We present a new Monte-Carlo methodology to forecast the crude oil production of Norway and the U.K. based on a two-step process, (i) the nonlinear extrapolation of the current/past performances of individual oil fields and (ii) a stochastic model of the frequency of future oil field...

The Scaled Model of Error has gained considerable popularity during the past ten years as a device for computing probabilistic population forecasts of the cohort-component type. In this report we investigate how sensitive probabilistic population forecasts produced by means of the Scaled Model...

This paper builds two factor discrete time models in order to investigate the effect of sovereign risk on the nominal exchange rates in a Markov switching framework. The empirical section of the paper uses seven currencies from Chile, the Czech Republic, Hungary, Iceland, Japan, Korea, and...

While prior research has studied the motivations of individuals to consume content on social media platforms, limited work exists on how contributors are motivated to create content. We examine the role of peer influence in content production on YouTube, where content creators are competing for...

Forecasting the price in online auctions is important for buyers and sellers. With good forecasts, bidders can make informed bidding decisions and sellers can select the right time and place to list their products. While information from other auctions can help forecast an ongoing auction, it...

This paper sets forth a synergy of existing statistical theories to obtain a clear-cut model for calculating forecasts with prediction intervals, named the “WK1 model.”Many predictive models calculate a linear or non-linear trend from the historical data and generate a single, discrete...

We revisit the empirical performance of the Q theory of investment, explicitly taking into account the frequency dependence of investment, Tobin's Q, and cash flow. The time series are decomposed into orthogonal components of different frequencies using wavelet multiresolution analysis. We find...

We conduct a sentiment analysis of the FOMC (Federal Open Market Committee) minutes based on the text mining results and examine the predictive ability of the resulting sentiment indicators. An adaptive Bayesian approach is employed to build the sentiment indicator for each of the Fed's...