When it comes to investing, many people believe it’s a game of “human intelligence” versus “market luck”. However, what if there was a way to interpret investor sentiment and predict market trends? Would you be willing to use it as your weapon? That’s where the powerful force of AI comes in! Instead of being trapped by the ups and downs of the market, it’s better to use artificial intelligence (AI) to outperform the market, turning investment decisions into a game of “human versus AI”. Research has shown that investor sentiment can help predict market and stock returns. With the continuous innovation of machine learning methods, researchers can not only analyze text content in media such as news and social media, but also use various image analysis methods in the computer vision field to make visual content a research subject and further explore the rules of investor sentiment and market changes.
Can Image Analysis Help Beat the Market?
A stock trading company can use artificial intelligence to analyze investor sentiment for accurate market predictions. They can use data from news reports, blogs, and social media to understand investor sentiment for specific stocks or markets. By using an AI system, they can quickly analyze and evaluate data to provide more accurate market predictions. They can use this technology to make wiser investment decisions to beat the market.
Scholars in the United States (Obaid & Pukthuanthong, 2022) studied economic-related news texts and images from The Wall Street Journal from September 2008 to September 2020. They classified the news images as “positive” or “negative” using a model, and constructed an investor sentiment index based on the proportion of negative images to all images each day. They built three real trading strategies using the news image sentiment index (PhotoPes), news text sentiment index (TextPes), and a combination of both (Combined Strategy). The investment return chart shows that the cumulative return of the PhotoPes Strategy was the highest during the sample period. Its cumulative return could reach 5 times the initial investment, while an S&P 500 index fund (SPY) during the same period could only achieve a return of 3 times the initial investment.
[SPY is an exchange-traded fund that tracks the S&P 500 Index, i.e. SPDR S&P 500 ETF.]
How Does Artificial Intelligence (AI) Judge Investment Sentiment from Images?
Machine learning in image processing is a method of inferring emotions by analyzing image data. In investor analysis, it can detect investor sentiment by using facial recognition technology to detect expressions, as well as by tracking eye and head movement to infer attention and interest. Additionally, analyzing investor body language and speech can also infer their emotions. The inferred emotional information can be used to provide information about whether investors are satisfied or dissatisfied with a particular investment, as well as their outlook for the future of the investment. This information can help investors better understand investor needs and preferences, and make more informed investment decisions.
Color analysis in image processing is a method of inferring emotions. By analyzing the proportion of colors used in an image, investor sentiment can be inferred. For example, using warm colors (such as orange and yellow) is often associated with pleasant and positive emotions, while using cool colors (such as blue and green) is often associated with calm and stable emotions.
Composition analysis refers to the analysis of the position and relationship of elements in an image. By analyzing the position and relationship of elements in an image, investor sentiment can be inferred. For example, placing an element in the center of an image may indicate strong attention to that element, while placing an element in the corner of an image may indicate weaker attention to it.
Texture, clarity, and other visual features of images can be analyzed to infer investor sentiment. For example, using sharp and clear images may indicate that investors are positive and attentive to certain things, while using blurry and unclear images may indicate that investors are not interested and dissatisfied. AI systems can learn how to recognize and classify emotional images, and provide more accurate emotional analysis and more accurate prediction of market trends, thereby increasing the accuracy of investment strategies.
How can AI image analysis be used to promote business?
The application of image machine learning for analyzing emotions is very extensive and can be used for market sentiment analysis, social media analysis, news sentiment analysis, and advertising sentiment analysis. These analyses can help to better understand customer needs and preferences, quickly identify potential customers, and provide more accurate information about potential customers. In terms of customer service and sales, image analysis technology can promote business development in the following ways:
Improving customer experience: Through image analysis, companies can understand customer needs and preferences, thereby improving customer experience and satisfaction.
Efficient advertising placement: Image analysis technology can help companies determine which ads are most effective in specific target markets, thereby improving advertising placement efficiency.
Marketing strategy development: Image analysis technology can collect information about customer preferences and behavior, thereby helping companies develop more flexible and effective marketing strategies.
Product quality control: Image analysis technology can assist companies in reviewing product quality to ensure that the quality meets standards.
In conclusion, interpreting investor sentiment using AI to outperform the market is a new investment method. It uses a large amount of data and algorithms to analyze investor sentiment and market trends, helping investors make more informed investment decisions. By combining the advantages of human intelligence and AI, it can not only reduce risks but also increase investment returns. In addition to investment, image analysis technology can support business development by providing emotional information and insights through AI, enabling more accurate product marketing and enhancing customer experience, helping companies maintain a leading position in a fiercely competitive market.
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This article was written with the assistance of AI and referred to the following sources:
Obaid, K., & Pukthuanthong, K. (2022). A picture is worth a thousand words: Measuring investor sentiment by combining machine learning and photos from news. Journal of Financial Economics, 273-297.