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Euro-Philippine Network in Banking and Finance Markov-Switching Market Risk Carlos Bautista Daniel Goyeau Joel Yu 27 August 2007 International Conference.

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Presentation on theme: "Euro-Philippine Network in Banking and Finance Markov-Switching Market Risk Carlos Bautista Daniel Goyeau Joel Yu 27 August 2007 International Conference."— Presentation transcript:

1 Euro-Philippine Network in Banking and Finance Markov-Switching Market Risk Carlos Bautista Daniel Goyeau Joel Yu 27 August 2007 International Conference on the Safety and Efficiency of the Financial Sector

2 Euro-Philippine Network in Banking and Finance Background Market Risk is measured by Beta, cov(r i,r m )/var(r m ) Traditional Estimation of Beta: Market Model R i = a + beta (R m -R f ) In the CAPM model, beta explains the cross section of expected returns on securities

3 Euro-Philippine Network in Banking and Finance Literature Time-varying beta –Empirical evidence –Nature of change/causes of change Beta as an explanatory variable and predictor of events Difficulty with existing methods

4 Euro-Philippine Network in Banking and Finance Model and Data Markov-switching market risk –Two states –Fixed transition probabilities –Markov-switching process Data –Datastream price data of 22 stocks of 17 firms in the PSEi –91-day T-bill rate

5 Euro-Philippine Network in Banking and Finance Results There is a strong statistical support for non- linearity in the market model In most cases, there is a fairly high frequency of changes in the market risk of common stocks in the Philippines from low beta regime to high beta regimes. There are few cases where there is a transient change in market risk, albeit significantly longer in duration. There are cases where there seems to be a permanent change in the market risk of the firm.

6 Euro-Philippine Network in Banking and Finance Results: Case 1 Jollibee Foods Corp Low Beta:0.43 High Beta:1.19 Metro Pacific Low Beta:1.23 High Beta:2.35

7 Euro-Philippine Network in Banking and Finance Results: Case 2 ICTSI Low Beta:0.80 High Beta:2.16 MERALCO Low Beta:1.01 High Beta:2.28

8 Euro-Philippine Network in Banking and Finance Results: Case 3 SAN MIGUEL Low Beta:0.54 High Beta:0.89 BPI Low Beta:0.30 High Beta:1.27

9 Euro-Philippine Network in Banking and Finance Conclusions This study demonstrates that time variation in the CAPM can be adequately modeled through Markov switching techniques. Results show that the technique is a productive alternative in evaluating the market risk of firms in the Philippines. Shifts in the market risk seem to be related to market developments which can have a permanent or transient change in the volatilities of security returns relative to that of the market.


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