Journal of Finance and Invesmen Analysis, vol. 1, no. 4, 2012, 53-65 ISSN: 2241-0998 (prin version), 2241-0996(online) Scienpress Ld, 2012 Marke Timing wih GEYR in Emerging Sock Marke: The Evidence from Sock Exchange of Thailand Nopphon Tangjiprom 1 Absrac This paper aims o examine wheher he marke iming sraegy wih Gil-Equiy Yield Raio or GEYR can creae abnormal reurns in Thai Sock marke. The rading rules using GEYR are esablished and swiching sraegies beween bonds and equiies are implemened. The ou-of-sample profiabiliy of hese swiching sraegies compared wih he simple buy-and-hold sraegy. The resul shows ha swiching sraegies using GEYR can provide higher reurn bu lower risk han buy-and-hold equiy porfolio, even afer he ransacions coss are considered. Alhough hese swiching sraegies canno be fully uilized in some ypes of funds because here are some resricions under invesmen policies, he resul reveals ha swiching porfolios can sill be more efficien han buy-and-hold porfolios. JEL classificaion numbers: G11 Keywords: Trading Sraegies, Markeing Timing, Equiies, Gil-Equiy Yield 1 Inroducion Efficien marke hypohesis proposes ha all available informaion should be refleced in he sock price. Therefore, any invesor canno bea he marke wih public informaion. One of popular acive rading sraegies is marke iming, 1 Marin de Tours School of Managemen and Economics, Assumpion Universiy, Bangkok, Thailand, e-mail: nopphon@gmail.com Aricle Info: Received : July 27, 2012. Revised : Sepember 11, 2012. Published online : December 12, 2012
54 Nopphon Tangjiprom which invesors can bea he marke by making he posiion in he marke in he appropriae ime. The common sraegy o do so is o swich beween sock marke and bond marke. Generally speaking, an invesor would like o ake posiion in he sock marke when he performance is beer relaive o bond marke and swich o ake posiion in he bond marke when he performance of sock marke is worse. If i is successful, his swiching sraegy can ouperform he passive buy-and-hold sraegy. In his paper, he swiching sraegies will be signaled by Gil-Equiy Yield Raio. Three rading rules are implemened and ou-of-sample porfolio performance will be compared wih he simple buy-and-hold sraegy. The resul has revealed ha he performance of swiching porfolios is beer han equiy-only porfolios in mean-variance framework. In he oher word, he swiching porfolios are more efficien as hey can provide higher reurns whereas he variances are lower. The resuls in his paper suppor he usefulness of using Gil-Equiy Yield Raio o ime he equiy marke. The ouline of his paper is as followings; Secion 2 discusses Gil-Equiy Yield Raio in he lieraures, Secion 3 summarizes he empirical mehodologies including daa and how he rading rules are formed, Secion 4 repors he model esimaion and porfolio performance, Secion 5 presens is he conclusion of his research. 2 The lieraure on GEYR GEYR sands for Gil-Equiy Yield Raio. I is he raio beween he yield on governmen securiies (which is known as gil in UK marke) and he dividend yield on equiy securiies. As is fundamenal, lower GEYR means bond yield is relaively lower compared o equiy yield and i can signal he appropriae ime o purchase socks. Meanwhile, higher GEYR can be inerpreed in he oher hand and signal he iming o purchase bonds. Mill (1991) finds he co-inegraion among equiy price, dividends, and governmen bond yield. This long-run equilibrium can imply he usefulness of GEYR o predic he fuure reurn beween bond and equiy markes. Hoare Gove, well-known UK sock broker develops he rading rule for GEYR in UK sock marke and suggess ha GEYR less han 2 is he signal o buy equiy. If GEYR is greaer han 2.4, i is he signal o swich from equiy o governmen bond (Hoare Gove, 1991). Clare, Thomas, Wickens (1994) use ime-series forecasing of equiy reurn by informaion abou GEYR o creae he rading rule. If he forecased equiy reurn is greaer han bond yields, equiy securiies should be purchased. If he forecased equiy reurn is less, i is he signal o swich o governmen securiies. Based on he above rading rule, hey show ha he swiching sraegy can ouperform he buy-and-hold sraegy. Levin and Wrigh (1998) adjus he rading rule by including he effec of oher variables, which can help o capure ime-varying facors of GEYR, o forecas excess equiy reurn
