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dc.contributor.authorDalapo, Alexandre Nicole
dc.contributor.authorBantilan, Judy Ann
dc.contributor.authorMonson, Janica
dc.date.accessioned2025-02-15T08:01:41Z
dc.date.available2025-02-15T08:01:41Z
dc.date.issued2022-09
dc.identifier.citationDalapo, A. N. O., Bantilan, J. A. B., & Monson, J. B. (2022). Forecasting PSEI using Holtwinter multiplicative model [Undergraduate Thesis]. University of Mindanao.en_US
dc.identifier.urihttps://repository.umindanao.edu.ph/handle/20.500.14045/1299
dc.descriptionIn Partial Fulfillment of the Requirements for the Degree of Bachelor of Science in Business Administration Major in Financial Managementen_US
dc.description.abstractThis study aims to determine and forecast stock prices in the Philippines using time series analysis, precisely the Holt-winter multiplicative method. The study proves that the HW-multiplicative model is better than the HW additive and simple moving average. The relative mean absolute error (MAE), mean square error (MSE) and mean absolute percentage error (MAPE) is the final indicators of the accuracy of forecasting models utilized. The margin of error between the Holt-winter Multiplicative, Holt-winter Additive, and Simple Moving Average models is compared to see which one is the most accurate. The lesser the error, the closer the stock market in the Philippines is to its actual trend. The data also demonstrated that the volatility of both price and non-price factors had a direct influence on the movement of the Philippine stock market. By displaying graphical patterns and thorough tables of data, this study ensures that predicting is free of bias.en_US
dc.language.isoen_USen_US
dc.publisherCollege of Business Administrationen_US
dc.subjectEconomic forecastingen_US
dc.titleForecasting PSEI using Holtwinter multiplicative modelen_US
dc.typeThesisen_US


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