Summary of Key Points
This article discusses how technology is altering the sources of information advantage in financial markets, indicating that traditional advantages (based on insider knowledge) are being replaced by two new forms: the ability to deeply analyze public information and "alternative data" generated outside of companies. These new forms of information asymmetry are not covered by existing regulatory rules, such as the U.S.'s Fair Disclosure Act (Reg FD), posing fundamental challenges to the current financial regulatory framework. The competition for information advantage has shifted from a focus on speed and data to one on intelligence, leading to the conclusion that only through collaboration between humans and machines can one prevail in the future battle for information.
Detailed Analysis
#### 1. The Change in Information Advantage: From "Knowing Secrets" to "Mastering Public Information"
In the past, information advantage in financial markets was associated with having access to insider knowledge that others did not—such as Gekko in the movie "Wall Street," who made money by using information leaked from within companies. However, this is no longer the case:
- Example 1: Simones from Renaissance Technologies, a mathematician by training, does not need to know any company CEOs; by analyzing vast amounts of public data (such as stock price trends and trading volumes) using mathematical models, he can consistently generate excess returns.
- Example 2: In the paper's CEO example, when an aggressive shareholder quietly buys company stocks, the CEO receives no insider information, but he is very familiar with the company's fundamentals. He notices abnormalities in public transaction data (such as a sudden surge in buying) and realizes that this might indicate external investors are building positions. He then buys shares as a defense measure.
This new form of advantage lies in the ability to interpret public information more effectively, which is not within the scope of traditional legal regulations because the data used is publicly available.
#### 2. "Alternative Data" Outside Company Walls: New Information Sources Beyond Regulatory Reach
Many critical pieces of information are no longer generated by companies themselves but come from external sources:
- What is alternative data? This includes satellite images of mall parking lot traffic (used to assess sales performance), data from IoT devices measuring factory smoke emissions (indicating production levels), and user comments on social media (used to analyze brand popularity). These data are not held by companies and are not part of their disclosures.
- Regulatory Gaps: Traditional regulations like Reg FD require companies to disclose internal information, but these external data are not within their disclosure obligations. For example, satellite data is collected by third parties, and Reg FD does not regulate who can access it or how it can be used. This breaks the one-way information chain of "company → disclosure → market," allowing institutions with alternative data to gain insights into companies before they are made public.
#### 3. Three Stages of the Information Advantage Competition: From Speed to Intelligence
The competition for information advantage has gone through three stages:
- Stage 1: The Speed Race: Institutions invested heavily in shorter fiber optic cables and placed servers near exchanges (known as "hosting") to gain a few milliseconds' advantage in accessing information.
- Stage 2: The Data Race: Once speed became less of an issue, those with access to unique alternative data (such as satellite images) had the upper hand. For example, using satellite data to predict retail foot traffic months before financial reports were released.
- Stage 3: The Intelligence Race: AI can now analyze large amounts of public information (such as financial reports and news), and AI analysts often outperform human analysts in predicting stock returns. However, humans are better at handling "soft information" (such as the integrity of company management and subtle industry trends). Companies even adjust their financial reporting language to make it easier for AI to understand—this shows how technology can influence corporate disclosure strategies.
#### 4. Regulatory Blind Spots: Unable to Cope with New Information Asymmetries
Traditional regulation focuses on prohibiting trading based on unpublicized information, but the new sources of information advantage do not depend on whether the information is public or not, but on the ability to interpret it and the use of external data:
- Gaps in Interpretation: For example, if a CEO makes a correct judgment using public data, laws cannot accuse him of violating regulations because the information is publicly available.
- Alternative Data: Since these data are not part of company disclosures, regulators cannot require companies to control them.
The current regulatory framework is inadequate for addressing these changes, and there is a need to rethink how to address the unfairness caused by differences in interpretation capabilities or how to manage the use of alternative data.
#### 5. Future Trends: Collaboration Between Humans and Machines
Research suggests that:
- AI excels at processing large amounts of structured data (such as financial figures), while humans are better at understanding soft information (such as company culture and industry dynamics).
- The highest prediction accuracy is achieved when human analysts use AI tools to analyze data and then apply their own judgment.
- Companies are also adapting to the presence of AI by adjusting their disclosures to make them more understandable to AI.
In conclusion, humans cannot defeat machines alone, but a combination of human and machine capabilities can outperform any single entity.
The core message of this article is that technology has changed the rules of the financial market, and regulation must evolve accordingly. Individuals and institutions seeking success in the market must learn to collaborate with AI.