从哈雷到AI：当量化成为信仰，我们离真相更近了吗？

Core Viewpoint - The article discusses the historical significance of Caspar Neumann's population records and how they laid the foundation for modern financial mathematics, particularly in the context of life annuities and risk assessment [4][10][13]. Group 1: Historical Context - In the late 17th century, Caspar Neumann, a pastor in Breslau, meticulously recorded births and deaths, creating one of the earliest continuous population databases in Europe [4][5]. - Neumann's records were later recognized for their potential value by mathematician Gottfried Wilhelm Leibniz, who encouraged him to share the data with the Royal Society in London [4][5]. Group 2: Key Discoveries - Edmund Halley, upon reviewing Neumann's records, discovered patterns in mortality rates, allowing for the first statistical analysis of life expectancy and the calculation of fair prices for life annuities [8][10]. - Halley's work demonstrated that mortality could be quantified, leading to the establishment of a mortality table that provided insights into life expectancy at various ages [9][10]. Group 3: Impact on Financial Mathematics - Halley's integration of probability and compound interest marked a significant advancement in financial mathematics, enabling the calculation of fair values for annuities based on statistical data [10][11]. - This approach shifted the pricing of annuities from subjective estimates to a more rational, mathematical basis, influencing the development of modern insurance and financial systems [10][13]. Group 4: Evolution of Financial Models - The principles established by Halley laid the groundwork for future financial innovations, where mathematical models began to dominate risk assessment and pricing strategies across various sectors [13]. - However, the reliance on complex models has also led to vulnerabilities, as seen in the 2008 financial crisis, highlighting the need for a balanced approach to risk management [13][14]. Group 5: Contemporary Reflections - The article draws parallels between historical reliance on mathematical models and today's dependence on artificial intelligence and data analytics in finance, cautioning against blind faith in technology [14]. - It emphasizes the importance of maintaining human judgment in decision-making processes, ensuring that technology serves as a tool rather than a replacement for critical thinking [14].