خلاصة:
این پژوهش، به بررسی اثر روزها و ماه های سال، متغیرهای کلان اقتصادی مانند GDP و تورم بر بازده سهام در بورس اوراق بهادار تهران می پردازد. در این تحقیق، همه ی شرکت های پذیرفته شده در بورس اوراق بهادار تهران، طی یک دوره ی 10 ساله از سال 1378- 1387- بررسی شده اند. از رگرسیون چند متغیره برای تشخیص ارتباط اثر متغیرهای کلان اقتصادی و از آزمون t استیودنت برای بررسی تاثیرات فصلی بر بازده سهام استفاده شده است. نتایج تحقیق نشان می دهد که بیش ترین بازده سهام در روزهای هفته متعلق به چهارشنبه ها و کم ترین بازده سهام متعلق به یکشنبه ها است. در رابطه با ماه های سال، بیش ترین بازده سهام، متعلق به شش ماه اول و کم ترین بازده، متعلق به شش ماه دوم سال (به ویژه اسفند ماه) است. در ضمن هیچ ارتباط معناداری، بین متغیرهای کلان اقتصادی و بازده فوق العاده فصلی وجود ندارد.
Introduction: Undoubtedly discovering trends in the market and earn returns is one of the important issues from the perspective of an investor. Discovering the hidden angles، is very attractive.
Abundant empirical evidence worldwide suggests that repeating patterns over time is possible. This efficient market concept and theories associated with it، is not compatible with the concept of performance based foundation of modern theories of financial market as the unpredictable behavior of the market has been long established.
There are exceptions to the financial markets that show deviations from the rules of logic and rational that is in violation of efficient markets. One of these exceptions، "seasonality or calendar anomalies"، is that certain patterns existing at different years، months، weeks and days will be approved. Irregularities include calendar، asymmetric distribution of returns in the days and months.
Research hypotheses
1. The stock returns in December are different from the stock returns in other months in Tehran stock Exchange.
2. The stock returns in April are different from the Stock returns in other months in Tehran stock Exchange.
3. The stock returns on Saturday are different from the Stock returns on other days in Tehran stock Exchange.
4. The stock returns on Wednesday are different from the Stock returns on other days in Tehran stock Exchange.
5. There is a significant relationship between GDP variations and extraordinary return of season.
6. There is a significant relationship between inflation and extraordinary return of season.
7. There is a significant relationship between annual stock returns and extraordinary return of season.
8. There is a significant relationship between extraordinary efficiency risk (deviation of stock returns) and extraordinary return of season.
Methodology: To evaluate the relationship between stock returns and the months of H0 and H1 hypothesis، we used:
H0: M1 = M2
H1: M1 ≠ M2
M1: The percentage of average daily stock returns in the month
M2: The percentage of average daily stock returns in the remaining months
To study the relationship between stock returns and days of a week and also the hypotheses H0، H1، we use:
H0: D1 = D2
H1: D1 ≠ D2
D1: The percentage of average daily stock returns of the desired day
[[
D2: The percentage of average daily stock returns in the rest of days a week
To evaluate the relationship between changes in GDP and inflation wonderful seasonal efficiency of multiple regressions، we use the following:
To evaluate the relationship between changes in GDP and inflation wonderful seasonal efficiency of multiple regressions in next year، we use the following:
Result
1. There is no January effect in Iran.
2. The stock returns in December are different from the stock returns in other months in Tehran stock Exchange.
3. The highest stock returns between days of a week for Iran as for European and American countries are on Wednesday.
4. The lowest stock returns between days of a week unlike European and American countries are on Sunday.
5. The highest Stock returns in seasons belong to summer and the lowest belong to the winter.
6. The highest stock returns belongs to the first half of the year and the lowest belong to the second half of the year.
7. There is no significant relationship between GDP variations and extraordinary return of season.
8. There is no significant relationship between inflation and extraordinary return of season.
9. There is no significant relationship between annual stock returns and extraordinary return of season.
10. There is no significant relationship between extraordinary efficiency risks (Deviation of stock returns) and extraordinary return of season.
Conclusion: Based on the results we find that Macro Variables of Economic does not effect season extraordinary return and we know some days and some months have extraordinary return that effect investors’ investing.
