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Enstitüsü Dergisi 6 (2) 2016 s.1-14
(2) 2016 p.114 1Yrd. Doç. Dr. Ali ÖZER
aliozer@erzincan.edu.trYrd. Doç. Dr.
oece@erzincan.edu.tr.ÖZET
Ocak a
vadeli piyasalar incelemek için BIST-100 ait 2005 ve2 ARCH-GARCH
piyasa cuma veBIST-100 ,
C32, G10, G14
TESTING THE ANOMALIES AT FUTURES MARKETS WITH
ARCH-GARCH MODELS: A STUDY FOR THE TURKISH
FUTURES MARKETS
ABSTRACT
This study investigates the presence of calendar anomalies, which is a commencement of the behavioral finance and contradicts wit the Efficient Market Hypothesis, particularly january and day of-the-week anomalies at futures markets. In this study, to investigate the anomalies , 2143 daily data belonging to BIST-100 Index contract between 2005 and 2013 years, have been used. As a result of the study done by the ARCH-GARCH models, prove that the daily returns of BIST-100 Index contract in January do not show a statistically significant difference from other months. For the day-of-the-week anomalies, statistics indicate that BIST-100 futures contracts daily returns on Fridays and Wednesdays are positive, while returns on Mondays are negative. Keywords: Futures Markets, Anomaly, Arch-Garch. Jel Classification:C32, G10, G14
Enstitüsü Dergisi 6 (2) 2016 s.1-14
(2) 2016 p.114 2 1.G elde etmenin Bund nu bu sebeple bireysel olar li hipotez bir büt getirisinin -momentum stratejileri gibi etkiler yeni edilebilmektedir. ararlarda psikolojinin etkisini d unun analizler ve rasyonel davran beraberinde anomalileri getirmektedir.Enstitüsü Dergisi 6 (2) 2016 s.1-14
(2) 2016 p.114 3 dalgalanmalara sebep olmakt kullanomolilerin vadeli ip BIST 100 ne ait 2.143 adet getiri verisi e 2. 500cuma günleri ortalama getirinin Pazartesi günleri ortalama
French (1980) 1953-1977
bu bulguyu Bu etki literatürde hafta sonu etkisi olarak bilinmektedir.Smirlock ve Starks (1986) 1963 v
için, Chang vd. (1993) ve Kamara (1997) 1962 ve da bu sonucu destekler etkisi Solnik veBousquet (1990), lar
Jaffe ve Westerfield (1985), Dubois ve Louvet s s c , 2001 ve 2008 krizlerini inceleyen ki endeksler için pazartesi günü negatif getiri umaEnstitüsü Dergisi 6 (2) 2016 s.1-14
(2) 2016 p.114 4 inde en yüksek pMabberly ve Waggoner (2000),
Schwert
(2001),Steeley (2001),
Kohers vd. (2004) dünyadaki 12 büyük hisse senedi piy ve Hui (2005)Sullivan vd. (2001) geleneksel
e Sadorsky (2006),Demirer ve Karan
(2002), -1996 , Dyl (1977) 19 ve Brown vd. (1983) 1967 ve 1979 re dahaCooper vd.
