1. ARE THERE RATIONAL SPECULATIVE BUBBLES IN ASEAN STOCK MARKETS? Gilbert V. Nartea Bo Hu and Baiding Hu Faculty of Commerce Lincoln University New Zealand

2. Introduction  Bubbles: long run up in price followed by a crash. (e.g., ++++++++++++ -)  Stock prices diverge from fundamental values  Often attributed to irrational behaviour and evidence of inefficient markets.  Rational bubble is a special case  investors realise a bubble exists, but they find it rational to stay in the market because they believe the growth rate of the bubble compensates them for the possibility of a crash.

3. Introduction  Episodes of price run ups followed by large drops in ASEAN stock markets.  Led observers to suggest presence of bubbles  No conclusive evidence of whether or not rational speculative bubbles exist in Asian stock markets. Important issue in relation to the efficient allocation of investment resources and asset pricing.

4. Introduction  Common tests for bubbles  Cointegration (relation between fundamentals and stock prices)  Descriptive stats (autocorrelation, skewness, and kurtosis) in stock returns These attributes necessarily derive from the two characteristics of bubbles (i.e price run-up and crash). ++++++++++++ - The long run of positive returns (positive autocorrelation) and the singular negative return during the crash means that the bubble process must be skewed. Leptokurtosis (fat-tailed distributions) is consistent with the occasional large deviation in price characterising the crash. Problem is these could also be caused by other factors other than bubbles.  Duration dependence (McQueen and Thorley, 1994).

5. Introduction  We use descriptive stats and duration dependence tests for Indonesia, Malaysia, and the Philippines (1991 to 2009).  Preliminary results

6. Introduction  McQueen and Thorley (1994)  Testable implication of rational speculative bubbles: the longer is the run of positive returns, the smaller is the probability that the run will end (negative duration dependence)

7. Introduction  Rational bubble process :  UPC = ΔFV + ΔBubble UPC = unexpected price changes ΔFV = changes in fundamental value ΔBubble = changes in the bubble  As the bubble component grows it dominates the fundamental component  in such a way that negative shocks to fundamental value will have minimal impact on total returns  hence as the bubble grows, the longer is the run of positive returns and the probability of getting a negative total return decreases (ie., negative duration dependence)  (as to what causes the bubble to grow and what causes it to eventually burst, unfortunately we do not yet have a coherent theory about how this comes about)

8. Introduction  Duration dependence test does not require  specification of the underlying fundamental value relationship model.  normality of the time series behaviour under investigation

9. Literature Review  Chan et al. (1998)  Duration dependence tests (1975- 1994)  Rational speculative bubbles in Thailand but not in Hong Kong, Japan, Korea, Malaysia, Taiwan.  Sarno and Taylor (1999)  Cointegration tests (1989-1997)  Bubbles in China, Indonesia, Malaysia, Philippines, Singapore, South Korea, Taiwan and Thailand  Ali et al. (2009) and Mokhtar et al. (2006)  Rational speculative bubbles in Malaysia

10. Literature Review  Jirasakuldech et al. (2008)  cointegration and duration dependence tests (1975- 2006)  Rational speculative bubbles in the Thai stock market consistent with those of Watanapalachaikul and Islam (2007).  Rangel and Pillay (2007)  excess volatility tests, cointegration tests, duration dependence tests, and the intrinsic bubbles model (1975-2007)  Rational speculative bubbles in Singapore

11. Data and Methods  McQueen and Thorley (1994) suggest  monthly data contains less noise  but short data series from monthly data could result in lack of power of tests used  we use both monthly and weekly index values.  Monthly and weekly closing prices from Datastream (February 1991- December 2009)  Jakarta Composite Index,  Kuala Lumpur Composite Index and the  Philippine Stock Exchange Index

12. Data and Methods  We use real returns  First, transform real returns into run lengths of positive and negative observed returns, i.e., ++++++---+++++++++-  Run is a sequence of returns with the same sign.

13. Data and Methods  Next we compute the probability of ending a run or the sample hazard rate for each length i h i = N i /(M i + N i )  where  N i is the number of completed runs of the length i, and  M i the number of completed runs with length greater than i.

