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Using Financial and Macroeconomic Indicators to Forecast Sales of Large Development and Construction Firms

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  • Hong Chen

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  • Hong Chen, 2010. "Using Financial and Macroeconomic Indicators to Forecast Sales of Large Development and Construction Firms," The Journal of Real Estate Finance and Economics, Springer, vol. 40(3), pages 310-331, April.
    • Handle: RePEc:kap:jrefec:v:40:y:2010:i:3:p:310-331
    DOI: 10.1007/s11146-008-9158-7
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    References listed on IDEAS

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    1. Russell Kenley, 1999. "Cash farming in building and construction: a stochastic analysis," Construction Management and Economics, Taylor & Francis Journals, vol. 17(3), pages 393-401.
    2. Pami Dua & Anirvan Banerji & Stephen M. Miller, 2006. "Performance evaluation of the New Connecticut Leading Employment Index using lead profiles and BVAR models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 25(6), pages 415-437.
    3. Gelfand, Alan E, et al, 1998. "Spatio-Temporal Modeling of Residential Sales Data," Journal of Business & Economic Statistics, American Statistical Association, vol. 16(3), pages 312-321, July.
    4. Dubin, Robin A, 1998. "Predicting House Prices Using Multiple Listings Data," The Journal of Real Estate Finance and Economics, Springer, vol. 17(1), pages 35-59, July.
    5. Dua, Pami & Miller, Stephen M & Smyth, David J, 1999. "Using Leading Indicators to Forecast U.S. Home Sales in a Bayesian Vector Autoregressive Framework," The Journal of Real Estate Finance and Economics, Springer, vol. 18(2), pages 191-205, March.
    6. Daniel S. Putler & Shilpa Lele, 2003. "An Easily Implemented Framework for Forecasting Ticket Sales to Performing Arts Events," Marketing Letters, Springer, vol. 14(4), pages 307-320, December.
    7. Markos Papageorgiou & Apostolos Kotsialos & Antonios Poulimenos, 2005. "Long-term sales forecasting using holt-winters and neural network methods," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 24(5), pages 353-368.
    8. Peter S. Fader & Bruce G. S. Hardie & Chun-Yao Huang, 2004. "A Dynamic Changepoint Model for New Product Sales Forecasting," Marketing Science, INFORMS, vol. 23(1), pages 50-65, October.
    9. Derek W. Bunn & Stefania Pantelidaki, 2005. "Development of a multifunctional sales response model with the diagnostic aid of artificial neural networks," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 24(7), pages 505-521.
    10. Wendy W. Moe & Peter S. Fader, 2002. "Fast-Track: Article Using Advance Purchase Orders to Forecast New Product Sales," Marketing Science, INFORMS, vol. 21(3), pages 347-364, March.
    11. Donna F. Davis & John T. Mentzer & Teresa M. Mccarthy & Susan L. Golicic, 2006. "The evolution of sales forecasting management: a 20-year longitudinal study of forecasting practices," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 25(5), pages 303-324.
    12. Jonathan Lee & Peter Boatwright & Wagner A. Kamakura, 2003. "A Bayesian Model for Prelaunch Sales Forecasting of Recorded Music," Management Science, INFORMS, vol. 49(2), pages 179-196, February.
    13. Luxhoj, James T. & Riis, Jens O. & Stensballe, Brian, 1996. "A hybrid econometric--neural network modeling approach for sales forecasting," International Journal of Production Economics, Elsevier, vol. 43(2-3), pages 175-192, June.
    14. Dua, Pami & Miller, Stephen M, 1996. "Forecasting Connecticut Home Sales in a BVAR Framework Using Coincident and Leading Indexes," The Journal of Real Estate Finance and Economics, Springer, vol. 13(3), pages 219-235, November.
    15. D J Robb & E A Silver, 2002. "Using composite moving averages to forecast sales," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 53(11), pages 1281-1285, November.
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    Cited by:

    1. Manchun Han & Sanghyo Lee & Jaejun Kim, 2019. "Effectiveness of Diversification Strategies for Ensuring Financial Sustainability of Construction Companies in the Republic of Korea," Sustainability, MDPI, vol. 11(11), pages 1-19, May.
    2. Chuan Zhang & Yu-Xin Tian & Ling-Wei Fan, 2020. "Improving the Bass model’s predictive power through online reviews, search traffic and macroeconomic data," Annals of Operations Research, Springer, vol. 295(2), pages 881-922, December.

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