(2006), 1940 ve 2003Gültekin ve Gültekin (1983)
Reinganum (1983) Ocak
sa fiyatlar iddia etmektedir.Leontitsis ve Siriopoulus (2006),
Lakonishok ve Smidt (1988),
Enstitüsü Dergisi 6 (2) 2016 s.1-14
(2) 2016 p.114 5Atakan (2008) l
delillere . Tunçel (2012), 2000-2010 g daKonak ve Kendirli (2014),
kullanarak rt T piyasalarLiteratür incelemesi sonucunda,
Türki
3.BIST-100 getirilerinden
hareketle toplam 2143 günlük veri irilerle (VOB) web s - www.vob.org.tr). tarihinde VOB- 8Enstitüsü Dergisi 6 (2) 2016 s.1-14
(2) 2016 p.114 6 y-FullerTablo 1: ADF
Sabitli Sabitli Trendli Sabitsiz Trendsiz Sabitli Sabitli Trendli Sabitsiz Trendsiz -1.39886 -2.034723 1.125852 -44.403* -44.3931* -44.387*Kritik
a=%1 -3.43320 -3.962329 -2.56604 -3.43320 -3.962331 -2.56604 b=%5 -2.86268 -3.411906 -1.94097 -2.86268 -3.411907 -1.94097 c=%1 -2.56742 -3.127851 -1.61660 -2.56742 -3.127851 -1.61660 Not: -trendsiz ve sabitli- tirilen her üç durumda da da 0 100200
300
400
500
600
-0.10-0.050.000.050.10
Series: VOB_100
Sample 2/04/2005 8/02/2013
Observations 2143
Mean 0.000457
Median 0.001031
Maximum 0.121272
Minimum -0.110638
Std. Dev. 0.018084
Skewness -0.311164
Kurtosis 6.518291
Jarque-Bera 1139.867
Probability 0.000000
Grafik 1: BIST-100
Enstitüsü Dergisi 6 (2) 2016 s.1-14
(2) 2016 p.114 7BIST-100 getiri serisinin
, çlu , simetrik sahiptir. Jarque H0: Normallikten sapma yoktur
Jarque-
-.15 -.10 -.05 .00 .05 .10 .1505 0607080910111213 Grafik 2: 2005-BIST-100 E Getirileri
Grafik 2 , BIST- endeks getirilerindeki
Logaritmik getirilerde
BIST-100
ikten sonra, BIST-100 getiri serisinde ARCH -LM testine vermektir. lerdeki ARMA modelleri denen rEnstitüsü Dergisi 6 (2) 2016 s.1-14
(2) 2016 p.114 8Ortalama denklemin
tespiti için 10. seviyeye kadar bütün Box Jenkins (ARIMA) modelleri lama gücüne sahip ARMA (1,1) modeli ortalamaARMA (1,1)
Tablo 2: BIST-100 En Küçük Kareler ARMA (1,1) Modeli c 0.001450 2.718954*AR(2) -0.274409 -13.19550*
MA(2) 0,289803 4935,882*
R2 0.0322
77.4479
0.0000
Durbin-Watson 2.00322
Not n olup/ tespiti için, hata terimlerine Breucsh-Pagan LM ve White testleriTablo 3:
Breusch-Pagan LM
LM(1) 5.26655**
LM(2) 2.45789
LM(3) 3.88752*
LM(4) 3.01457**
LM(6) 3.45879*
LM(12) 3.875427*
White Testi 22.41250 (0,00000)
, -LM testiTablo 4: ARCH-
176.4258 0.0000
Enstitüsü Dergisi 6 (2) 2016 s.1-14
(2) 2016 p.114 92 160.0124
4 Uygulamada volatilitenin tahmini için en çok ARCH(1), GARCH(1,1) modelleridir ve bu modeller ve GARCH modelleri (ARCH(2), GARCH(2,1), GARCH(2,2) gibi) 5t Tablo 5: BIST-l00 Getiri Serisi için Alternatif ARCH-GARCH ModelleriARCH(1) ARCH(2) ARCH(3) ARCH(4) ARCH(5) GARCH
(1,1) GARCH (1,2) c 0.001431 0.001478 0.001493 0.001486 0.001472 0.001431 0.0014301 0.21323* 0.192373* 0.139757* 0.124064* 0.123046* 0.124409* 0.122010*
2 0.239938* 0.196183* 0.133707* 0.126005*
3 0.242772* 0.205688* 0.197329*
4 0.135580* 0.133495*
