Research Economic Seminar: The good, the bad, and the asymmetric: Evidence from a new conditional density model

We propose a conditional density model where returns are decomposed into a sum of copula-connected positive and negative shocks, both continuous and discrete. We compare 52 variants of our model with different marginal distributions and copulæ to 40 well-established GARCH variants. Our models with dynamic scale parameters and without jumps perform better both in sample and out of sample. We show that the independence assumption for signed shocks does not hold: covariance is an important component of total variance, and it is time-dependent with a leverage-like effect. Conditional skewness behaviour reveals naïve investors’ expectations. The U.S. market on average has a propensity for bull trends. The relation between returns and volatility is either very non-linear or insignificant. Results for models with jumps show that introduction of discrete jumps does not improve the model performance; however, negative jumps have greater sizes, and occur more frequently.