标题： 增强应对社会经济挑战的系统韧性：使用纳维-斯托克斯方程对流动性流动和系统性风险的动力学进行建模 显示英文标题

标题： Increasing Systemic Resilience to Socioeconomic Challenges: Modeling the Dynamics of Liquidity Flows and Systemic Risks Using Navier-Stokes Equations

摘要： 现代经济系统面临前所未有的社会经济挑战，使得系统韧性与有效的流动性流动管理变得至关重要。 传统的模型如CAPM、VaR和GARCH往往无法反映真实的市场波动和极端事件。 本研究开发并验证了一种基于纳维-斯托克斯方程的创新数学模型，旨在对流动性流动和系统性风险进行定量评估、预测和模拟。 该模型包含13个宏观经济和金融参数，包括流动性速度、市场压力、内部应力、随机波动和风险溢价，所有参数均基于真实数据，并正式纳入修改后的方程中。 该方法采用计量经济学测试、傅里叶分析、随机模拟和基于人工智能的校准，以实现动态测试和预测。 基于仿真的敏感性分析评估了参数变化对金融平衡的影响。 该模型使用格鲁吉亚2010-2024年的宏观经济和金融数据进行了实证测试，包括国内生产总值、通货膨胀率、基尼系数、信用违约互换利差和流动性覆盖率指标。 结果表明，该模型能够有效描述流动性动态、系统性风险和极端情景，同时为多因素分析、危机预测和逆周期政策规划提供了一个稳健的框架。 显示英文摘要

摘要： Modern economic systems face unprecedented socioeconomic challenges, making systemic resilience and effective liquidity flow management essential. Traditional models such as CAPM, VaR, and GARCH often fail to reflect real market fluctuations and extreme events. This study develops and validates an innovative mathematical model based on the Navier-Stokes equations, aimed at the quantitative assessment, forecasting, and simulation of liquidity flows and systemic risks. The model incorporates 13 macroeconomic and financial parameters, including liquidity velocity, market pressure, internal stress, stochastic fluctuations, and risk premiums, all based on real data and formally included in the modified equation. The methodology employs econometric testing, Fourier analysis, stochastic simulation, and AI-based calibration to enable dynamic testing and forecasting. Simulation-based sensitivity analysis evaluates the impact of parameter changes on financial balance. The model is empirically tested using Georgian macroeconomic and financial data from 2010-2024, including GDP, inflation, the Gini index, CDS spreads, and LCR metrics. Results show that the model effectively describes liquidity dynamics, systemic risk, and extreme scenarios, while also offering a robust framework for multifactorial analysis, crisis prediction, and countercyclical policy planning.