Conditional beta capital asset pricing model (CAPM) and duration dependence tests

Similar documents
Conditional Beta Capital Asset Pricing Model (CAPM) and Duration Dependence Tests

MgtOp 215 Chapter 13 Dr. Ahn

THE VOLATILITY OF EQUITY MUTUAL FUND RETURNS

Tests for Two Correlations

ACADEMIC ARTICLES ON THE TESTS OF THE CAPM

Which of the following provides the most reasonable approximation to the least squares regression line? (a) y=50+10x (b) Y=50+x (d) Y=1+50x

International ejournals

Evaluating Performance

Consumption Based Asset Pricing

Kent Academic Repository

ECONOMETRICS - FINAL EXAM, 3rd YEAR (GECO & GADE)

CHAPTER 9 FUNCTIONAL FORMS OF REGRESSION MODELS

3/3/2014. CDS M Phil Econometrics. Vijayamohanan Pillai N. Truncated standard normal distribution for a = 0.5, 0, and 0.5. CDS Mphil Econometrics

Final Exam. 7. (10 points) Please state whether each of the following statements is true or false. No explanation needed.

Financial Risk Management in Portfolio Optimization with Lower Partial Moment

Domestic Savings and International Capital Flows

R Square Measure of Stock Synchronicity

An Application of Alternative Weighting Matrix Collapsing Approaches for Improving Sample Estimates

A Meta Analysis of Real Estate Fund Performance

A copy can be downloaded for personal non-commercial research or study, without prior permission or charge

TRADING RULES IN HOUSING MARKETS WHAT CAN WE LEARN? GREG COSTELLO Curtin University of Technology

SYSTEMATIC LIQUIDITY, CHARACTERISTIC LIQUIDITY AND ASSET PRICING. Duong Nguyen* Tribhuvan N. Puri*

Market Opening and Stock Market Behavior: Taiwan s Experience

>1 indicates country i has a comparative advantage in production of j; the greater the index, the stronger the advantage. RCA 1 ij

Monetary Tightening Cycles and the Predictability of Economic Activity. by Tobias Adrian and Arturo Estrella * October 2006.

THE MARKET PORTFOLIO MAY BE MEAN-VARIANCE EFFICIENT AFTER ALL

Maturity Effect on Risk Measure in a Ratings-Based Default-Mode Model

On the Style Switching Behavior of Mutual Fund Managers

A Comparison of Statistical Methods in Interrupted Time Series Analysis to Estimate an Intervention Effect

Notes are not permitted in this examination. Do not turn over until you are told to do so by the Invigilator.

Raising Food Prices and Welfare Change: A Simple Calibration. Xiaohua Yu

Evaluation of the Factors Affecting Initial Public offering Underpricing by Newly-accepted Companies into Tehran Stock Exchange

Spatial Variations in Covariates on Marriage and Marital Fertility: Geographically Weighted Regression Analyses in Japan

Module Contact: Dr P Moffatt, ECO Copyright of the University of East Anglia Version 2

Labor Market Transitions in Peru

Method of Payment and Target Status: Announcement Returns to Acquiring Firms in the Malaysian Market

Tests for Two Ordered Categorical Variables

Basket options and implied correlations: a closed form approach

Spurious Seasonal Patterns and Excess Smoothness in the BLS Local Area Unemployment Statistics

Research Paper 347 March Capturing the Impact of Latent Industry-Wide Shocks with Dynamic Panel Model

Risk and Return: The Security Markets Line

The Determinants of International Portfolio Holdings and Home Bias

Prospect Theory and Asset Prices

Do not Fear the Fear Index: Evidence from US, UK and European Markets

Elements of Economic Analysis II Lecture VI: Industry Supply

The Initial Going-concern of Delisting Firms: An Application of Proportional Hazard Model

