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 industry carry high risks; however, an analysis of systematic risk and return compared other asset classes missing. This paper investigates time–frequency interconnectedness between stocks biotech ten using daily cross-country data from 1995 2019. We capture investors' heterogeneous investment horizons by decomposing time series according frequencies. Using a maximal overlap discrete wavelet transform (MODWT) dynamic conditional correlation (DCC)-Student-t copula, diversification potentials are revealed, helping investors reap benefits investing biotech. Our findings indicate underlying assets exhibit nonlinear asymmetric behavior strengthens during periods turmoil.