We present an approach to forecast customer orders of ready-to-launch new products that are similar to past products. The approach fits product life cycle (PLC) curves to historical customer order data, clusters the curves of similar products, and uses the representative curve of the new...

This study employs big data and text data mining techniques to forecast financial market volatility. We incorporate financial information from online news sources into time series volatility models. We categorize a topic for each news article using time stamps and analyze the chronological...

Volatility forecasts play a central role among equity risk measures. Besides traditional statistical models, modern forecasting techniques, based on machine learning, can readily be employed when treating volatility as a univariate, daily time-series. However, econometric studies have shown that...

Out-of-sample tests are subject to look-ahead bias when a forecaster constructs a model using an intuition derived from empirical patterns in the test sample. Even if model parameters are estimated without the test sample, information from it affects a forecaster's model choice. Since such...

Game-theoretic models of learning are hard to study even in the laboratory setting due to econometric and practical concerns (like the limited length of an experimental session).In particular, as the simulations by (Salmon, 2001) show, in a cross-model (or "blind'') testing of several models,...

We propose an alternative Ratio Statistic for measuring predictability of stock prices. Our statistic is based on actual returns rather than logarithmic returns and is therefore better suited to capturing price predictability. It captures not only linear dependence in the same way as the...

We conduct a lottery experiment to assess the predictive importance of simple choice process metrics (SCPMs) in forecasting risky 50/50 gambling decisions using different types of machine learning algorithms as well as traditional choice modeling approaches. The SCPMs are recorded during a fixed...

The focus of this paper is on nowcasting and forecasting quarterly private consumption. The selection of real-time, monthly indicators focuses on standard (“hard”/“soft” indicators) and less-standard variables. Among the latter group we analyze: i) proxy indicators of economic and policy...