SPATIAL ANALISIS OF EFFECT OF GOVERNMENT EXPENDITURES ON ECONOMIC GROWTH

Forecasting and Stress Testing Credit Card Default using Dynamic Models

Understanding price volatility in electricity markets

REFINITIV INDICES PRIVATE EQUITY BUYOUT INDEX METHODOLOGY

Stochastic ALM models - General Methodology

Statistical Inference for Risk-Adjusted Performance Measure. Miranda Lam

Clearing Notice SIX x-clear Ltd

FM303. CHAPTERS COVERED : CHAPTERS 5, 8 and 9. LEARNER GUIDE : UNITS 1, 2 and 3.1 to 3.3. DUE DATE : 3:00 p.m. 19 MARCH 2013

ASSET LIQUIDITY, STOCK LIQUIDITY, AND OWNERSHIP CONCENTRATION: EVIDENCE FROM THE ASE

Forecasts in Times of Crises

Testing Benjamin Graham s Net Current Asset Value Strategy in London

Competition in Hong Kong s banking industry

Analysis of Moody s Bottom Rung Firms

Risk, return and stock performance measures

The Effects of Industrial Structure Change on Economic Growth in China Based on LMDI Decomposition Approach

Forecasting and Stress Testing Credit Card Default using Dynamic Models

THE RELATIONSHIP BETWEEN AVERAGE ASSET CORRELATION AND DEFAULT PROBABILITY

Synergy Motivation and Target Ownership Structure: Effects on Takeover Performance

Networks in Finance and Marketing I

A Bootstrap Confidence Limit for Process Capability Indices

THE IMPORTANCE OF THE NUMBER OF DIFFERENT AGENTS IN A HETEROGENEOUS ASSET-PRICING MODEL WOUTER J. DEN HAAN

Testing the weak efficient market hypothesis using Bangladeshi panel data

Network Analytics in Finance

Labor Income and Predictable Stock Returns

Asset Pricing When Returns Are Nonnormal: Fama-French Factors vs. Higher-order Systematic Co-Moments*

occurrence of a larger storm than our culvert or bridge is barely capable of handling? (what is The main question is: What is the possibility of

Solutions to Odd-Numbered End-of-Chapter Exercises: Chapter 12

Using Conditional Heteroskedastic

Understanding Predictability (JPE, 2004)

Risk and Returns of Commercial Real Estate: A Property Level Analysis

Price and Quantity Competition Revisited. Abstract

Price Formation on Agricultural Land Markets A Microstructure Analysis

Analysis of the Relationship between Managers Compensation and Earnings in Companies Listed in the Tehran Stock Exchange

/ Computational Genomics. Normalization

Creating a zero coupon curve by bootstrapping with cubic splines.

Financial crisis and exchange rates in emerging economies: An empirical analysis using PPP- UIP-Framework

CAPM for Estimating the Cost of Equity Capital: Interpreting the Empirical Evidence 1

Macroeconomic Uncertainty and Expected Stock Returns

NYSE Specialists Participation in the Posted Quotes

A survey on the relationship between ownership structure and dividend policy in Tehran stock exchange

THE MARKET PORTFOLIO MAY BE MEAN-VARIANCE EFFICIENT AFTER ALL

Corporate Governance and Equity Liquidity: An Analysis of S&P Transparency and Disclosure Ranking

Firm fundamentals, short selling, and stock returns. Abstract

arxiv: v1 [q-fin.pm] 13 Feb 2018

Supplementary Material to Cash Flow, Consumption Risk, and the Cross-Section of Stock Returns

arxiv:cond-mat/ v1 [cond-mat.other] 28 Nov 2004

Measurement of Dynamic Portfolio VaR Based on Mixed Vine Copula Model

Competitive Conditions in the Turkish Non-Life Insurance Industry

Appendix - Normally Distributed Admissible Choices are Optimal

Chapter 6 Risk, Return, and the Capital Asset Pricing Model

TESTING THE RELATION BETWEEN RISK AND RETURNS USING CAPM AND APT: THE CASE OF ATHENS STOCK EXCHANGE (ASE) Abstract

Does Stock Return Predictability Imply Improved Asset Allocation and Performance? Evidence from the U.S. Stock Market ( )

