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Item Restricted The impact of natural disasters on Philippine stock market: an analysis utilizing VAR and GARCH(2023-07) Cao, Cayenne T.; Catap, Diana Louise A.; Jandoc, Karl Robert L.This study investigates the relationships between natural disasters and the Philippine stock market through the utilization of Vector Autoregression (VAR) and Generalized Autoregressive Conditional Heteroskedasticity (GARCH) models. Through the GARCH analysis, we found that floods and droughts both have a negative impact on the Industrials, Property, Services, and Mining and Oil Sectors. The VAR model shows that drought has a negative impact on the closing price of the mining and oil sector and storms have a positive effect on the closing price of the property sector. As for the natural disaster’s effects on Macroeconomic factors, our analysis shows that volcanic activity has a negative relationship with the exchange rate and so does drought with the inflation rate. Our results suggest that any financial decisions to be made that account for the volatility effects of natural disasters may be done in consideration of the factors that have significant impacts on closing prices.Item Restricted Modelling the oil price–exchange rate nexus: the Philippine case(2023-01-16) Dela Cruz, Frabert Ace E.; Reyes, Eirene Gillian M.; Alburo, Florian A.This paper examines the impact of oil prices on the PHP/USD nominal exchange rate. The literature specifies two channels through which the effects of oil price shocks are transmitted to changes in exchange rates. In the case of the Philippines, one can see that the “terms of trade” channel is the dominant effect. Using daily oil prices and PHP/USD exchange rate data from January 2, 2003 to October 24, 2022, this study employed the Generalized Autoregressive Conditional Heteroskedasticity (GARCH) model to determine the effects of oil prices on the exchange rate. The results show that a 10% increase in oil prices is associated with a 0.13% Philippine peso appreciation relative to the US dollar and is statistically significant. This finding is consistent with the “terms of trade” channel, where oil price increases are expected to be associated with exchange rate appreciation for countries with energy-intensive non-tradable sectors.Item Restricted The search for digital gold: Google trends data as a predictor for cryptocurrency price volatility(2023-07) Maliwanag, Rafael John S.; Uligan, Ileanna April D.; Alburo, Florian A.Cryptocurrency price determination is one of the most interesting phenomena in modern finance. Polarizing as it is volatile, return and, consequently, risk in cryptocurrencies dwarf those of other traditional financial markets, and hence, constructing more holistic models of prediction undoubtedly has practical value. Proving to be useful in predicting market outcomes, the benefits of incorporating web search activity in forecasting models of cryptocurrency may be augmented due to the digital nativity of the market. Using time series data obtained from Google Trends, this paper examines the predictive capability of Google search volumes on cryptocurrency price volatility beyond prominent volatility models such as the GARCH(1,1). The study employs a two-step approach consisting of a GARCH(1,1) process and an ordinary least squares (OLS) regression. The conditional variance from the former, along with short-term and long-term indicators of Google Trends data are used as independent variables in an OLS regression of log volatility. The study has three main findings: 1.) Google Trends data predict cryptocurrency price volatility beyond the GARCH(1,1) model; 2.) Cryptocurrency price volatility is more responsive to the short-term Google Trends indicators rather than the long-term; and 3.) Among examined categories, keywords relating to the name and ticker of the coin (e.g. “Bitcoin” and “BTC”, for Bitcoin) and on widespread cryptocurrency-related terms have the most significant additional forecasting capabilities on the volatility of cryptocurrency returns beyond the GARCH(1,1). On the other hand, economic, geopolitical, and pandemic-related words seem to have little to no additional predictive capabilities. Ethereum is found to be most responsive to Google Trends data, while Cardano was found to be least responsive.Item Restricted Consumption an the stock market in the Philippine: evidence from a vector autoregression approach(2013-10) Contreras, Sofia T.; Garcia, Czarina V.; Balanquit, Romeo Matthew T.This paper empirically analyzes the relationship among consumption, stock market returns, and stock market volatility using evidence from the Philippines over the period 1998-2013. Based on the Generalized Autoregressive Conditional Heteroskedasticity (GARCH) model, it is found that high volatility clustering occurs with high predictability in the Philippine stock market, but this does not lead to large changes in consumption. Results of the study using the Vector Autoregression (V AR) analysis also reveal that changes in the stock market do not Granger-cause changes in consumption.Item Restricted Navigating uncertainty: the effect of West Philippine Sea geopolitical risk on Philippine Stock and Foreign Exchange Markets through OLS, GARCH, and Event Study(2025-06-06) Alcantara, Adrian M.; Tanjuatco, Rafael Emmanuel H.; Magno, Maria Cielo D.This study aims to find out the effect of geopolitical risk, specifically the West Philippine Sea dispute, on the Philippine stock and foreign exchange markets. The West Philippine Sea dispute continues to be a major concern for the Philippines and the sovereignty of territory. The study hypothesizes that the increased geopolitical risk due to the West Philippine Sea dispute lead to decreased market returns, PHP depreciation, and increased market volatility. Utilizing a custom West Philippine Sea Geopolitical Risk Index consisting of local news sources, namely The Manila Times, INQUIRER.net and Business Mirror, these hypotheses were tested using OLS, GARCH and event study empirical models. Results show that geopolitical risk from the WPS does not have a statistically significant effect on both the returns and volatility of the PSEi and USD/PHP exchange rate. In addition, the event study showed no significant abnormal returns around major WPS-related incidents. The Philippine markets are relatively insensitive to the local geopolitical events in the WPS. This can be likely due to investor sentiment in emerging markets having a stronger influence from global factors. The study contributes to the existing literature on emerging markets sensitivity to geopolitical risk in the context of the Philippines and West Philippine sea dispute.