Marke Timing wih GEYR in Thailand 55 over bond yields. The similar resul abou usefulness of GEYR is concluded. Brook and Persand (2001) proposed he forecass of GEYR using regime-swiching framework. They simplify he model ino high and low regime and use Markov swiching echnique and self-exciing hreshold auoregression o model regime swiching. Alhough using GEYR in regime swiching can yield he higher reurn han buy-and-hold porfolio, he profiabiliy disappears afer considering he ransacion cos incurred by frequen rading of swiching sraegy. 3 Empirical Mehodologies 3.1 Daa The daa abou equiy reurn is colleced from Sock Exchange of Thailand. SET50 index is used as he reference of equiy marke reurn because i is more possible o replicae he reurn from SET50 index e.g. invesing in index fund or exchange raded fund (ETF). One-year governmen bond yields are from Thai Bond Marke Associaion, which is he major bond dealer marke in Thailand. The daa is colleced based on monhly basis saring from January 2001 o December 2011. Gil-Equiy Yield Raio or GEYR is compued from he raio beween bond yields and dividend yields. Thereafer, he informaion abou GEYR is used o consruc differen rading rules represening swiching porfolio in order o compare he performance wih buy-and-hold equiy porfolio and buy-and-hold bond porfolio. Equiy reurn is compued based on SET50 Toal Reurn because i has included reurns from boh capial gains and dividends. The log-difference of index is used o ge coninuous compound reurn. According o he swiching sraegies are based on monhly basis, he reurn from bond markes will be measured by yields on one-monh reasury bills, which are also ransformed o coninuous compound reurn. 3.2 Trading Rules The firs rading rule has followed Clare, Thomas, and Wickens (1994). They menion ha informaion abou GEYR has incorporaed forecasabiliy of fuure equiy reurn. They use special from of disribued lag of GEYR o forecas fuure equiy reurn as follows. r GEYR o k 1 i GEYR i (1) i 1 Where r is coninuous compound equiy reurns and k is he number of lags of change in GEYR in he model. Akaike Informaion Crieria (AIC) is used o selec he opimal number of lags. The firs 60 observaions are used o esimae his forecasing model. Thereafer, he esimaed model will be used o forecas he
56 Nopphon Tangjiprom fuure equiy reurns ou-of-sample for he remaining 72 observaions. For example, he pas informaion abou GEYR and change in GEYR are used o predic he equiy reurn in he 1 s monh during ou-of-sample period. If he forecased equiy reurn is higher han he yield on one-monh reasury bills ha is known a he beginning of period, he rading rule will sugges o invesmen in equiy. If he forecased equiy reurn is lower han, he reasury bills should be invesed insead. This swiching sraegy is implemened hroughou he ou-of-sample 72 observaions. The second rading rule has adoped from Levin and Wrigh (1998). The excess reurns on equiy over yields on governmen bonds are esimaed. Then, ha excess reurn will be forecased by lagged change in GEYR and oher variables ha can make GERY change bu no due o mispricing. The model is as follows. r* GEYR TP DY Z (2) o 1 1 2 1 3 1 4 1 Where r * is he difference beween coninuous compound equiy reurns and yields on governmen bonds. TP is erm premiums, which are he difference beween en-year governmen bond yields and one-monh Treasury bill yields. DY is dividend premiums and Z is he ineracion beween equiy reurns and bond yields. Equaion 2 is esimaed based on he firs 60 observaions. The esimaed model is used o esimae excess reurn over ou-of-sample period. The prediced posiive excess reurns rigger equiy invesmen. Oherwise, he one-monh reasury bills will be invesed insead. The hird rading rule is based on regime-swiching by Markov swiching model. Markov swiching model is developed by Hamilon (1990), which can overcome he basic assumpion of ime series daa abou means and variance saionary. In Markov swiching, he whole ime series daa may no have consan mean and variance overime because he daa comes from differen regimes. However, he ransiions among differen regimes are no deerminisic bu sochasic. In his case, he univariae Markov swiching model for GEYR is as follows. GEYR where s 1,2 (3) s S deermines saes or regimes, which is assumed o be wo regimes in his case and ransiions beween wo regimes are sochasically deermined by he ransiion marix as follows. p11 p12 P (4) p21 p22 p 11 is he probabiliy ha here is no swiching from sae 1. p 21 is he ransiion probabiliy of swiching from sae 1 o 2. p 12 is he ransiion probabiliy of swiching from sae 2 o sae 1 and p 22 is he probabiliy of no swiching from sae 2. The Markov swiching model of GEYR is esimaed based on he procedure developed by Perlin (2010).