Department of Economics Working Paper Series

Lecture Note 2 Time Value of Money

Transcription:

Edth Cowan Unversty Research Onlne ECU Publcatons Pre. 2011 2009 Condtonal beta captal asset prcng model (CAPM) and duraton dependence tests Davd E. Allen Edth Cowan Unversty Imbarne Bujang Edth Cowan Unversty Ths artcle was orgnally publshed as: Allen, D. E., & Bujang, I. (2009). Condtonal beta captal asset prcng model (CAPM) and duraton dependence tests. Proceedngs of MODSIM 09. (pp. 1107-1112). Carns. Modellng and Smulaton Socety of Australa and New Zealand and Internatonal Assocaton for Mathematcs and Computers n Smulaton. Orgnal artcle avalable here Ths Conference Proceedng s posted at Research Onlne. http://ro.ecu.edu.au/ecuworks/230

18 th World IMACS / MODSIM Congress, Cans, Australa 13-17 July 2009 http//mssanz.org.au/modsm09 Condtonal Beta Captal Asset Prcng Model (CAPM) and Duraton Dependence Tests Davd E. Allen and Imbarne Bujang School of Accountng, Fnance and Economc Edth Cowan Unversty, Western Australa Emal :bujang@student.ecu.edu.au Abstract Ths paper uses a sample of 50 companes contnuously lsted on Man Board of Bursa Malaysa from January 1994 untl December 2001 and uses duraton dependence tests whlst applyng two asset prcng models based on the CAPM; the two Factor Model developed by Fama and French (F&F)(1998) and Ferson, Sarkssan and Smn s (FSS) (2008) condtonal beta model appled to estmate the condtonal beta of CAPM as to generate the postve and negatve abnormal returns. The fndngs suggest that both the Log Logstc and Webull hazard models seem to support the exstence of negatve duraton dependence for both postve and negatve runs of abnormal returns, consstent wth the presence of bubbles theory as predcted by McQueen and Thorley (1994). The negatve runs of abnormal returns for both the F&F and FSS models show that more than 80% of the sample seems to support the exstence of negatve duraton dependence usng both hazard models. Meanwhle the postve runs show that not more than 80% of the sample rejects the null hypothess based on LR tests of the absence of duraton dependence. Ths study also compare whether the estmaton of the run lengths of postve and negatve abnormal returns for both F&F and FSS models are sgnfcantly dfferent. The results suggest that the number of runs for both models by F&F and FSS are sgnfcantly dfferent. Keywords: Duraton dependence, Two Factor Models, ratonal bubbles, Log Logstc and Webull Hazard Models 1107

