Principal Component Analysis in Negative Interest Rate Environment

Principal Component Analysis (PCA) is a risk management technique which is, due to the consequences of multicollinearity, particularly suitable to describe the yield curve. Its final results in this segment are presented through three main factors: shift, slope and curvature. They express predictive trajectories and explain over 95% of variability under normal market conditions. The main goal of this paper is to assess whether the established behavioural patterns are observable in the presence of negative interest rates. The EU bond market was used as an empirical basis with respect to the reactions of the European Central Bank and the establishment of negative reference interest rates in the assessed period. The algebraic properties of the principal components in the presence of negative interest rates correspond to the determined directions of movement, except that the slope and curvature have different signs given their diametrically opposite trends. The percentage of variability explained with the help of PCA is lower compared to the normal market conditions and if an equivalent level of approximation is required, it is necessary to include a fourth factor in PCA. This factor is, due to its properties, aptly named oscillatority. An implicit conclusion of our research is that the duration in the conditions of negative interest rates has less useful power in managing the interest rate risk of individual instruments.