Emergence of correlations between securities at short time scales
arXiv:1807.05015 · doi:10.1016/j.physa.2019.04.262
Abstract
The correlation matrix is the key element in optimal portfolio allocation and risk management. In particular, the eigenvectors of the correlation matrix corresponding to large eigenvalues can be used to identify the market mode, sectors and style factors. We investigate how these eigenvalues depend on the time scale of securities returns in the U.S. market. For this purpose, one-minute returns of the largest 533 U.S. stocks are aggregated at different time scales and used to estimate the correlation matrix and its spectral properties. We propose a simple lead-lag factor model to capture and reproduce the observed time-scale dependence of eigenvalues. We reveal the emergence of several dominant eigenvalues as the time scale increases. This important finding evidences that the underlying economic and financial mechanisms determining the correlation structure of securities depend as well on time scales.
References in corpus (16)
- Noise Dressing of Financial Correlation Matrices
- A Random Matrix Approach to Cross-Correlations in Financial Data
- Signal and Noise in Correlation Matrix
- Financial Applications of Random Matrix Theory: Old Laces and New Pieces
- A New Method to Estimate the Noise in Financial Correlation Matrices
- Increasing market efficiency: Evolution of cross-correlations of stock returns
- Market dynamics immediately before and after financial shocks: quantifying the Omori, productivity and Bath laws
- Cross-Correlation Dynamics in Financial Time Series
- Evolution of correlation structure of industrial indices of US equity markets
- Dissecting cross-impact on stock markets: An empirical analysis
- Random Matrix Theory and Fund of Funds Portfolio Optimisation
- Exponential Weighting and Random-Matrix-Theory-Based Filtering of Financial Covariance Matrices for Portfolio Optimization
- Individual and collective stock dynamics: intra-day seasonalities
- Quantitative law describing market dynamics before and after interest-rate change
- Eigenvector dynamics: general theory and some applications
- Time scales involved in market emergence