Allen, D.E., and I. Bujang, Condtonal Beta Captal Asset Prcng Model (CAPM) and Duraton Dependence Tests 1. Introducton The ssue of whether stock markets are ratonal s a central one. (In ths paper, the concern s whether the Malaysan stock market s ratonal?). One way of approachng ths ssue s by means of the concept of ratonal bubbles. Bubbles can be defned as the phenomena of stock prces movng consstently away from fundamental values. A recent study conducted by Chan, McQueen and Thorley (1998) used the ratonal bubble concept to assess whether the US market as represented by the Standard and Poor 500 Index, s ratonal through a technque called a duraton dependence test. However, they found that there s no duraton dependence n ths market. Harman and Zuehlke (2004) dsagreed and asserted that there s sgnfcant duraton dependence evdent n runs of both postve and negatve abnormal returns that are nconsstent wth the model of ratonal bubbles as proposed by McQueen and Thorley (1994). Watanapalachakul and Islam (2007) also nvestgated the exstence of ratonal bubbles n the Tha stock market. Smlar to Chan et al. (1998), they employed the duraton dependence test but they used two hazard models namely () the Log-Logstc and () the Webull Hazard Model. In addton, they also analysed ratonal bubbles usng annual data. Ths s n contrast to the prevous studes (McQueen and Thorley, 1994; Chan et al., 1998), whch used one-short perod of analyss. Based on ther study, Watanapalachakul and Islam (2007) contended that t was easer to detect the exact sze of bubbles n each partcular year usng a yearly based analyss. In another study conducted by Harman and Zuehlke (2004) further support was provded for Watanapalachakul and Islam (2007). They employed the generalzed Welbull hazard model on value weghted portfolos of NYSE stocks from 1927 through 1997. Ths model provdes much more flexblty whch allows changes n the drecton of duraton dependence. Ther fndngs suggest that duraton dependence s not monotonc. Bascally, the dea s of duraton elastcty beng ntally postve. However, the sgn can be negatve as the duraton of the run of abnormal returns ncreases. The presence of sgnfcant duraton dependence n runs of negatve abnormal return returns s nconsstent wth McQueen and Thorley (1994). McQueen and Thorley (1994) suggested that the duraton dependence pattern s ndcatve of the exstence of bubbles snce t cannot be the result of asymmetrc or leptokurtc nnovatons n fundamentals alone. Though a study by Harman and Zuehlke (2004) agreed wth Mudholkar, Srvasta, and Kolla (1996) who reported negatve duraton over much of the range of data they examned, and t s evdence n support of both postve and negatve runs of abnormal returns. Another study conducted by Harman and Zuehlke (2004) appled the duraton dependence test to both equally weghted and value weghed portfolos of NYSE traded securtes and found that both portfolos produced evdence of negatve and postve duraton dependence, whch once agan was not supported by the model proposed by McQueen and Thorley (1994). One potental explanaton for ths s a falure of the assumpton of market effcency. The ntal research on the exstence of ratonal bubbles n equty securtes on the Malaysan stock market was conducted by Chan et al. (1998), usng monthly and weekly Kuala Lumpur Composte Index returns from January 1977 through Aprl 1994 employng duraton dependence tests usng a Log-Logstc Hazard Model. They found that there was no evdence of the exstence of ratonal bubbles n the Malaysan stock market between the years 1977 untl 1999. However, n ths paper, the focus wll be on a sample of Man Board companes from the Kuala Lumpur Stock Exchange (Bursa Malaysa). The performance of the South East Asan economes has been relatvely erratc throughout the 1990s and untl 2007, most sgnfcantly durng the 1997 Asan fnancal crss. Do ratonal bubbles n the equty premum exst n the Malaysan stock market? The present study attempts to detect ratonal bubbles n the equty premum usng Duraton Dependence Tests. In these tests two models are employed: (1) the Log Logstc Hazard Model and (2) the Webull Hazard Model. There are a few relevant papers publshed about the Malaysan stock market, and n one of the latest papers, publshed by Mokhtar at. el. (2006), t was revealed that bubbles dd not exst durng the economc crss of 1997. However, the detecton of ratonal bubbles n ths study lmts ther analyss to a study of sectoral ndces data rather than ndvdual stocks, as opposed to the use of ndvdual stocks that we adopt for 1108