Marke Timing wih GEYR in Thailand 57 The rading rule of GEYR using Markov swiching models is proposed by Brook and Persand (2001). Based on heir paper, hey forecas he probabiliy of being in regime 1 in nex period based on he formula by Engel and Hamilon (1990) as follows. p, 1 p 1, 1 ( 1 p22) ( 1 p11 p22) p1, (5) 1 is forecased probabiliy of being in regime 1 in nex period given informaion in his period. p 1, is he filered probabiliy of being in regime 1 in las period of he model. Using he firs 60 observaions, he probabiliy in nex period is forecased. Suppose he regime 1 is high-geyr regime and he forecased probabiliy is more han 0.5, he rading rule suggess ha GEYR is sill on high regime and Treasury bills should be invesed. However, if he forecased probabiliy suggess ha GEYR is in low-geyr regime, i riggers swiching o equiy marke. Afer adding one more observaion, he model is re-esimaed and he probabiliy is forecased unil he las observaion. Thereafer, he porfolio reurn will be calculaed based on swiching sraegy following he above hree rading rules. The performances of swiching porfolio are compared wih buy-and-hold equiy-only porfolio and buy-and-hold bond-only porfolio. 4 Analysis and resuls Table 1 repors descripive saisics of GEYR. The mean of GEYR is 0.8708 wih he sandard deviaion of 0.4525. The disribuion of GEYR is no normal bu here are posiively-skewed and lepokuric. This is no surprising because he componens of GEYR are bond yields and dividend yields, which can be only posiive amoun. The Jacque-Bera es also confirms non-normaliy characerisics of boh GEYR and dividend yields. Equiy reurns are more symmeric wih slighly negaive skewness and lower excess kurosis. However, he normaliy assumpion of equiy reurn is sill rejeced. The ime series propery has revealed ha boh GEYR and equiy reurns series are saionary based on he rejeced of Augmened Dickey-Fuller es. Table 1: Descripive saisic of GEYR and equiy reurn GEYR Dividend Yield Equiy Reurn Mean 0.8708 3.4827 1.1228 Median 0.8300 3.5150 1.6045 Sandard Deviaion 0.4525 1.0330 8.5012 Skewness 1.5643 1.0645-0.2000 Excess Kurosis 3.3501 3.2294 1.6247
58 Nopphon Tangjiprom JB 127.1145** 52.2683** 15.2817** ADF -3.5730** -2.6701* -12.0971** ** Significan a 5%, * significan a 10% 4.1 Model esimaion The firs model is he modified disribue lag model in which pas informaion of GEYR and change in GEYR are used o forecas equiy reurns. Table 2 repors he resuls of hree esimaed models, which are model wih one lag of change in GEYR, model wih wo lags of change in GEYR and model wih hree lags of change in GEYR. F-ess reveal ha all hree models are significance as a whole. There is no problem abou heeroskedasiciy in hese models based on Whie general es of heeroskedasics. Moreover, auocorrelaion problem is no deeced based on