between risk and uncertainty is implemented by applying the Gilboa-Schmeidler maxmin with multiple priors framework to lenders …, ultimate lenders and financial intermediaries. The model is used to investigate the impact of uncertainty about the likelihood … include: (i) An unanticipated increase in bailout uncertainty raises interest rates, the volume of defaults in both the real …

This paper considers the problem of model uncertainty in the case of multi-asset volatility models and discusses the … use of model averaging techniques as a way of dealing with the risk of inadvertently using false models in portfolio … management. Evaluation of volatility models is then considered and a simple Value-at-Risk (VaR) diagnostic test is proposed for …

framework, based on the explicit consideration of model uncertainty under rich parameterizations for the predictive models. We … propose a novel methodology to deal with model uncertainty based on ‘thick’ modelling, i.e. considering a multiplicity of …

their risk assessments and outcomes to those from a simple methodology that relies on publicly available market data and … market data; (iii) This discrepancy arises due to the reliance on regulatory risk weights in determining required levels of … capital once stress-test losses are taken into account. In particular, the continued reliance on regulatory risk weights in …

their risk assessments and outcomes to those from a simple methodology that relies on publicly available market data and …) This discrepancy arises due to the reliance on regulatory risk weights in determining required levels of capital once … stress-test losses are taken into account. In particular, the continued reliance on regulatory risk weights in stress tests …

. We compute the equilibrium in closed form when arbitrageurs' utility over consumption is logarithmic or risk-neutral with … expected returns are hump-shaped. Liquidity is a priced risk factor: assets that suffer the most when liquidity decreases, e …