Allen, D.E., and I. Bujang, Condtonal Beta Captal Asset Prcng Model (CAPM) and Duraton Dependence Tests forecastng the equty premum. Furthermore, ths s the frst study of Malaysan data to employ a condtonal beta verson of CAPM. We apply two models whch are; (1) the two Factor model developed by Fama and French (1998) and an asset prcng model wth tme varyng coeffcents as developed by Ferson, Sarkssan and Smn (2008) to estmate the abnormal returns and utlse them n duraton dependence tests. Ths paper contans 4 sectons whch nclude an ntroducton, a data and methodology secton, an explanaton of the estmaton of the hazard model and a further secton presentng the results followed by a concludng secton. 2. Data and Methodology We adopt the Duraton dependence test usng the Log Logstc Hazard Model and Webull Hazard Model that are more wdely accepted (Fung 2001; Harman and Zuehlke 2004), because of ther robustness n testng for ratonal bubbles. Furthermore, both hazard models are chosen because of ther flexblty n applyng the hazard rate dstrbuton. The paper uses monthly aggregate returns on the Malaysan Stock Exchange for the perod 1994 to 2001 and collected the data for dvdend prce ratos and dvdend yelds from Professor Kenneth French s personal webste (data for Malaysa). These wll be analysed usng regressons applyng the two factor model of Fama & French (1998) and a tme varyng coeffcent model by Ferson, Sarkssan and Smn (2008). These models are used to assess the relatonshp between the equty premum and dvdend yelds. The dvdend yeld has been chosen as an ndependent varable as the ntal regresson result shows sgnfcantly ablty to explan the equty premum. The model can be llustrated as follows: The two Factor Model By Fama and French (1998) R t - R ft = α + β 0 (Rm Rf) + β 1 (HB- LB /M) t + u t ( 1 ) β* = β 0 + β 1 (HB- LB /M) t Where, HB and LB are defned as hgh and low book value to market value respectvely. Asset Prcng Tme Varyng coeffcents model by Ferson, Sarkssan and Smn (FSS) (2008) R t = α 0 + α 1 Z t-1 + β 0 (Rm t ) + β 1 (Rm t Z t-1 ) + u t ( 2 ) β*= β 0 + β 1 (Z t-1 ) Where the Zt-1 s the lagged predctor varable. For the purposes of ths paper, one month lagged dvdend yelds are used to estmate condtonal betas. The regresson models are used to forecast aggregate returns (the equty premum) and to measure realsed excess returns. These excess returns are then subjected to duraton dependence tests based on hazard models and the Log Logstc and Webull dstrbutons. The FF model and FSS model assume that the both the two factor and condtonal CAPM mply that α 0 =0 and α 1 =0. Where, f the model holds, then E(u t )=E(u t [R m -R f ) t ])=0 and E(u t ) = E(u t [Rm t Z t-1 ])=0 respectvely. Once the betas have been estmated, then equaton (1 and 2) are used to calculate the forecast stock returns and can then be appled to dentfy abnormal returns for both posttve and negatve seres for the duraton dependence tests. Thus the sample perod adopted for ths paper s shown n table 1: Table 1: Perod of Estmatng coeffcent and forecast for duraton Dependence Test Model Benchmark Total Perod Estmaton perod Forecast Perod Two Factor Model * (Model 1) Fama and French (1998) Condtonal beta Based on Asset prcng Tme varyng* (Model2) Ferson, Sarkssan &Smn (2008) 50 companes of Man Board KLSE January 1994 untl January 1994 untl November 1997 December 1997 untl 50 companes of Man Board KLSE January 1994 untl January 1994 untl November 1997 December 1997 untl 1109

