Forecasting research project ideas - The Business.
By RecessionALERT on October 14, 2019 in Research Papers Following on from extensive client feedback since the launch of the SP-500 trough probabilities and SP-500 Trendex trend-following model, we have decided to target the models at the six largest investable U.S Exchange Traded Fund (ETF) categories by assets under management (AUM) as depicted below, for a total of 50.1% coverage of the.
Usefully this year’s research shines a light on the characteristics of insightful organizations and reveals what technologies they deploy in support of this goal. CFOs clearly appreciate the importance of technology in driving better forecasting performance, for example, 80% agree that standardizing and automating the planning budgeting and forecasting process is the top technology priority.
Epidemiological forecasting is critically needed for decision making by public health officials, commercial and non-commercial institutions, and the general public. The Delphi group at Carnegie Mellon University focuses on developing the technological capability of epi-forecasting, and its role in decision making, both public and private. Our long term vision is to make epidemiological.
Crime forecasting is an emerging application area for forecast research. While there have been isolated papers in the literature, it is only recently that there has been major interest and thus research programs in the area. This interest has been fueled by the availability of electronic police records for analysis, availability of geographic information systems ( (GIS) software and street.
Category: Journal papers Tags: Croston's method, exponential smoothing, intermittent demand Tactical sales forecasting using a very large set of macroeconomic indicators Y.R. Sagaert, E-H. Aghezzaf, N. Kourentzes and B. Desmet, 2018.
This article also launches the Annals of Tourism Research Curated Collection on tourism demand forecasting,. Some applications of the STSM in tourism demand modelling and forecasting can be found in the papers by Greenidge, 2001, Guizzardi and Stacchini, 2015, Ognjanov et al., 2018. Another stream of studies extends the static single equation model by capturing the interdependency of.
Forecasting US GDP over 1-, 4- and 8-step horizons using the dataset from Stock and Watson (2009) updated to 2011:2 shows factor models are more useful for nowcasting or short-term forecasting, but their relative performance declines as the forecast horizon increases. Forecasts for GDP levels highlight the need for robust strategies such as intercept corrections or differencing when location.