Breusch-Godfrey serial correlaion LM es and Durbin-Wason saisics are around wo. Based on one-lag model, adding he second lag can provide only lile more explanaion power as adjused r-squared has only slighly increased. Furhermore, adding he hird lag resuls in lower adjused r-squared. Therefore, he one-lag model, which has lowes value of Akaike informaion crieria, is used for he firs rading rule. Consan GEYR(-1) ΔGEYR(-1) ΔGEYR(-2) ΔGEYR(-3) Table 2: The resul of esimaed model based on rading rule 1 Lag 1 Lag 2 Lag 3 2.6699 (1.2603) -0.9864 (-0.5045) 17.2509 (2.4233)** 2.7531 (1.2490) -1.2913 (-0.6196) 19.8784 (3.5957)** -6.8562 (-1.3113) 2.9579 (1.3076) -1.4422 (-0.6700) 21.5050 (3.0942)** -7.3071 (-1.2967) 3.2259 (0.6075) F-sa 6.241** 4.4514** 2.7286** Adjused R-squared 0.1553 0.1560 0.1117 AIC 6.9214 6.9411 6.9865 Whie 0.7066 1.4475 3.4186 DW 1.9687 2.2635 2.2336 BG (3) 4.6788 3.1557 3.7407 Noe: The numbers in parenhesis are -sa. Whie represens he LM-es saisic of Whie es of heeroskedasiciy wihou cross-erm. DW represens Durbin-Wason saisics. BG (3) represens
Marke Timing wih GEYR in Thailand 59 he es saisics of Breusch-Godfrey serial correlaion LM es a hree lags. ** Significan a 5%, * significan a 10% The second model uses lag of GEYR and oher variables o predic excess reurn on equiy over T-bills. Table 3 repors he resuls of esimaed models based on equaion 2. Boh model wih only lag GEYR and model wih GEYR and oher variables are saisically significan. The muliple-variable model is suffered from heeroskedasiciy and he -sa is re-esimaed based on robus sandard error. The significance of oher variables beside lag of change in GEYR suggess ha he muliple-variable model is he beer one. The higher adjused r-squared also confirms he superior of muliple-variable model. Consan ΔGEYR(-1) DY(-1) Z(-1) TP(-1) Table 3: The resul of esimaed model based on rading rule 2 Single variables 1.5408 (1.5508) 17.4649 (3.5002)** Muliple variables 25.4729 (3.1896)** 21.5229 (3.0944)** -4.0307 (-1.6013)* -0.3559 (-1.1221) -3.5491 (-3.8340)** F-sa 12.2513** 7.0983** Adjused R-squared 0.1649 0.2997 AIC 6.8965 6.7688 Whie 0.6343 19.6384** DW 2.2678 2.5245 BG (3) 3.2133 6.1353 Noe: The numbers in parenhesis are -sa. Whie represens he LM-es saisic of Whie es of heeroskedasiciy wihou cross-erm. DW represens Durbin-Wason saisics. BG (3) represens he es saisics of Breusch-Godfrey serial correlaion LM es a hree lags. The -sas in he muliple-variable model are esimaed based on robus sandard errors. ** Significan a 5%, * significan a 10% Table 4 repors he resul of Markov swiching model based on he whole sample of 132 observaions. Based on Brook and Persand (2001), he mean difference beween wo regimes and he high probabiliy of ρ 11 and ρ 22 sugges he sabiliy of wo regimes and regime-swiching model is appropriae.
