Computational and financial econometrics comprise a broad field that has clearly interested a wide variety of researchers in economics, finance, statistics, mathematics and computing. Examples include estimation and inference on econometric models, model selection, panel data, measurement error, Bayesian methods, time series analyses, portfolio allocation, option pricing, quantitative risk management, systemic risk and market microstructure, to name but a few. While such studies are often theoretical, they can also have a strong empirical element measuring risk and return and often have a significant computational aspect dealing with issues like high-dimensionality and large numbers of observations. Algorithmic developments are also of interest since existing algorithms often do not utilize the best computational techniques for efficiency, stability, or conditioning. So also are developments of environments for conducting econometrics, which are inherently computer based. Integrated econometrics packages have grown well over the years, but still have much room for development.