Forecasting the Sales of Console Games for the Italian Market

Akaike H., 1974, A new look at the statistical model identification, IEEE Transactions on Automatic Control, 19(6), pp. 716-723.10.1109/TAC.1974.1100705Open DOISearch in Google Scholar

Anvari S., Tuna S., Canci M., Turkay M., 2016, Automated Box–Jenkins forecasting tool with an application for passenger demand in urban rail systems, Journal of Advanced Transportation, (50), pp. 25-49.10.1002/atr.1332Open DOISearch in Google Scholar

Armstrong J.S., 1985, Long-Range Forecasting: From Crystal Ball to Computer, 2nd. ed., Wiley.Search in Google Scholar

Assimakopoulos V., Makridakis S., Spiliotis E., 2018, Statistical and Machine Learning forecasting methods: Concerns and ways forward, Alejandro Raul Hernandez Montoya, Universidad Veracruzana, Mexico Plos One 13(3).10.1371/journal.pone.0194889Search in Google Scholar

Barrow D., Kourentzes N., 2016, Distributions of forecasting errors of forecast combinations: Implications for inventory management, International Journal of Production Economics, 177, pp. 24-33.10.1016/j.ijpe.2016.03.017Search in Google Scholar

Box G.E.P., Jenkins G.M., Reinsel G.C., 1994, Time Series Analysis; Forecasting and Control, 3rd Edition, Prentice Hall, Englewood Cliff, New Jersey.Search in Google Scholar

Brown R.G., 1959, Statistical Forecasting for Inventory Control, McGraw-Hill, New York.Search in Google Scholar

Entertainment Software Association Year Report (2017-2018).Search in Google Scholar

Fildes R., 1989, Evaluation of aggregate and individual forecast method selection rules, Management Science, 35(9), pp. 1056-1065.10.1287/mnsc.35.9.1056Open DOISearch in Google Scholar

Fildes R., Lusk E.J., 1984, The choice of a forecasting model, Omega, 12(5), pp. 427-435.10.1016/0305-0483(84)90042-2Search in Google Scholar

Gardner E.S., Jr., 2006, Exponential smoothing: The state-of-the-art – Part II, International Journal of Forecasting, 22(4), pp. 637-666.10.1016/j.ijforecast.2006.03.005Open DOISearch in Google Scholar

Gardner E.S., Jr., McKenzie E., 1985, Forecasting trends in time series, Management Science, 31, pp. 1237-1246.10.1287/mnsc.31.10.1237Open DOISearch in Google Scholar

Gardner E.S., Jr., McKenzie E., 1988, Model identification in exponential smoothing, The Journal of the Operational Research Society, Vol. 39(9), pp. 863-867.10.1057/jors.1988.146Open DOISearch in Google Scholar

Gardner E.S., Jr., McKenzie E., 2011, Why the Damped Trend works, Journal of the Operational Research Society, 62(6), pp. 1177-1180.10.1057/jors.2010.37Open DOISearch in Google Scholar

Handanhal V.R., 2013, Determining the optimal values of exponential smoothing constants – does solver really work?, American Journal of Business Education, 6 (3).10.19030/ajbe.v6i3.7815Search in Google Scholar

Hannan E.J., Quinn B.G., 1979, The determination of the order of an autoregression, Journal of the Royal Statistical Society, Series B, 41, pp. 190-195.10.1111/j.2517-6161.1979.tb01072.xSearch in Google Scholar

Hibon M., Makridakis S., 1979, Accuracy of forecasting, Journal of the Royal Statistical Society Series A (General), 142(2).10.2307/2345077Search in Google Scholar

Hyndman R.J., Koelher A.B., Ord J.K., Snyder R.D., 2008, Forecasting with Exponential Smoothing, The State Space Approach, Springer Series in Statistics.10.1007/978-3-540-71918-2Search in Google Scholar

Hyndman R.J., Koehler A.B., Snyder R.D., Grose S., 2002, A state space framework for automatic forecasting using exponential smoothing methods, International Journal of Forecasting, 18(3), pp. 439-454.10.1016/S0169-2070(01)00110-8Open DOISearch in Google Scholar

Holt C.C., 1957, Forecasting Seasonals and Trends by Exponentially Weighted Moving Averages, ONR Memorandum, Vol. 52, Carnegie Institute of Technology, Pittsburgh.Search in Google Scholar

International Game Developer Association, Developer Satisfaction Survey 2017.Search in Google Scholar

Kalman R.E., 1960, A New Approach to Linear Filtering and Prediction Problems, Research Institute for Advanced Study, Baltimore, Maryland.10.1115/1.3662552Search in Google Scholar

Koehler A.B., Ord J.K., Snyder R.D., 2001, Forecasting models and prediction intervals for the Multiplicative Holt-Winters Method, International Journal of Forecasting, 17(2), pp. 269-287.10.1016/S0169-2070(01)00081-4Open DOISearch in Google Scholar

Lutkepohl H., Xu F., 2009, The role of the log transformation in forecasting economic variables, EUI Working Papers, Max Weber Programme.10.2139/ssrn.1505506Search in Google Scholar

Gossel W., Laehne R., 2013, Applications of time series analysis in geosciences: An overview of methods and sample applications, Hydrology and Earth System Sciences Discussions, 10(10), pp. 12793-12827.10.5194/hessd-10-12793-2013Search in Google Scholar

Lattyak W.J., Stokes H.H., 2011, Exponential Smoothing Forecasting Using SCAB34S and SCA Work-Bench, Department of Economics University of Illinois, Chicago.Search in Google Scholar

Newzoo Global Market Report, 2018, Trends, Insights, and Projections toward 2021.Search in Google Scholar

Office for National Statistics, 2008, From Holt-Winters to ARIMA Modelling: Measuring the Impact on Forecasting Errors for Components of Quarterly Estimates of Public Service Output, UK Centre for the Measurement of Government Activity.Search in Google Scholar

Sbrana G., 2012, Damped trend exponential smoothing: Prediction and control, Journal of Quantitative Economics, 10(2), pp. 152-192.Search in Google Scholar

Schwarz G.E., 1978, Estimating the dimension of a model, Annals of Statistics, 6(2), pp. 461-464.10.1214/aos/1176344136Open DOISearch in Google Scholar

Winters P.R., 1960, Forecasting sales by exponentially weighted moving averages, Management Science, 6, pp. 324-342.10.1287/mnsc.6.3.324Open DOISearch in Google Scholar

Zhang G.P., 2001, Time series forecasting using a hybrid ARIMA and neural network model, Neurocomputing, 50, pp. 159-175.10.1016/S0925-2312(01)00702-0Search in Google Scholar