Following the recent crisis and the revealed weakness of risk management practices, regulators of developed markets have recommended that financial institutions assess model risk. Standard risk measures, such as the Value-at-Risk (VaR), emerged over recent decades as the industry standard for risk management and have today become a key tool for asset allocation. We illustrate and estimate model risk, and focus on the evaluation of its impact on optimal portfolios at various time horizons. Based on a long sample of U.S. data, we find a non-linear relation between VaR model errors and the horizon that impacts optimal asset allocations.