60 Nopphon Tangjiprom Table 4: The resul of Markov swiching model (whole sample) for rading rule 3 Mean Variance 11 22 Regime 1 Regime 2 0.9769 (0.0423) 0.0692 (0.0425) Noe: The numbers in he parenhesis are he sandard error. 0.97 (0.11) 0.99 (0.17) 0.4660 (0.0248) 0.0151 (0.0049) 4.2 Porfolio performance The performances of swiching porfolio based on hree rading rules are compued in order o compare wih buy-and-hold equiy porfolio and buy-and-hold T-bills. Table 5 repors five-year ou-of-sample means and sandard deviaions of hose five porfolios. For buy-and-hold sraegies, T-bills provide he average annual reurn of 2.76% wih sandard deviaion only 0.36% whereas equiy marke has provided much higher annual reurn of 11.44% wih sandard deviaion of 29.45%. All swiching porfolios are more efficien han equiy-only porfolio as hey provide more reurns bu lower risks. The higher Sharpe raio and high posiive Jensen's Alpha confirm he superioriy of swiching sraegies. The hird swiching porfolio following regime-swiching has clearly shown lower number of swiching compared oher wo swiching porfolios. The esimaed roundrip ransacion cos of 0.83% based on commission fees and average bid-ask spreads from ick-size. The ne reurns afer deducing ransacion coss shows he similar resul as before. All performance measuremen has shown ha swiching sraegies can make more profi wih lower risk. Figure 1 shows he performance of five porfolios ploed on mean-variance framework. Based on he figure, i can be clearly seen ha swiching porfolios are superior o he curren efficien fronier on he combinaion of equiy and T-bill invesmens.
Marke Timing wih GEYR in Thailand 61 Figure 1: Mean-Variance Porfolios Buy-and-hold Equiy Buy-and-hold T-bills Swiching 1 Swiching 2 Swiching 3 Table 5: Ou-of-sample porfolio performance (2006-2011) Mean Reurn (%) Sandard Deviaion (%) Sharpe Raio 11.44 29.45 0.295 2.76 0.36 0.000 30.00 (28.82) 22.27 (20.82) 18.57 (17.25) 22.30 11.97 14.15 1.222 (1.169) 1.630 (1.509) 1.118 (1.025) Jensen's Alpha 21.844 (20.668) 17.912 (16.459) 13.687 (12.373) Noe: The numbers in he parenhesis are he reurns ne of ransacion coss. Number of swiching 15 15 8 In order o compare he performance of five porfolios more clearly, he annual reurns by year are shown in able 6. We can see ha he performance of equiy marke is abnormally negaive in 2008 a negaive 76.69%, which is he side effec from subprime crisis in US. In 2009, equiy marke shows he abnormal reurn as he resul of recovery from previous year. Alhough swiching sraegies can ouperform he equiy-only porfolio in many years, he major conribuion o heir
62 Nopphon Tangjiprom superior average reurns is from he abiliy o avoid or reduce loss in 2008. Swiching porfolios canno consisenly ouperform equiy porfolio in every year. Therefore, hese swiching sraegies can be more useful in long-erm invesmen horizon. Year Buy-and-hold T-bills Table 6: Porfolio reurn classified by year Buy-and-hold Equiy Swiching 1 Swiching 2 Swiching 3 2006 4.54 16.33 27.82 30.58 4.54 2007 3.50 20.19 32.77 38.55 3.50 2008 3.18-76.69-17.39 4.11 3.18 2009 1.20 66.04 66.04 1.20 59.59 2010 1.36 38.65 38.65 33.75 24.74 2011 2.77 4.13 32.11 25.42 15.86 Average 2.76 11.44 30.00 22.27 18.57 4.3 Invesmen resricion of muual funds in Thailand Based on he invesmen resricions of differen ypes of muual funds, he swiching sraegies menioned above are unable o be fully uilized. Flexible funds are he porfolio ha can freely inves in any proporion of equiy and fixed-income securiies. Therefore, flexible funds can fully uilize hese swiching sraegies. Equiy funds are he muual funds ha focus in invesing in equiy marke. They are regulaed o hold a leas 65% of equiy a anyime. I is possible o implemen swiching sraegies under resricion by holding all equiies during bull equiy marke and swiching o hold only 65% and inves 35% in T-bills. Balanced funds can hold he combinaion beween equiy and bond markes bu hey are regulaed o hold equiy wih he maximum proporion of 65% and minimum proporion of 35%. They can implemen swiching