Systematic risk in the biopharmaceutical sector: a multiscale approach

Abstract

It is well documented that the biopharmaceutical sector has exhibited weak financial returns,contributing to underinvestment. Innovations in the industry carry high risks; however, ananalysis of systematic risk and return compared to other asset classes is missing. This paperinvestigates the time–frequency interconnectedness between stocks in the biotech sector andten asset classes using daily cross-country data from 1995 to 2019. We capture investors’heterogeneous investment horizons by decomposing time series according to frequencies.Using a maximal overlap discrete wavelet transform (MODWT) and a dynamic conditionalcorrelation (DCC)-Student-t copula, diversification potentials are revealed, helping investorsto reap the benefits of investing in biotech. Our findings indicate that the underlying assetsexhibit nonlinear asymmetric be.havior that strengthens during periods of turmoil