Market states: A new understanding
We present the clustering analysis of the financial markets of S&P 500 (USA) and Nikkei 225 (JPN) markets over a period of 2006-2019 as an example of a complex system. We investigate the statistical properties of correlation matrices constructed from the sliding epochs. The correlation matrices can be classified into different clusters, named as market states based on the similarity of correlation structures. We cluster the S&P 500 market into four and Nikkei 225 into six market states by optimizing the value of intracluster distances. The market shows transitions between these market states and the statistical properties of the transitions to critical market states can indicate likely precursors to the catastrophic events. We also analyze the same clustering technique on surrogate data constructed from average correlations of market states and the fluctuations arise due to the white noise of short time series. We use the correlated Wishart orthogonal ensemble for the construction of surrogate data whose average correlation equals the average of the real data.
Code (0)
등록된 구현이 없습니다.
Tasks
ClusteringTime SeriesTime Series AnalysisSimilar Papers 제목 키워드 기반
Fires and Local Labor Markets
We study the dynamic effects of fires on county labor markets in the US using a novel geophysical measure of fire exposure based on satellite imagery. We find increased fire exposure causes lower employment growth in the…
Fragmentation in trader preferences among multiple markets: Market coexistence versus single market dominance
Technological advancement has lead to an increase in number and type of trading venues and diversification of goods traded. These changes have re-emphasized the importance of understanding the effects of market competiti…
Linkages among the Foreign Exchange, Stock, and Bond Markets in Japan and the United States
While economic theory explains the linkages among the financial markets of different countries, empirical studies mainly verify the linkages through Granger causality, without considering latent variables or instantaneou…
Causal DiscoveryIdentifying Dominant Industrial Sectors in Market States of the S&P 500 Financial Data
Understanding and forecasting changing market conditions in complex economic systems like the financial market is of great importance to various stakeholders such as financial institutions and regulatory agencies. Based …
Dimensionality ReductionExplainable artificial intelligenceExplainable Artificial Intelligence (XAI)Dynamics of market states and risk assessment
Previous research explored various conditions of financial markets based on the similarity of correlation structures and classified as market states. We introduce modifications to previous selection criteria for these ma…
Clustering