宏观流动性失衡逆转新探——基于马尔可夫机制转换模型

A Study of Macro Liquidity Imbalance Reversal——Based on Markov Mechanisms Conversion Model

由于我国宏观流动性过剩或者短缺的状态并不是相互独立的,而是与前一期或者前几期的状态具有相关性,因此构建马尔可夫机制转换模型可对我国流动性的变化做出进一步的分析解释。从模型拟合结果来看,我国宏观流动性表现为以下特点:流动性序列"过剩"与"短缺"相互转换;机制取值平滑概率趋于"不足"时期伴随着序列较大的波动;流动性的不同状态所持续的时间存在非对称性。文章旨在为宏观流动性的逆转提供决策依据,使宏观流动性预测更具科学性。

China＇s macro liquidity excess or shortage state are not independent of each other, but related to one or more periods of previous state. Therefore,we can construct Markov Mechanisms Conversion model to make further analysis and interpretation. From the results of model fitting, China＇s macro liquidity shows the following characteristics：the mutual conversion between ＂sur- plus＂ and ＂shortage＂ of fluidity mechanism values to ＂inadequate the asymmetry of the duration of basis for macro liquidity reversal sequence conversion~ the tendency of smoothed probability of ＂ period along with the larger fluctuations of the sequence and the different states. This paper aims to provide decision-making to make the prediction of macro liquidity more scientific.