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MBA thesis on the Philippine stock market
 

MBA thesis on the Philippine stock market

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The Philippine Stock Market and Industry Behavior

The Philippine Stock Market and Industry Behavior

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    MBA thesis on the Philippine stock market MBA thesis on the Philippine stock market Presentation Transcript

    • Jeaneth Michelle L. Balaba MBA Program De La Salle University-Dasmariñas 26 January 2008 THE INFLUENCE OF SELECTED INDUSTRIES ON THE RISK BEHAVIOR OF THE PHILIPPINE STOCK EXCHANGE COMPOSITE INDEX ANNEX A
    • INTRODUCTION TYPES OF RISK ANNEX A Systematic Market/ Relevant/ Non-diversifiable Risk Unsystematic Diversifiable/ Firm-specific Combined Risk Interest risk Inflation risk Business risk Maturity risk Total risk Financial risk Liquidity risk Corporate risk Default risk Exchange rate risk Equity risk Equity index risk Political risk
    • k i = k rf + (k m -k rf )β i ; where k i is the required return on stock i, k rf is the risk-free rate, (k m -k rf )is the market risk premium, and β i is the measure of risk in relation to the returns on a security or portfolio of securities to the returns on the market (stock i’s β). CHAPTER I. INTRODUCTION I. THE CAPITAL ASSET PRICING MODEL (CAPM) Brigham and Houston (2004)
    • Harvey (1995) II. REGRESSION EQUATION
      • STATEMENT OF THE PROBLEM
      • The market risks of industry sectors collectively influence the behavior of the Philippine stock market.
      • Alternatively, the Philippine stock market depends on the performance of Philippine business industry on the whole and not just on the riskiness of the best-performing stocks.
      • OBJECTIVES OF THE STUDY
      • Identify select industry sectors and their effect on the Philippine stock market;
      • Evaluate the riskiness of the PSEi to the movements in the industry indices by testing the predictability of the regression model;
      • Assess the impact of political administrations on the behavior of the PSEi.
    • Thus, the following null and alternative hypotheses are put forward, premised on the regression equation that PSEi = α + β j IndustryIndex H 0 : β j = 0; H a : β j ≠ 0; where β j is the measure of the market risk behavior of the PSEi with respect to movements in the industry index Figure 7. Null and Alternative Hypotheses
    • SIGNIFICANCE OF THE STUDY The performance of business in every sector is critical to the attainment of capital market development. The stock market’s role as source of cheap funds is reinforced when the companies that comprise the stock market are able to go with the direction of the stock market and strengthens it in the process.
    • SCOPE AND LIMITATION
      • The study covers the companies that comprise the PSE Composite Index and PSE Sectoral Index for the years 1997-2005.
      • 2. Only data available for a nine-year period (1997-2005) based on old industry classification are considered.
      • 3. The study utilizes aggregate data (stock indexes) rather than firm-level data.
    • The risk of a firm should be determined by some combination of the firm’s fundamentals and the market characteristics of the firm’s stocks. Elton and Gruber (1994) CHAPTER II. REVIEW OF RELATED LITERATURE
    • The CAPM pushes forward the proposition that the riskier the asset, as measured by the relationship of the returns on the particular security or portfolio of securities to the returns on the market, the higher the returns on the asset. Harvey (1995)
    • The concept of beta arises because all stocks tend to move to some extent with movements in the overall market. Some stocks tend to move more than others when the market moves; thus, their sensitivity to the movements of the overall market index is an important measure, known as the beta coefficient. The beta coefficient is estimated by running a market model regression. Bradfield (2003)
    • In developing countries like the Philippines, stock markets are sensitive not only to economic activity but also to changes in the political and international economic environment. In a study of stock price data of seven economies that included Hong Kong, Indonesia, Thailand and the Philippines that global and regional events like the 1990 Gulf War and the 1997 Asian Currency Crisis led to high volatility episodes whose magnitude relative to normal times differ from country to country. In addition, country-specific events like the opening up of country borders also led to high volatility periods. Bautista (2003), (2005)
