Forecasting the Sales of Console Games for the Italian Market

• Autorzy: Renato Rossetti

Warianty tytułu

Prognozowanie sprzedaży gier konsolowych na rynek włoski

• Języki publikacji: EN

Abstrakty

EN

In videogames industry, time series analysis can be very useful in determining the general evolution and behaviour of the market dynamics. These methods are applicable to any time series forecasting problem, regardless of the application sector. This article discusses time series approaches to forecast the sales of console games for the Italian market. In particular two univariate techniques were evaluated, exponential smoothing and the SARIMA technique. The aim is to exploit the capabilities of these statistical methods in order to have a comparison of the results and to choose the most accurate model through an ex-post evaluation. Using monthly time-series data from November 2005 to September 2017, the selection of the most suitable model was indicated by the smallest value of the measures of accuracy (MAPE, sMAPE, RMSE) for the out-of-sample observations regarding the period October 2017-September 2018. The implementation of the models was done using Forecast PRO and Gretl. The time series involved is related to the sales regarding the first party manufacturers of consoles and handhelds (Microsoft, Sony and Nintendo).(original abstract)

Analiza szeregów czasowych może być bardzo przydatna w określaniu ogólnej ewolucji i zachowania dynamiki rynku gier wideo. Metody mogą być stosowane do poszukiwania rozwiązań problemów związanych z prognozowaniem szeregów czasowych, niezależnie od sektora aplikacji. W prezentowanym artykule omówiono aplikacyjne aspekty zastosowania szeregów czasowych do prognozowania sprzedaży gier konsolowych na rynek włoski. Zastosowano i oceniono użyteczność dwóch technik jednoczynnikowych, takich jak wygładzanie wykładnicze i technika SARIMA. Celem badania było wykorzystanie możliwości tych metod statystycznych do porównania wyników i wybrania najdokładniejszego modelu na podstawie oceny ex post. Na podstawie danych miesięcznych (od listopada 2005 r. do września 2017 r.) wskazano najbardziej odpowiedni model o najmniejszej wartości miar dokładności (MAPE, sMAPE, RMSE) dla obserwacji poza próbą dotyczących okresu październik 2017 r. - wrzesień 2018 r. Implem4entację modeli przeprowadzono z wykorzystaniem Forecast PRO i Gretl. Szeregi czasowe dotyczyły wielkości sprzedaży pierwszych producentów konsol i urządzeń przenoś- nych (Microsoft, Sony i Nintendo).(abstrakt oryginalny)

Słowa kluczowe

EN

SARIMA models; Forecasting; Econometrics; Computer games

PL

Modele SARIMA; Prognozowanie; Ekonometria; Gry komputerowe

• Czasopismo: Ekonometria / Uniwersytet Ekonomiczny we Wrocławiu
• Rocznik: 2019
• Tom: 23
• Numer: nr 3
• Strony: 76--88

Twórcy

autor

Renato Rossetti

• Ubisoft S.p.A., Milan, Italy

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Identyfikatory

DOI

10.15611/eada.2019.3.07