Title

Predicting the ASEAN-4 sectoral performance using commodity price indices

Date of Publication

2017

Document Type

Bachelor's Thesis

Degree Name

Bachelor of Science in Management of Financial Institutions

College

Ramon V. Del Rosario College of Business

Department/Unit

Financial Management Department

Thesis Adviser

Patrick Caoile

Defense Panel Chair

Alfredo M. Santoyo

Defense Panel Member

Robert Dan J. Roces

Abstract/Summary

This study focuses on analyzing the relationship between commodities and sectorial performance in the ASEAN-4 countries (Philippines, Indonesia, Malaysia and Thailand) over the period of 2011-2017, whether the former can be utilized to predict the latter. RICI commodity indices (base metals, precious metals, energy and agriculture) are used to represent the performance of commodities and the proponents devised their own sectorial indices (financial, industrial, services, property and mining & oil) to represent each sectorial performance. Sectors are composed of sub-sectors which constitute the top five largest companies based on its market capitalization. ARIMAX is used as the statistical model for the study. ARIMA and cointegration tests are also used to evaluate the forecasting power of the ARIMAX model in addition to back testing. Empirical results showed that all of the sectors in an aggregate of the 4-ASEAN countries were affected by one or more commodities and exhibited a direct relationship to the former. RICI-agriculture have the largest influence on the property, industrial, services and financial sectors while base metals have the most impact on mining and oil sector. Moreover, forecasted values obtained from ARIMAX is closer to the actual in comparison to the values obtained from ARIMA. These results indicate that individuals can utilize the current values of certain commodity indices to predict performance of certain sectors tomorrow. Nonetheless, only a few ARIMAX models have cointegrated independent and dependent variables, suggesting that these predictive models will be inefficient in the long run.

Abstract Format

html

Language

English

Format

Print

Accession Number

TU21879

Shelf Location

Archives, The Learning Commons, 12F, Henry Sy Sr. Hall

Physical Description

x, 282 leaves ; illustrations (some color) ; 28 cm.

Keywords

Price indexes

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