"A rotated dynamic factor model for the yield curve: squeezing out information when it matters" by Chiara Casoli

Topic

It has long been argued that the yield curve is a powerful descriptor of the economy and the expectation of the markets. Although not universal, a very common approach to give a statistical description on the yield curve relies on the idea that a small number of factors can describe adequately the whole curve. Under this assumption, it may be thought that if one could observe the factors, then these can be used to forecast real activity. In this paper, we argue that optimal extraction of the factor is key for squeezing out information from the yields when considering an approximate factor model. In fact, with a rotation of the factor model including cointegration, we reduce the cross-sectional correlation of the idiosyncratic components. We show that this advantage produces better forecasts of relevant macroeconomic variables in periods of economic instability and financial turmoil.