We analyze a fixed panel of S\&P 500 stocks from 1996 to 2026 using complementary static and kinetic Ising models applied to daily binary open-to-close movements. The static pairwise model provides a long-run maximum-entropy summary of low-order dependence and reveals a sectorally organized interaction network with modest small-world structure and within-sector couplings about 2.8 times stronger than between-sector couplings, with especially coherent real estate and energy sectors. The kinetic model incorporates smooth time-varying external fields, self-memory, and directed lagged couplings to describe next-day dynamics. It reveals slow field-regime shifts around three major market-wide perturbations -- the dot-com bust, the global financial crisis, and the COVID-19 episode. Self-memory is generally weak, and the directed coupling structure is much less sector-concentrated and more asymmetric than the static network, while still reproducing the broad evolution of aggregate market movement. Taken together, the two complementary models characterize both persistent market organization and short-horizon cross-stock dynamics, providing a compact statistical physics view of interaction structure and time-varying behavior in the S\&P 500.

翻译：我们运用互补的静态和动力学伊辛模型，对1996年至2026年间S&P 500指数成分股固定面板的每日二元开盘-收盘涨跌进行分析。静态两两模型提供了低阶依赖性的长期最大熵总结，揭示了一个具有适度小世界结构的部门组织化相互作用网络，其中部门内部耦合强度约为部门间耦合的2.8倍，房地产和能源部门尤为紧密。动力学模型则引入平滑时变外场、自记忆及有向滞后耦合来描述次日动态。该模型识别出围绕三场重大市场扰动（互联网泡沫破裂、全球金融危机及新冠疫情事件）的缓慢外场制度转变。自记忆整体较弱，且与静态网络相比，有向耦合结构的部门集中度更低、不对称性更强，同时仍能再现整体市场运动的广义演化。总体而言，这两个互补模型共同刻画了市场中的持久组织结构和短时跨股票动态，为S&P 500中的相互作用结构及时变行为提供了紧凑的统计物理学视角。