We study the development of a duopoly industry -evolution of firm capacities and competitive behavior- in a continuous-time real-options model of capacity investment. Our methodology allows the evaluation of investment options and exercise rules in a strategic setup. In the initial industry...

We explore mixed data sampling (henceforth MIDAS) regression models. The regressions involve time series data sampled at different frequencies. Volatility and related processes are our prime focus, though the regression method has wider applications in macroeconomics and finance, among other...

We introduce a new measure called Inflation-at-Risk (I@R) associated with (left and right) inflation tail risk. We estimate I@R using survey-based density forecasts. We show that it contains information not covered by usual inflation risk indicators which focus on inflation uncertainty and do...

We consider estimating volatility risk factors using large panels of filtered or realized volatilities. The data structure involves three types of asymptotic expansions. There is the cross-section of volatility estimates at each point in time, namely i = 1,...; N observed at dates t = 1;....., T....

The U.S. equities market price process is largely driven by the information set and actions of large institutional investors, not individual retail investors. Using quarterly 13-F holdings, we construct the Herfindahl-Hirschman Index (HHI) of institutional investor concentration as a measure of...