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JDE MANUEL
SELECTED MACROECONOMIC VARIABLES ON STOCK PRICES: AN EMPIRICAL ANALYSIS OF THE
PHILIPPINE STOCK EXCHANGE INDEX
ByJOANNA MARIE PINA S. DE MANUEL, MBA
*Research was presented last August, 2013 at Research and Educational Development and Training Institute (REDTI) International Research Conference*
JDE MANUEL
BACKGROUND OF THE STUDY
HOUSEHOLD FIRMS
INVESTMENT FUNDS
INCOME
STOCK - A type of security that signifies ownership in a corporation and represents a claim on part of the corporation's assets and earnings.
A holder of stock (a shareholder) has a claim to a part of the corporation's assets and earnings. In other words, a shareholder is an owner of a company. Ownership is determined by the number of shares a person owns relative to the number of outstanding shares. For example, if a company has 1,000 shares of stock outstanding and one person owns 100 shares, that person would own and have claim to 10% of the company's assets.
JDE MANUEL
BACKGROUND OF THE STUDYINVESTORS
Php. 3
Php. 33.33
Php. 100,000 investment or 30,000 shares becomes 999,900 thereafter.
JDE MANUEL
BACKGROUND OF THE STUDYINVESTORS
Php. 3
Php. 33.33
Stock returns are affected by macroeconomic variables
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THEORETICAL FRAMEWORK
ARBITRAGE PRICING THEORY (APT)
An asset pricing model based on the idea that an asset's returns can be predicted using the relationship between that same asset and many common risk factors. Created in 1976 by Stephen Ross, this theory predicts a relationship between the returns of a portfolio and the returns of a single asset through a linear combination of many independent macro-economic variables.
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RESEARCH PARADIGM
Selected Macroeconomic
Variables- Interest rates- Inflation rates- Exchange rates
Philippine Stock Exchange Index (2006-
2013)
INDEPENDENT DEPENDENT
To determine if there is a long and short-run relationship between the selected macroeconomic variables and PSEi.
OBJECTIVES
Selected macroeconomic variables• Interest Rate (91-day T-
bills)• Exchange Rate• Inflation Rate• Philippine Stock
Exchange Index 2006-2013
VARIABLES
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ANALYSIS AND PRESENTATION OF DATA
Augmented Dickey-Fuller (ADF) Test Statistics Results
UN
IT R
OO
T TE
STIN
GAugmented Dickey-Fuller Test (ADF)
LON
G-RU
N R
ELAT
ION
SHIPCo-
integration Tests
SHO
RT-R
UN
REL
ATIO
NSH
IPEngle-Granger Test
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AUGMENTED DICKEY-FULLER (ADF)Variables
DifferenceMulti-collinearity
StatisticsP - value DecisionLevel Intercept
ER
1st Level -2.92 4.467 .099 Significant at .10
2nd Level .163 3.898 .321 Not Significant
3rd Level .075 3.017 .602 Not Significant
4th Level .019 1.742 .864 Not Significant
Durbin Watson Statistic (ER)
2.001
IR 1st Level .247 1.075 .019 Significant at .05 and .10
2nd Level -.096 1.131 -.151 Not Significant
Durbin Watson Statistic (IR)
1.997
CPI 1st Level .261 1.036 .013 Significant at .05 and .10
Durbin Watson Statistic (CPI)
2.108
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LONG-RUN TESTS
Model Coefficient Std. Error t P-value(Constant) .002 .036
Lag e .185 .060 3.084 .003
Co-integration Results
The p-value is .003 which is lesser than .05 and .10 level of significance hence, falling within the rejection region therefore rejecting the null hypothesis of no co-integration between the variables. The result of the data demonstrates that there is a long-run relationship between Psei and the selected macroeconomic variables.
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LONG-RUN TESTS
R R Square Adjusted R Square
Std. Error of the Estimate
.908 .824 .818 .6028
Model Coefficient Std. Error t P-value(Constant) 1.434 1.316
Inflation Rate .297 .087 3.430 .001
Exchange Rate .124 .138 .896 .373
Interest Rate -.558 .058 -9.588 .000
PSEi = 1.434 + .124ER - .558IR + .297CPI + E
Quantitative Model
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LONG-RUN TESTS
Quantitative Model PSEi = 1.434 + .124ER - .558IR + .297CPI + E
1% Increase in Exchange
Rate
.124% Increase in
PSEi
Dimitrova (2005) have observed that exchange rate and stock returns have positive weak correlation.
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LONG-RUN TESTS
Quantitative Model PSEi = 1.434 + .124ER - .558IR + .297CPI + E
1% Increase in Interest
Rate
.558% Decrease in
PSEi
Smith (1990), as cited on the report made by Osamwonyi and Osagie (2012), United States’ economy showed a negative correlation between stocks and interest rate.
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LONG-RUN TESTS
Quantitative Model PSEi = 1.434 + .124ER - .558IR + .297CPI + E
1% Increase in Inflation
Rate
.297% Increase in
PSEi
Hussain and Aamir (2012) supports the findings of this study and have indicated that companies will most likely pass the burden of the new price to consumers and therefore enhance their potential earnings.
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LONG-RUN TESTS
Psei = 1.434 + .124ER - .558IR + .297CPI + EQuantitative Model
Model Sum of Square Df Mean Square F Sig
Regression 156.616 3 52.205 143.678 .000Residual 33.428 92 .363
Total 190.044 95
**F(3,92) = 143.678 presents that the variables statistically significantly predicted Psei.
With a P-value of .000, which is less than .05, the table indicates that the regression model is statistically significant to predict the outcomes of the dependent variable, Psei.
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SHORT-RUN TESTS
Variables Hypothesis P-value Results
ERER to Psei .008*
Uni-directionalPsei to ER .350IR IR to Psei .009*
Bi-directionalPsei to IR .079*CPI CPI to Psei .487
independentPsei to CPI .190
ENGLE GRANGER TEST
The table shows a uni-directional relationship between ER to Psei which implies that ER predicts Psei but not vice versa. IR on the other hand is the only variable that can predict Psei and vice versa and finally CPI reflects no causal relationship to stock prices and vice versa.
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CONCLUSION AND RECOMMENDATION
The study revealed a long-run association between the selected macroeconomic variables and stock prices. ER and CPI showed a positive and significant relationship while IR presented a negative significant relationship with stock prices. The Granger Causality Test revealed that ER have a uni-directional relation, CPI have independent relation and IR have bi-directional relationship.
From the results, it is therefore suggested that money supply and oil price index be included for further studies. More advanced time series models may be used to generate more accurate results. Future researchers may seek to explore the effects of the macroeconomic variables to individual stocks listed under PSEi. To the government, it is suggested to create policies that will monitor the Philippine capital markets. And finally, to the investors, the information taken from this study may serve as basis for investing decision-making.
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CONCLUSION AND RECOMMENDATION
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CONCLUSION AND RECOMMENDATION
THANK YOU FOR LISTENING