sraegy by holding maximum of 65% in equiy marke and 35% in bonds or holding minimum of 35% in equiy marke and 65% in bonds. Table 7 repors he reurns on porfolio under he above resricions for equiy funds and balanced funds. In panel A of able 7, we can see ha he reurns of swiching porfolios have reduced drasically for equiy funds. This is no surprising as he swiching sraegies lose heir advanages of loss-avoidance. However, he resuls sill show ha all swiching sraegies can provide reurns higher han equiy-only porfolios. Panel B of able 7 shows he performance of swiching porfolio assuming hey are balanced funds. The reurns have reduced even lower as swiching sraegies canno fully be uilized. They canno ake advanages of loss avoidance oally during bear equiy marke as hey sill need o hold equiies 35% whereas hey canno ake full advanages during bull equiy markes as hey can hold equiies up
Marke Timing wih GEYR in Thailand 63 o 65%. Two ou of hree swiching porfolios have shown ne reurns slighly lower han equiy-only porfolio. However, swiching porfolio can sill have advanages of lower risk. Figure 2 shows he performance of porfolio under he resricion of balanced funds in mean-variance framework. Even hough some swiching porfolio provided lower reurns, he advanages of lower risk make all of hem are more efficien han he combinaion of equiy and bond invesmens. Figure 2: Mean-Variance porfolios wih he resricion of balanced funds Table 7: Annual porfolio performance based on invesmen resricion Year Buy-and-hold T-bills Buy-and-hold Equiy Swiching 1 Swiching 2 Swiching 3 Panel A: Wih he resricion of invesing in equiies a leas 65% 2006 4.54 16.33 20.35 21.32 12.21 2007 3.50 20.19 24.60 26.62 14.35 2008 3.18-76.69-55.94-48.41-48.74 2009 1.20 66.04 66.04 43.34 63.78 2010 1.36 38.65 38.65 36.94 33.78 2011 2.77 4.13 13.92 11.58 8.23 Average 2.76 11.44 17.94 (16.90) 15.23 (14.19) Panel B: Wih he resricion of invesing in equiies a leas 35% bu no exceed 65% 13.94 (13.38)
64 Nopphon Tangjiprom 2006 4.54 16.33 15.65 16.48 8.67 2007 3.50 20.19 18.13 19.86 9.35 2008 3.18-76.69-30.95-24.50-24.78 2009 1.20 66.04 43.34 23.89 41.41 2010 1.36 38.65 25.60 24.13 21.43 2011 2.77 4.13 12.05 10.04 7.17 13.97 11.65 Average 2.76 11.44 (12.93) (10.61) Noe: The numbers in he parenhesis are he reurns ne of ransacion coss. 10.54 (9.99) 5 Conclusion This paper has examined wheher he informaion abou GEYR is useful o generae abnormal profis using swiching sraegies. Three rading rules have bee esimaed. The firs rading rule uses only pas informaion abou GEYR o predic he fuure equiy reurns. The second rading rule uses no only GEYR bu oher variables including erm premiums and dividend yields o predic he fuure excess reurn on equiy over T-bills. The hird rading rule employs Markov swiching o predic wheher he nex period GEYR should be in high or low regime. Afer model esimaions, ou-of-sample profiabiliy of hree rading rules is compued. The resuls have revealed ha swiching porfolios can ouperform buy-and-hold equiy-only porfolio, even afer he ransacion coss from swiching sraegies are included. However, he year-by-year resuls sugges ha swiching porfolios canno consisenly ouperform equiy-only porfolio. This can be concluded ha hese swiching sraegies are more useful for long-erm invesmen horizons. This paper has conribued o show he evidence of marke iming using GEYR. The informaion conained in GEYR is useful o predic he fuure equiy reurn and can be used o develop rading rules and creae swiching porfolios, which can ouperform buy-and-hold equiy-only porfolio. The abnormal profis from rading rules are no disappear even in long invesmen horizon like six-year in his paper. The possibiliy o do marke iming has raised he quesion abou equiy marke efficiency, especially in emerging marke like Thailand. ACKNOWLEDGEMENTS: I would like o express my very grea appreciaion o Ass. Prof. Dr Aida Charoenrook for her valuable and consrucive suggesions during he developmen of his research work.
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