We consider dynamic sublinear expectations (i.e., time-consistent coherent risk measures) whose scenario sets consist of singular measures corresponding to a general form of volatility uncertainty. We derive a càdlàg nonlinear martingale which is also the value process of a superhedging...

March 2020 packed 2 ½ years of normal U.S. stock market volatility into one month, making it the most volatile month on record. Daily variability clocked in at 6%, six times higher than the average over the past 90 years. How should an investor respond to such volatility? In this article we...

In assessing drivers of commodity prices and volatility at this stage of the current super-cycle in commodities (year 12 of a projected 25), it is vital to understand that production cost is a fundamental. Moreover, marginal production costs are among the most powerful drivers of commodity...

This paper treats the risk-averse optimal portfolio problem with consumption in continuous time for a stochastic-jump-volatility, jump-diffusion (SJVJD) model of the underlying risky asset and the volatility. The new developments are the use of the SJVJD model with...

This study introduces a novel index based on expectations concordance for explaining stock-price volatility when novel events that are each somewhat unique cause unforeseeable change and Knightian uncertainty in the process driving outcomes. Expectations concordance measures the degree to which...

In this paper we examine the optimal level of central bank activism in a standard model of monetary policy with uncertainty, learning and strategic interactions. We calibrate the model using G7 data and find that the presence of strategic interactions between the central bank and private agents...

This study introduces a novel index based on expectations concordance for explaining stock-price volatility when historically unique events cause unforeseeable change and Knightian uncertainty in the process driving outcomes. Expectations concordance measures the degree to which non-repetitive...

How do financial markets switch from states of optimism to pessimism and vice versa? Given that a financial market is currently stable, what is the probability that it will become unstable and crash? We answer those questions in the context of a natural experiment with risk sources of...

We contrast two different asset pricing models, where the pricing kernel either (i) increases in the volatility dimension, reflecting investors' aversion to volatility, or (ii) could be non-monotonic in volatility, reflecting heterogeneity in investors' beliefs. The two models yield opposite...

We propose a model of volatility tail behavior, in which the pricing measure dominates the physical measure in both tails of the volatility distribution and, hence, the derived pricing kernel exhibits an increasing and decreasing region in the volatility dimension. The model features investors...