14. Data and Methods  Examine the relation between the hazard rate or probability of the run ending (h i ) and length of the run i.  A negative relationship indicates the presence of rational speculative bubbles.  Focus only on positive runs  since t here can be no bubbles in runs of negative returns because this would imply that stock prices can be negative as the bubble grows over time.

15. Data and Methods  Formal test  We estimate a Log-logistic hazard function. h i = {1+ exp[-α -β ln(i)]} -1  where  h i is the hazard rate (probability of ending a run)  i is the length of the run and  β is the slope parameter.  A negative β signals the presence of rational bubbles  probability of a positive run ending is a decreasing function of the length of the run (ie., negative duration dependence)

16. Empirical Results  Index plots  Descriptive statistics  Duration dependence tests

17. Figure 1. Index Plots

18. Figure 1. Index plots  Evident from plots  Long run-up in price followed by a sudden drop  1993 to 1997 (Asian financial crisis)  JCI reached an historic low in September 1997;  PSE CI dropped 1000 points from a high of some 3000 points in the same year.  KL CI lost more than 50%, from above 1,200 points to fewer than 600 points during May to December.  2001 (U.S. housing bubble) to 2007 (Sub-prime loan financial crisis)

19. Table 1a. Real monthly returns, 02:1991-12:2009 Indonesia (Jakarta Composite Index) Malaysia (Kuala Lumpur Composite Index) Philippines (Philippine Composite Index) Monthly returns T227 Mean-0.000809 0.0016910.001758 Maximum0.286522 0.3345830.336165 Minimum-0.401982 -0.386219-0.294769 Standard Deviation0.089032 0.0792530.083648 Skewness-0.818110 -0.2757170.183939 (SE)(0.162578) Kurtosis6.451037 7.8410695.222854 (SE)(0.325156) Jarque-Bera137.9675 224.541148.01441 ρ 1ρ 1 0.229 0.1040.109 ρ 2ρ 2 0.000 0.1450.074 ρ 3ρ 3 0.051-0.119-0.049 ρ 4ρ 4 0.102-0.061-0.044 ρ 5ρ 5 0.002-0.0710.011 ρ 6ρ 6 0.048-0.074-0.023 ρ 12 -0.074-0.0660.073 Q(6)15.68013.9785.1811 Q(12)20.70836.50911.048

20. Table 1b. Real weekly returns, 02:1991-12:2009 Indonesia (Jakarta Composite Index) Malaysia (Kuala Lumpur Composite Index) Philippines (Philippine Composite Index) Weekly returns T987 Mean -0.0003790.0003470.000276 Maximum 0.2185980.2852990.180984 Minimum -0.259975-0.210479-0.216020 Standard Deviation 0.0413120.0353440.039632 Skewness -0.2883500.143651-0.043448 (SE) (0.077968) Kurtosis 8.29819112.229855.551043 (SE) (0.155936) Jarque-Bera 1168.0903503.283267.9447 ρ 1ρ 1 -0.025-0.018-0.011 ρ 2ρ 2 0.0810.0050.064 ρ 3ρ 3 0.1190.0820.079 ρ 4ρ 4 0.087-0.006-0.020 ρ 5ρ 5 0.0610.0600.035 ρ 6ρ 6 0.0650.044-0.016 ρ 12 0.020-0.061-0.006 Q(6)36.49812.58512.218 Q(12)50.05725.56924.632

21. Descriptive statistics  Mean Monthly returns  Similar for Malaysia and the Philippines  Indonesia had a negative average monthly real return  Maximum Monthly returns  Similar for Malaysia and the Philippines  Lower for Indonesia  Minimum Monthly returns  Indonesia experienced the lowest real return, followed by Malaysia then Philippines.  ALL monthly and weekly return distributions are Non-normal (Jarque-Bera test statistics).

22. Descriptive statistics  Negative coefficients of skewness imply the presence of bubbles.  Skewness of Monthly and Weekly returns  Significant negative skewness in Indonesia (consistent with bubbles)  BUT NOT in Malaysia and the Philippines.

23. Descriptive statistics Leptokurtosis of returns also imply the presence of rational speculative bubbles. Monthly and weekly returns in ALL markets exhibit leptokurtosis Consistent with the presence of rational speculative bubbles.

