forecasting

I use QLIKE as loss function to evaluate the forecasting performance of a RV realized volatility model. QLIKE = log $h$ + $\frac{\hat{\sigma}^2}{h}$ where $h$ is volatility forecast and $\hat{\sigma}^2$ is the ex post value of volatility (realized volatility computed with intraday returns). If I proxy volatility with log(RV), what are $h$ and $\hat{\sigma}^2$ in the QLIKE? The forecast and ex pos…

Methods capable of forecasting the entire yield curve based on a time series extension of the Nelson-Siegel model Nelson and Siegel (1987) were suggested in the literature and compared to the non-parametric alternatives Diebold and [...]

Today I was reading a recent discussion paper by Neil Ericcson , titled " Economic Forecasting in Theory and Practice: An Interview With David F. Hendry ". The interview is to be published in the International Journal of Forecasting . Here's the abstract: " David Hendry has made major contributions to many areas of economic forecasting. He has developed a taxonomy of forecast errors and a theory …

Here’s the start of the paper I’ve just written on forecasting the UK General Election (rather easy for a quant, much easier than valuing a CDO!), and lectured on for the CQF yesterday. The lecture [...]

Most economic data are released with a lag, sometimes quite a substantial one. Since the advent of regularly scheduled releases of economic data in the 1930s, a key challenge for economists has been to identify indicators that provide timely information about the release before it comes out—effectively, that “now-cast” its content.