We study nonparametric regression in a setting where N(N-1) dyadic outcomes are observed for N randomly sampled units. Outcomes across dyads sharing a unit in common may be dependent (i.e., our dataset exhibits dyadic dependence). We present two sets of results. First, we calculate lower bounds...

We construct and estimate a dynamic stochastic general equilibrium model that features demand- and supply-side uncertainty. Using term structure and macroeconomic data, we find sizable effects of uncertainty on risk premia and business cycle fluctuations. Both demand-side and supply-side...

Uncertainty appears to jump up after major shocks like the Cuban Missile crisis, the assassination of JFK, the OPEC I oil-price shock and the 9/11 terrorist attack. This paper offers a structural framework to analyze the impact of these uncertainty shocks. I build a model with a time varying...

We study short-term market risks implied by weekly S&P 500 index options. The introduction of weekly options has dramatically shifted the maturity profile of traded options over the last five years, with a substantial proportion now having expiry within one week. Economically, this reflects a...

We propose several econometric measures of systemic risk to capture the interconnectedness among the monthly returns of hedge funds, banks, brokers, and insurance companies based on principal components analysis and Granger-causality tests. We find that all four sectors have become highly...

The aim of this study was to investigate the Granger causality between geopolitical risk (GPR) sub-indices in order to examine the implications of geopolitical risk on ten agricultural commodities classified as softs or grains. The Granger causality test was used to determine the causal...

The aim of this study was to determine whether referendums affect stock price risks and returns, using an event study approach. Daily end period data for the Swiss stock market index, the STOXX European market index, and the Swiss/US exchange rate running from the beginning of 2004 to June 2021,...

This paper presents a comprehensive extension of pricing two-dimensional derivatives depending on two barrier constraints. We assume randomness on the covariance matrix as a way of generalizing. We analyse common barrier derivatives, enabling us to study parameter uncertainty and the risk...

We consider a one-period portfolio optimization problem under model uncertainty. For this purpose, we introduce a measure of model risk. We derive analytical results for this measure of model risk in the mean-variance problem assuming we have observations drawn from a normal variance mixture...