplement content delivered through textual form (supplementation).
In Ronen et al.'s (2023) research, we used Google Vision to obtain labels identifying objects or subjects depicted in images. Based on these labels and project descriptions, we constructed supplementation measures to capture the degree to which information contained in images supplements textual description information.
**Generative AI and Its Applications in Financial Analysis**
Revolutionary developments in image processing technologies, such as TensorFlow and Google Vision, now enable us to interpret information embedded in image data. These tools also make it possible to generate valuable insights by interpreting complex data and presenting data in visually impactful ways.
This evolution is crucial for decision-makers, such as financial analysts who must evaluate trends, predict outcomes, and provide strategic recommendations in increasingly large and complex databases. Moreover, analysts must effectively interpret and present this data to stakeholders with different levels of financial expertise.
**AI-Generated Images with Visual Reinforcement and Expressiveness**
A simple example using ChatGPT-4o (DALL-E) and text from the MD&A section of GE Aerospace's 2023 10-K report illustrates how AI tools can be used to create images with specific visual characteristics as described in expressiveness and reinforcement measures.
We asked ChatGPT to generate two images that both reinforce the following text from GE Aerospace's 2023 10-K report: "Our 2023 performance reflects strong demand for commercial aviation travel and continued strong performance of our services business, contributing to more than 70% of aerospace revenue this year."
The first image was constructed to reflect higher expressiveness values based on the seven visual characteristics previously introduced and described by Ronen et al. (2023); the second image was constructed to reflect lower expressiveness values.
**Discussion and Summary**
Ancient cave dwellers drew patterns on the walls of their dark dwellings; they were communicating information to us. Over time, painters and sculptors whispered or shouted their inner thoughts through their artistic paintings, drawings, and sculptures. Of course, da Vinci, Picasso, and other masters in art history believed they were communicating with us mortals through their masterpieces. What's strange about today's executives thinking they can communicate with us through various images?
This article explains and demonstrates how images convey information. Through machine learning techniques, we have proven that images can influence business stakeholder decisions by potentially strengthening textual information conveyed to decision-makers or adding to the information set available to document readers.
In the crowdfunding scenario, images help increase funding through dual emotional and cognitive channel effects by providing incremental information on content provided in textual materials. Additionally, we have shown that images in annual reports are associated with reductions in analyst forecast errors and their dispersion; images also have significant impacts on risk measures and other performance indicators.
There are many questions that need to be determined: What is the actual process of selecting images to include in annual reports and other relevant presentations? What are the ethical and practical implications of exposing market participants to AI-generated images?
Despite these unresolved questions, it can be reasonably argued that images can enhance financial analysts' ability to communicate effectively with their audiences. To help analysts better communicate with their stakeholders, further research on the role of images and their impact on investment management is urgently needed.
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