When do jumps matter for portfolio optimization?

We consider the continuous-time portfolio optimization problem of an investor with constant relative risk aversion who maximizes expected utility of terminal wealth. The risky asset follows a jump-diffusion model with a diffusion state variable. We propose an approximation method that replaces the jumps by a diffusion and solve the resulting problem analytically. Furthermore, we provide explicit bounds on the true optimal strategy and the relative wealth equivalent loss that do not rely on results from the true model. We apply our method to a calibrated affine model and find that relative wealth equivalent losses are below 1.16% if the jump size is stochastic and below 1% if the jump size is constant and ... 5. We perform robustness checks for various levels of risk-aversion, expected jump size, and jump intensity.