Allen, D.E., and I. Bujang, Condtonal Beta Captal Asset Prcng Model (CAPM) and Duraton Dependence Tests Usng the LR test, both versons of the CAPM models (F&F and FSS) are tested based on the followng hypothess: H 0 : H 1 : There s no ratonal bubble. Excess returns do not exst. There s no duraton dependence; there s a constant hazard rate. There are ratonal bubbles. Excess returns do exst. There s postve or negatve duraton dependence; there are decreasng or ncreasng hazard rates. 3. Log Logstc and Webull Hazards Model The Log Logstc Hazard Model s defned as estmated by McQueen and Thorley (1994) and Harman and Zuehlke (2004): N ln L(, β ) = { J ln[ g( t )] + ( 1 J ) ln[ 1 G( t )]} = 1 α (3) where α s the shape parameter of the lognormal dstrbuton, β s the duraton elastcty of the hazard functon, J s a duraton of the process or tme to ext from a state, g s the dscrete functon for duraton, and G s the correspondng dstrbuton functon. The dscrete densty and dstrbuton functons for duraton are related as: t ( ) g( k) G t = = k 1 (4) However, f the law of condtonal probablty s appled (Harman and Zuehlke, 2004), the densty for completed duraton s: k 1 ( k) = h( k) [ h( m) ] 1 m= 0 g (5) For postve nteger k, where h(0) s defned as zero. In addton, McQueen and Thorley (1994) used the logstc dstrbuton functon ψ evaluated at a lnear transformaton of log duraton as: h(k) = ψ [α + β ln (k)] = {1+ exp [-α -β ln (k)]} -1 (6) The Webull hazard Model (Mudholkar, Srvastava and Kola, 1996) s defned as S(t) = exp (-αt bt+1 ) (7) where S(t) s the probablty of survval n the data up to at least tme (t), The correspondng hazard functon s: h(t) = α (β + 1)t β (8) where α s the shape parameter of the Webull dstrbuton, and β s the duraton elastcty of the hazard functon. The fundamental assumpton of the Webull Hazard model s a lnear relatonshp between the log of the hazard functon and the log of duraton, where: ln [h(t)] = ln[α (β + 1] + β ln(t) (9) Further nformaton regardng Webull Hazard Model can be found n Harman and Zuehlke (2004). 1110

Allen, D.E., and I. Bujang, Condtonal Beta Captal Asset Prcng Model (CAPM) and Duraton Dependence Tests 4. Fndngs The man objectve of the paper s to llustrate whether the forecastng of returns usng CAPM as n the Fama and French (1998) model or the condtonal verson of the Ferson, Sarkssan and Smn model (2008) as a flter, are approprate n evaluatng the exstence of duraton dependence n the resultng excess returns on the Malaysan Stock Market. Based on the LR test for the absence of duraton dependence, there s evdence of negatve duraton dependence n Malaysa stock market for the perod for December 1997 untl. Table 2 presents a summary of number of companes that rejected the null hypothess of no duraton dependence n excess returns. Table 2 Results summary: percentage of sample of 50 companes to detect the exstence of duraton dependence Bubble Model Log Logstc Hazard Model Webull Hazard Model CAPM Model Fama and French Model Ferson, Sarkssan and Smn Fama and French Model Ferson, Sarkssan and (1997) (2006) (1997) Smn (2006) Abnormal Returns Postve Negatve Postve Negatve Postve Negatve Postve Negatve Number of Companes 35 41 38 43 36 42 40 45 reject null hypothess % of Sample reject null hypothess 70 82 76 86 72 84 80 90 Notes: H 0 = the null hypothess for the absence of duraton dependence Table 2 shows that n the case of negatve runs of abnormal returns for both the F&F and FSS model t seems more than 80% (82%, 86%, 84% and 90%) of the sample seem to support the exstence of negatve duraton dependence usng both hazard models. Meanwhle the postve runs suggest not more than 80% (70%, 76%, 72%% and 80%) of the sample reject the null hypothess at a 95% confdence level based on LR tests for the absence of duraton dependence whch ndcates that there s both negatve duraton dependence and postve runs of abnormal returns for the perod December 1997 untl October 2001(forecast perod). Therefore, based on ths analyss, there are postve and negatve runs of abnormal return prevalent for both hazard models. 1 Table 3 Pared Sample t-test on the number of postve, negatve and total runs of abnormal returns for both the F&F Model and FSS Model Statstc Postve F&F Model Postve FSS Model Negatve F&F Model Negatve FSS Model Total F&F Model Total FSS Model Mean 13.66 12.42 13.72 12.66 27.38 25.08 Standard Devaton 1.184 2.081 1.819 2.309 3.568 3.948 Pared t- test 4.128 (0.0001)*** 3.409 (0.001)*** 4.195 (0.0001)*** Correlaton 0.412 (0.003)*** 0.453 (0.001)*** 0.472 (0.001)*** Notes: fgures n the parentheses are the t-statstcs and Correlaton p-values. * denotes sgnfcance at the 10% level, ** denotes sgnfcance at the 5% level and *** denotes sgnfcance at the 1% level. The purpose of table 3 s to compare whether the estmaton of the run lengths of postve and negatve abnormal returns for both F&F and FSS models are sgnfcantly dfferent. The results suggest that the number of runs for both models by F&F and FSS are sgnfcantly dfferent. The pared sample t-tests suggest sgnfcant dfferences n the means of runs of postve and negatve abnormal returns for all types of runs (Postve, negatve and Total ). Lastly, the analyss of the hazard rate dctates that the Log Logstc results suggest that the seres of abnormal return runs were decreasng whle the Webull Hazard rate found that the runs seres were decreasng then ncreasng. 1 Results for 50 companes Log Logstc and Webull hazards model are avalable upon request. 1111

