Sigmoidal dynamics of macro-financial leverage

IF 3.2 Q1 BUSINESS, FINANCE
A. D. Smirnov
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引用次数: 0

Abstract

Logistic sigmoids due to their flexibility seem to be natural candidates for modelling macrofinancial leverage behavior. The sigmoidal leverage transition towards its stationary value, which was driven by the yield spreads, could have replicated the dynamics of macrofinancial assets, debt and capital. The leverage transition, in its turn, has been a major factor in better balancing macrofinancial liabilities and assets. The sigmoidal leverage trajectories including their inflections and different phases were identified by a nonlinear transition function providing information necessary for steering the process towards its stable state. Solving the stationary Kolmogorov-Fokker-Plank logistic equation revealed that random leverage realizations might follow the gamma distribution. Parameters of its stationary probability density function, as well as the expected and the modal leverage, were dependent on the process variance and the yield spreads. Thus, the stochastic leverage behaviour reproduced a sequence of stylized phases similar to the observed in the US Treasuries market meltdown in 2020. In particular, larger yield spreads and smaller modal leverage signalled a "defensive" market response to sudden volatility increases. In addition, it was shown that the logistic leverage modelling could be helpful in the analysis of debt and money dynamics including some consequences of "minting a one trillion dollars coin".
宏观金融杠杆的s型动力学
Logistic s型曲线由于其灵活性似乎是建模宏观金融杠杆行为的自然候选人。在收益率息差的推动下,杠杆向平稳值的s型转变,可能复制了宏观金融资产、债务和资本的动态变化。反过来,杠杆化转型一直是更好地平衡宏观金融负债和资产的主要因素。利用非线性过渡函数识别了包括其拐点和不同相位在内的s型杠杆轨迹,提供了将过程转向稳定状态所需的信息。求解平稳Kolmogorov-Fokker-Plank logistic方程揭示了随机杠杆实现可能遵循伽玛分布。其平稳概率密度函数的参数,以及期望和模态杠杆,依赖于过程方差和收益率价差。因此,随机杠杆行为再现了一系列程式化阶段,类似于在2020年美国国债市场崩盘中观察到的情况。特别是,更大的收益率差和更小的模式杠杆表明,市场对波动性突然上升的“防御性”反应。此外,研究表明,逻辑杠杆模型可以帮助分析债务和货币动态,包括“铸造一万亿美元硬币”的一些后果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
0.30
自引率
1.90%
发文量
14
审稿时长
12 weeks
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