The persistent nature of equity volatility is investigated by means of a multi-factor stochastic volatility model with time varying parameters. The parameters are estimated by means of a sequential matching procedure which adopts as auxiliary model a time-varying generalization of the HAR model...

This paper employs an applied econometric study concerning forecasting spot prices in bulk shipping in both markets of tankers and bulk carriers in a disaggregated level. This research is essential, as spot market is one of the most volatile markets and there is a great uncertainty about the...

We extend the work done in our “Redux” paper from Oct 2011 to find a weighted composite U.S coincident economic index (CEI) that includes non-zero weightings from all 50 states and when used in a standard Probit model, produces a perfect correlation (R2 of 1) to NBER recession dating. We...

Wilfried Despagne describes a Web-based forecasting support system, “Horizons,” that was designed for a French subsidiary of a European temperature-controlled-transport group. The major challenge was the adaptation of the system to more than 70 different transportation hubs, requiring a...

The world's data is growing more than 40% annually. Coupled with exponentially growing computing horsepower, this provides us with unprecedented basis for “learning” useful things from the data through statistical induction without material human intervention and acting on them. Philosophers...

This paper considers sampling proportional to expected size from a partly unknown distribution. The applied context is the exploration for undiscovered resources, like oil accumulations in different deposits, where the most promising deposits are likely to be drilled first, based on some...

This quick introductory note is intended to provide the background to the frequency alignment problem of analyzing disparate economic variables of interest, a solution, and its use in the nonparametric vector autoregression NNS.VAR()

You're probably familiar, at least in passing, with the 'convexity' of long-term bonds - i.e. that yields dropping 1% produce a bigger price move than yields rising 1%. A significant amount of brainpower has gone into understanding all the ramifications of this convexity in the fixed income...

The purpose of this paper is to investigate whether a dynamic Value at Risk model and high frequency realized volatility models can improve the accuracy of 1-day ahead VaR forecasting beyond the performance of frequently used models. As such, this paper constructs 60 conditional volatility...