24. Descriptive statistics  Autocorrelated returns (serial dependence) could also indicate the presence rational speculative bubbles.  Sample autocorrelation coefficients  Monthly returns: seriaI dependence in Indonesia and Malaysia but NOT in Philippines Bubble in Indonesia and Malaysia  Weekly returns: serial dependence in ALL series. Bubble in ALL three markets

25. Descriptive statistics  We also conducted two Ljung-Box (LB) tests, one that included the first six and twelve-order autocorrelation coefficients (Q(6)), and (Q(12)).  Monthly series: the two LB tests agree with the conclusions derived from the individual autocorrelation coefficients that returns are serially correlated in Indonesia and Malaysia but not in the Philippines.  Weekly series: slight disagreement between the LB tests and the individual autocorrelation coefficients in the case of the Philippines. The Q(6) values suggest serial independence in the Philippines while the individual auto correlation coefficients suggest otherwise.

26. Descriptive statistics Autocorrelation On balance, the autocorrelated returns in Indonesia and Malaysia and to some extent in the Philippines suggest the presence of rational speculative bubbles in these markets.

27. Descriptive statistics  In summary  The characteristics of the return distributions indicate (in varying degrees) the presence of rational speculative bubbles in these markets.  However, these characteristics could also be due to factors NOT related to rational speculative bubbles.  Hence we conduct duration dependence tests next.

28. Duration dependence tests  Monthly returns  Weekly returns  Sub-period analysis

29. Table 2. Tests of duration dependence for positive runs of monthly indices’ returns for the full period (1991-2009) IndonesiaMalaysiaPhilippines Run Length Actual Run Counts Sample Hazard Rates Actual Run Counts Sample Hazard Rates Actual Run Counts Sample Hazard Rates 1 240.4800250.4717260.4643 2 90.346290.3214120.4000 3 90.529490.4737110.6111 4 20.250030.300050.7143 5 20.333340.571421.0000 6 10.250020.6667 7 2 11.0000 8 1 9 10 Total 50 53 56 Log-logistic test α -0.17166 0.27139 0.28014 β -0.14474 0.03684 0.55549 LRT of H0: β =0 0.2390 0.0145 2.2331 ( p-value) 0.6249 0.9041 0.1351

30. Monthly returns  Indonesia  longest run of positive returns : 8 months  If monthly returns are independent, the probability of getting 8 consecutive positive runs is 4 in one thousand.  The fact that we have 1 run of 8 consecutive positive returns out of 227 observations seem to indicate the presence of bubbles. The question is, are they rational bubbles?  “Eyeballing” sample hazard rates do not reveal any discernible patterns (no rational speculative bubbles over the sample period?)

31. Monthly returns  Malaysia  longest run: 7 months  sample hazard rates also do not reveal any pattern  no rational speculative bubbles over the sample period.

32. Monthly returns  Philippines  Longest run: 5 months  Hazard rates appear to be increasing (opposite to the pattern we would expect in the presence of rational speculative bubbles).

33. Monthly returns  Log-logistic test on the level of beta.  Indonesia is negative at -0.14474, BUT statistically insignificant (p-value of 0.6249)  Malaysia and the Philippines are of the wrong sign and statistically insignificant.  Therefore, No rational speculative bubbles in Indonesia, Malaysia and the Philippines

34. Table 3. Tests of duration dependence for positive runs of weekly indices’ returns for the full period (1991-2009) IndonesiaMalaysiaPhilippines Run Length Actual Run Counts Sample Hazard Rates Actual Run Counts Run Length Actual Run Counts Sample Hazard Rates 1 1070.48421070.47141220.5126 2 470.4123540.4500590.5086 3 270.4030290.4394240.4211 4 160.4000140.3784110.3333 5 8 70.3043120.5455 6 60.375040.250070.7000 7 20.200080.666731.0000 8 20.250030.7500 9 40.666700.0000 10 10.500000.0000 11 00.00000 12 11.00001 13 Total 221 227 238 Log-logistic test α -0.09387 0.11663 0.026118 β -0.26994 1.3875 -0.07468 LRT of H0: β =0 4.0593 1.3875 0.2230 ( p-value) 0.0440** 0.2388 0.6367