    • CHAPTER III. CONCEPTUAL/THEORETICAL FRAMEWORK Dependent Variable PSE Index (PSEi) Independent Variables Financial Index Industrial Index Property Index Mining Index Oil Index Intervening Variables Political climate Asian financial crisis
    • PSE i = α + β 1 Industrial i + β 2 Financial i + β 3 Property i + β 4 Mining i + β 5 Oil i + β 6 GMA + ε, where ε measures the firm-specific or non-diversifiable risks, GMA represents the dummy variable,and sectors represent the sectoral index THEORETICAL FRAMEWORK
    • SUMMARY MATRIX Statement of the Problem/ Objectives Methodology Results and Discussion Conclusion Recommendation Statement of the Problem: Do business industry sectors influence the behavior of the Philippine stock market indicator, PSEi? Regression analysis and secondary data research In general, business industry sectors have a significant effect on the risk behavior of the Philippine stock market, as measured by the PSEi The results validated the PSEi as indicator of the stock market in general and as benchmark for Philippine business and industry. Objective No. 1: Determine the critical industry sectors that influence the PSEi and assess its effect. PSEi = α + β 1 Industrial i + β 2 Financial i + β 3 Property i + β 4 Mining i + β 5 Oil i + β 6 Dummy i + ε All industry sectors showed significant influence on the PSEi except for the mining sector. Four industry sectors contribute to the riskiness of the Philippine stock market, namely: property, industrial, financial and oil. Oil industry has a negative effect . Mining showed no significant effect. Overall, the industry sector performance goes together with the movement of the PSEi, with the exception of the oil industry which showed a negative impact on the PSEi. The oil sector also puts the PSEi most at risk. The oil industry should reverse its impact on the PSEi and make stock investments more attractive by demonstrating significant inroads in oil exploration. Government must develop the oil sector. Investors, especially institutional investors, should compel companies to adopt the principles of responsible investment.
    • SUMMARY MATRIX Statement of the Problem/ Objectives Methodology Results and Discussion Conclusion Recommendation Objective No. 2: Test the predictability of the regression model PSEi = α + β 1 Industrial i + β 2 Financial i + β 3 Property i + β 4 Mining i + β 5 Oil i + β 6 Dummy i + ε PSEi = - 88.925 +0.412 (F) + 0.487(I) – 1.809 (O) + 0.492(P) + 6.257(GMA) + 3.317 t-values= -5.6, 41.9, (F) 163.3, (I) -2.2, (O) 78.6, (P) 1.8 (GMA) adjusted r-sq= .986 f-stat=31983.39 dw stat=1.98 The model was able to predict closely the behavior of the PSEi using the behavior of the sectoral indices. Future research can be made into assessing the managerial effectiveness of these determining Filipino companies and benchmarking them, using firm- level data. Objective No. 3: Assess the impact of political administrations on the behavior of the PSEi The impact of the political environment cannot be underestimated. The PSEi was observed to perform better in the GMA administration than other administrations. Government must continue to provide a conducive business environment for the industry, especially private sector, to thrive. Good government and good governance at all levels should be in place.
    • 1000 1500 2000 2500 3000 3500 4000 1/1/1997 5/1/1997 9/1/1997 1/1/1998 5/1/1998 9/1/1998 1/1/1999 5/1/1999 9/1/1999 1/1/2000 5/1/2000 9/1/2000 1/1/2001 5/1/2001 9/1/2001 1/1/2002 5/1/2002 9/1/2002 1/1/2003 5/1/2003 9/1/2003 1/1/2004 5/1/2004 9/1/2004 1/1/2005 5/1/2005 9/1/2005 RAMOS ESTRADA ARROYO Annex B 0 500
    • Thank you
    • Table 5. Companies Comprising the Philippine Stock Exchange Composite Index (As of 1 December 2005) Source: The Philippine Stock Exchange, Inc. Memo For Broker 274-2005.
    • No. Sector Publicly-Listed Companies, Partial Sectoral Composition 1 Financial BPI Banco de Oro Unibank Manulife Financial Security Bank Metrobank Union Bank Sun Life Financial Phil. National Bank China bank I-Vantage Corporation Equitable-PCI Bank Export & Industry Bank 2 Industrial San Miguel Corp. “A” Manila Water Inc. San Miguel Corp. “B” Holcim Phils., Inc. First Phil. Holdings Petron Corporation Meralco “B” EEI Corporation Universal Robina Corp Roxas Holdings Jollibee Foods Corp. Ginebra San Miguel Meralco “A” 3 Property Ayala Land, Inc. Filinvest Land, Inc. SM Prime Holdings Empire East Cebu Holdings, Inc. Megaworld Corporation Robinson’s Land Corp. Belle Corporation Metro Pacific Corp. 4 Mining Philex Mining Corp. Manila Mining “B” Lepanto Mining “A” Semirara Mining Lepanto Mining “B” Omico Corp Mining “A” Apex Mining “A” Atlas Consolidated Apex Mining “B” 5 Oil The Philodrill Corp. The Philodrill Corp. “B” Oriental Petroleum “A” Oriental Petroleum “B” Petroenergy Resources Corporation