Allen, D.E., and I. Bujang, Condtonal Beta Captal Asset Prcng Model (CAPM) and Duraton Dependence Tests 5. Concluson The tests for duraton dependence examne a partcular nonlnear form of return predctablty that s consstent wth the presence of bubbles allowng predctablty assocated wth tme varaton of the equty returns fltered through a prcng model. In ths paper two factor model developed by Fama and French (1998) and the condtonal model of Ferson, Sarkssan and Smn (2008) were used to generate return predctons that were then compared wth actual returns to derve excess returns. These were then subjected to duraton dependence tests. Both models suggest the exstence of duraton dependence n excess returns though tests on the means of the results of the two approaches suggest they are sgnfcantly dfferent. Ths paper featured novel tests of the mplcatons and estmaton of the run lengths of postve and negatve abnormal returns usng two models developed by F&F (1998) and FSS (2008). The overall results suggest that both postve and negatve runs show negatve duraton dependence as the LR test for absence of duraton dependence was rejected whch s consstent wth the evdence of McQueen and Thorley (1994). References Chan, K., McQueen, G., & Thorley, S. (1998). Are ratonal Speculatve bubbles n Asan Stock Market? Pacfc -Basn Fnance Journal, 6, 125. Fama, E. F. and K.R. French (1998). 'Value versus Growth: The Internatonal Evdence, Journal of Fnance, 53(6), 1975-1999. Ferson, W.E., Sarkssan, S., & Smn, T. (2008) 'Asset Prcng Models wth Condtonal Betas and Alphas: The Effects of Data Snoopng and Spurous Regresson', Journal of Fnancal and Quanttatve Analyss, 43(2), 331-353. Fung, L. 2001, Tme Seres Analyss of Ratonal Speculatve Bubble: A Smulaton Experment, Workng Paper, Department of Management, Brkbeck College, London. Harman, Y.S. & Zuehlke, T.W. (2004). 'Duraton Dependence Testng for Speculatve Bubbles', Journal of Economcs and Fnance, 28(2), 147-154. McQueen, G., & Thorley, S. (1994). Bubbles, Stock Returns and Duraton Dependence. Journal of Fnancal an Qualtatve Analyss, 29, 196-197. Mokhtar, S.H., Annuar, M.N., & Taufq, H. (2006). Detectng Ratonal Speculatve Bubbles n the Malaysan Stock Market. Internatonal Research Journal of Fnance and Economcs 6, 102-115. Mudhokar, G. S., Srvastava, D. K., & Kola, G. D. (1996). A Generalzaton of the Webull Dstrbuton wth applcaton to the Analyss of survval Data. Journal of the Amercan Statstcal Assocaton, 91, 1575-1583. Watanapalachakul, S. & Islam, S. M. N. (2007). 'Ratonal Speculatve Bubbles n the Tha Stock Market: Econometrc Tests and Implcatons', Revew of Pacfc Basn Fnancal Markets and Polces, 10(1), 1-13. 1112