We introduce the formalism of generalized Fourier transforms in the context of risk management. We develop a general framework in which to efficiently compute the most popular risk measures, value-at-risk and expected shortfall (also known as conditional value-at-risk). The only ingredient...

As common practice, oil studies in the economic literature are carried out by taking the correct specification of a model as given, and ignoring the problem of estimating overly optimistic confidence sets. This means that model uncertainty is pervasive in the empirical results. In this work I...

Risk management technology applied to high dimensional portfolios needs simple and fast methods for calculation of Value-at-Risk (VaR). The multivariate normal framework provides a simple off-the-shelf methodology but lacks the heavy tailed distributional properties that are observed in data. A...

We use a factor model with stochastic volatility to decompose the time-varying variance of Macro economic and Financial variables into contributions from country-specific uncertainty and uncertainty common to all countries. We find that the common component plays an important role in driving the...

A growing empirical literature has considered the impact of uncertainty using SVAR models that include proxies for uncertainty shocks as endogenous variables. In this paper we consider the possible impact of measurement error in the uncertainty shock proxies on the estimated impulse responses...

Changes in mortality rates have an impact on the life insurance industry, the financial sector (as a significant proportion of the financial markets is driven by pension funds), the governmental agencies, and the decision and policy makers. Thus, the pricing of financial, pension and insurance...

We propose a Markov Switching Graphical Seemingly Unrelated Regression (MS-GSUR) model to investigate time-varying systemic risk based on a range of multi-factor asset pricing models. Methodologically, we develop a Markov Chain Monte Carlo (MCMC) scheme in which latent states are identified on...

A common scenario risk analysis employs a multiple factor model with assumed changes in the factors to obtain changes in non-factor variables. This analysis is sometimes designated as a “predictive stress scenario”. We choose to designate the factor model as a multifactor “CAPM” model,...

Inter-temporal risk parity is a strategy that rebalances risky assets and cash in order to target a constant level of ex-ante risk over time. When applied to equities and compared to a buy-and-hold portfolio it is known to improve the Sharpe ratio and reduce drawdowns. We apply inter-temporal...

This paper provides new indices of global macroeconomic uncertainty and investigates the cross-country transmission of uncertainty using a global vector autoregressive (GVAR) model. The indices measure the dispersion of forecasts that results from parameter uncertainty in the GVAR. Relying on...