An automated financial indices-processing scheme for classifying market liquidity regimes. Issue 3 (4th March 2021)

• Record Type: Journal Article
• Authors: Gu, Xing; Mamon, Rogemar; Davison, Matt; Yu, Hao
• Is Part Of: International journal of control. Volume 94:Issue 3(2021)
• Page Start: 735
• Page End: 756
• Publication Date: 2021-03-04
• Subjects: Multivariate HMM filtering -- optimal parameter estimation -- S&P 500 -- TED -- VIX -- DXY; Automatic control -- Periodicals; Electronic journals; 629.8
• DOI: 10.1080/00207179.2019.1616225
• Languages: English
• ISSNs: 0020-7179

Abstract

Abstract : A multivariate hidden Markov model (HMM)-based approach is developed to capture simultaneously the regime-switching dynamics of four financial market indicators: Treasury-Euro Dollar rate spread, US dollar index, volatility index and S&P 500 bid-ask spread. These indicators exhibit stochasticity, mean reversion, spikes and state memory, and they are deemed to drive the main characteristics of liquidity risk and regarded to mirror financial markets' liquidity levels. In this paper, an online system is proposed in which observed indicators are processed and the results are then interfaced with an advanced alert mechanism that gives out appropriate measures. In particular, two stochastic models, with HMM-modulated parameters switching between liquidity regimes, are integrated to capture the evolutions of the four time series or their transformations. Parameter estimation is accomplished by deriving adaptive multivariate filters. Indicators' joint empirical characteristics are captured well and useful early warnings are obtained for occurrence prediction of illiquidity episodes.