Technical paper/Principal component analysis (PCA)
Does investors’ sentiment influence stock market volatility? Evidence from India during pre- and post-Covid-19 periods
The authors use data from during the Covid-19 pandemic to investigate the impact of investor sentiment on equity market volatility, finding negative news to have a stronger impact that positive news of the same magnitude.
A FAVAR modeling approach to credit risk stress testing and its application to the Hong Kong banking industry
In this paper, a credit risk stress testing model based on the factor-augmented vector autoregressive (FAVAR) approach is proposed to project credit risk loss under stressed scenarios.
Eigenportfolios of US equities for the exponential correlation model
In this paper, the eigendecomposition of a Toeplitz matrix populated by an exponential function in order to model empirical correlations of US equity returns is investigated.
Curve dynamics with artificial neural networks
Artificial neural networks can replace PCA for yield curves analysis
Flylets and invariant risk metrics
Kharen Musaelian, Santhanam Nagarajan and Dario Villani show how to build robust risk metrics for bond returns
Stock selection with principal component analysis
The authors of this paper propose a stock selection method based on a variable selection method used with PCA in multivariate statistics.
Risk budgeting and diversification based on optimised uncorrelated factors
Meucci, Santangelo and Deguest introduce a risk decomposition method based on minimum-torsion bets