5 0.047429*
1 0.841821* 0.870568*
2 -0.025975
3 R2 0.00159 0.002563 0.002763 0.002011 0.00090 0.001595 0.001587 F 18.5482* 24.9108* 26.21450* 30.21564* 32.46558* 8.21458* 9.60492* DW 1.963269 1.965473 1.972976 1.972184 1.975502 1.973269 1.973290 Akaik e -5.34320 -5.27503 -5.31808 -5.34172 -5.34578 -5.36320 -5.36227 Schwa rz -5.32318 -5.25915 -5.29954 -5.32054 -5.32195 -5.34731 -5.34374 Z tik 4.1914* 4.187903 4.44451* 4.41926* 2.84926* 4.19141* 4.44939* Tablo 5: BIST-l00 Getiri Serisi için Alternatif ARCH-GARCH Modelleri GARCH (1,3) GARCH (2,1) GARCH (2,2) GARCH (2,3) GARCH (3,1) GARCH (3,2) GARCH (3,3) c 0.001458 0.001430 0.001430 0.001347 0.001428 0.001405 0.0014091 0.12429* 0.121874* 0.121867* 0.118365* 0.121768* 0.11988* 0.09170*
2 0.0004069 -0.127069* 0.018499 -0.002954 -0.13257* -0.007288
3 0.02330 0.026330 0.07277*
4Enstitüsü Dergisi 6 (2) 2016 s.1-14
(2) 2016 p.114 10 51 1.61967* 0.839575* 1.784755* 0.785516* 0.838045* 1.45879* 1.53746*
2 -1.2818* -0.786684* -0.51676* -
0.64587*
1.48486*
3 0.54077* 0.589328* 0.74304*
R2 0.001879 0.001587 0.001587 0.0051 0.001574 0.001434 0.001481 F 3.54821* 8.716617* 13.4123 9.151918* 8.22574* 9.22681* 9.58471* DW 1.972494 1.973289 1.971159 1.970255 1.973424 1.973708 1.986037 Akaike -5.77432 -5.362275 -5.361341 -5.773976 -5.361344 -5.780367 -5.774578 Schwarz -5.76329 -5.343741 -5.340159 -5.761275 -5.340161 -5.770648 -5.753578 Z4.40873* 4.441203* 4.123035* 4.405894* 4.119162* 4.04238* 4.24390*
Tablo 5'te GARCH(1,2), GARCH(1,3), GARCH(2,2), GARCH(2,3), GACH(3,1), GARCH(3,2) ve GARCH(3,3) modelleri denklemdeki yerine getirmedikleri için uygun model olarak seçilemezler. Bu nedenle, BIST-100 günlük getirilerine uygun olan modelin seçimi -5.363202) GARCH (1,1) -5.347315) GARCH (1,1) modeli seçilmektedir. ARCH etkisinin bu modelde için tekrar ARCH-Tablo 6da
Tablo 6 GARCH (1-
2.604786 0.3345
Tablo 6da yer alan ARCH-1,1)
GARCH modelini tespit ettikten so tur; R t=0+ 1 D1 + 2 D2 + 3 D3 + 4 D4 + 5 D5 + 6 Rt-1t (1)Modelde D
12 aksi takdirde 0, D 34ise 1, aksi takdirde 0, D
5t-1;serinin bir
Rt= 1 Docak + 2 Rt-1t (2) Modelde D
ocakModellerden elde edilen sonuçlar
Enstitüsü Dergisi 6 (2) 2016 s.1-14
(2) 2016 p.114 11Tablo 7: Etkisine GARCH
(1,1) Model Z-Pazartesi -0,003742 -2.829457 0,0011
-0,000452 -0,475264 0,42590,014257 12,45796 0,0000
-0,0015647 -0,64893 0,1356Cuma 0,04061 16,4128 0,0000
Ocak 0,0001024 0,01597 0,4958
Bu sonuçlar, vadeli lem piyasalar için O
kararlar vermedikleri ve (anomalilerin) ol piyasalardan sapmalar olarO nin
piyasalar O ulan modellerde ise p getir uma günleri ise pozitifLiteratürde bir
Opiyasalar
piyasalarda etkinliktenEnstitüsü Dergisi 6 (2) 2016 s.1-14
(2) 2016 p.114 12 azaltmak için c vadeli piyasalarda pazartesi günü negatif getiriler elde edilquotesdbs_dbs14.pdfusesText_20[PDF] Kabel-Kontaktstifte
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