35. Weekly returns  Indonesia  the longest run: 12 weeks  sample hazard rates appear to be decreasing consistent with the presence of rational speculative bubbles.  Malaysia  the longest run: 12 weeks  sample hazard rates appear be decreasing  Philippines  longest run: 7 weeks but its  hazard rates also appear to be decreasing

36. Weekly returns  Log-logistic test on level of beta  Indonesia is negative at -0.26994 and is statistically significant (p-value of 0.0440).  Malaysia and the Philippines have negative beta coefficients BUT not statistically significant.  Therefore there is evidence of rational speculative bubbles in Indonesia BUT not in Malaysia and the Philippines.

37. Sub-period analysis We divide the sample into four sub- periods: 1991-1997 (run-up towards Asian Fin. Crisis (AFC)) 1998-2001 (immediate aftermath of AFC) 2002-2007 (run-up towards Global Fin. Crisis (GFC)) 2008-2009 (immediate aftermath of the GFC)

38. Table 4a. Tests of duration dependence for positive runs of monthly indices’ returns for sub-periods. IndonesiaMalaysiaPhilippines Monthly returns 1991-1997 α -0.49470.006562-0.39061 β 0.511646-0.313520.869177 LRT 0.73730.41221.7131 p - value 0.39050.52090.1906 1998-2001 α 1.1132050.3651650.351353 β -0.84681-0.39236-0.32962 LRT 0.67410.43100.1599 p - value 0.41160.51150.6892 2002-2007 α -1.35115-0.83989-0.36268 β 0.5106390.5639520.5304 LRT 1.16681.16390.7969 p - value 0.28010.28070.3720 2008-2009 α 0.890085-1.22568-1.10348 β -1.229160.9495991.892696 LRT 1.25100.70551.9281 p - value 0.26340.40090.1650

39. Table 4b. Tests of duration dependence for positive runs of weekly indices’ returns for sub-periods. IndonesiaMalaysiaPhilippines Weekly returns 1991-1997 α -0.06359-0.31126-0.0772 β -0.427080.0376240.105562 LRT3.45580.02550.1523 p - value 0.0630* 0.87320.6964 1998-2001 α 0.2023920.3848730.174027 β 0.255737-0.54013-0.08751 LRT0.35272.63100.0509 p - value0.55260.10420.8216 2002-2007 α -0.37766-0.211550.097248 β -0.18976-0.21222-0.26455 LRT0.84180.89851.0574 p - value0.35890.34320.3038 2008-2009 α -0.30705-0.4558-0.29281 β 0.4582290.3214950.118261 LRT0.77150.45950.0680 p - value0.37980.49790.7943

40. Sub-periods Panel A (Monthly returns) No significant beta in any sub-period in ALL markets No rational speculative bubbles consistent with full sample Panel B (Weekly returns)  No rational speculative bubbles in any sub-period for Malaysia and Philippines. Evidence of rational speculative bubbles in Indonesia (1991-1997); none in other sub-periods. Rational bubble detected in Indonesia in the full sample of weekly returns is due to at least one bubble episode in the run up towards the AFC of 1997.

41. Concluding remarks  Apparent episodes of long price run ups followed by large drops in ASEAN stock markets  prompted the popular press to conjecture the presence of asset bubbles in these markets causing stock prices to deviate from fundamental values.  Duration dependence to formally test for the presence of rational speculative bubbles in the stock markets of Indonesia, Malaysia, and the Philippines (1991-2009).

42. Concluding remarks  Results suggest that stock prices have deviated from fundamental values in Indonesia likely caused by rational speculative bubbles.  Sub-period analysis further reveals that the bubble might have occurred over the period from 1991 to 1997.

43. Concluding remarks  We do not detect rational bubbles in Malaysia and the Philippines.  This implies that the long run up in prices and the subsequent drop seen in the months leading up to the AFC and GFC could have been justified by fundamental value changes (ie, no bubble).  However also possible that there was a bubble but caused by irrational investor behaviour.  Or our tests may not be powerful enough to detect bubbles.  We suggest that further research into this area is warranted.

44. Thank you