ملخص الجهاز:
"ﻣﺠﻠﻪی ﭘﻴﺸﺮﻓﺖﻫﺎی ﺣﺴﺎﺑﺪاری داﻧﺸﮕﺎه ﺷﻴﺮاز دورهی ﭼﻬﺎرم، ﺷﻤﺎرهی دوم، ﭘﺎﻳﻴﺰ و زﻣﺴﺘﺎن 1931، ﭘﻴﺎﭘﻲ 3/36، ﺻﻔﺤﻪﻫﺎی 1-62 )ﻣﺠﻠﻪی ﻋﻠﻮم اﺟﺘﻤﺎﻋﻲ و اﻧﺴﺎﻧﻲ ﭘﻴﺸﻴﻦ( ارﺗﺒﺎط روزﻫﺎ و ﻣﺎهﻫﺎی ﺳﺎل، ﻣﺘﻐﻴﺮﻫﺎی ﻛﻼن اﻗﺘﺼﺎدی و ﺑﺎزده ﺳﻬﺎم در ﺑﻮرس اوراق ﺑﻬﺎدار ﺗﻬﺮان ﻃﻴﺒﻪ ﻛﻮاروﻳﻲ دﻛﺘﺮ ﻣﻬﺪی ﺑﻬﺎرﻣﻘﺪم داﻧﺸﮕﺎه ﺷﻬﻴﺪ ﺑﺎﻫﻨﺮ ﻛﺮﻣﺎن ﭼﻜﻴﺪه اﻳﻦ ﭘﮋوﻫﺶ، ﺑﻪ ﺑﺮرﺳﻲ اﺛﺮ روزﻫـﺎ و ﻣـﺎهﻫـﺎی ﺳـﺎل، ﻣﺘﻐﻴﺮﻫـﺎی ﻛـﻼن اﻗﺘﺼﺎدی ﻣﺎﻧﻨﺪ GDPو ﺗﻮرم ﺑﺮ ﺑﺎزده ﺳـﻬﺎم در ﺑـﻮرس اوراق ﺑﻬـﺎدار ﺗﻬـﺮان ﻣﻲﭘﺮدازد.
ﺑﺮای ﺑﺮرﺳـﻲ راﺑﻄـﻪی ﺑﻴﻦ ﻣﺎهﻫـﺎی ﺳﺎل و ﺑــﺎزده ﺳﻬــﺎم از ﻓﺮﺿﻴــﻪﻫـﺎی 0 Hو1H اﺳﺘﻔـﺎده ﺷﺪه اﺳﺖ: 2H0: M1 = M 2H1: M1 ≠ M 1 :Mﻣﻴﺎﻧﮕﻴﻦ ﺑﺎزده روزاﻧﻪ ﺳﻬﺎم در ﻣﺎه ﻣﻮرد ﻧﻈﺮ ﺑﻪ درﺻﺪ 2 :Mﻣﻴﺎﻧﮕﻴﻦ ﺑﺎزده روزاﻧﻪ ﺳﻬﺎم در ﺑﻘﻴﻪی ﻣﺎهﻫﺎی ﺳﺎل ﺑﻪ درﺻﺪ ﺑﺮای ﺑﺮرﺳﻲ راﺑﻄـﻪی ﺑـﻴﻦ روزﻫـﺎی ﻫﻔﺘـﻪ و ﺑـﺎزده ﺳـﻬﺎم، از ﻓﺮﺿﻴــﻪﻫـﺎی 1H0, H اﺳﺘـﻔـﺎده ﻣﻲﺷﻮد: 2H0: D1 = D 2H1: D1 ≠ D 1 :Dﻣﻴﺎﻧﮕﻴﻦ ﺑﺎزده روزاﻧﻪ ﺳﻬﺎم در روز ﻣﻮرد ﻧﻈﺮ ﺑﻪ درﺻﺪ ﻣﺠﻠﻪ ﭘﻴﺸﺮﻓﺖﻫﺎی ﺣﺴﺎﺑﺪاری، دوره ﭼﻬﺎرم، ﺷﻤﺎره دوم، ﭘﺎﻳﻴﺰ و زﻣﺴﺘﺎن 1931 21 2 :Dﻣﻴﺎﻧﮕﻴﻦ ﺑﺎزده روزاﻧﻪ ﺳﻬﺎم در ﺑﻘﻴﻪی روزﻫﺎی ﻫﻔﺘﻪ ﺑﻪ درﺻﺪ ﺑﺮای ﺑﺮرﺳﻲ راﺑﻄﻪی ﺑﻴﻦ ﺗﻐﻴﻴﺮات GDPو ﺗﻮرم ﺑﺎ ﺑﺎزده ﻓﻮقاﻟﻌﺎده ﻓﺼﻠﻲ از رﮔﺮﺳﻴﻮن ﭼﻨﺪ ﻣﺘﻐﻴﺮه زﻳﺮ اﺳﺘﻔﺎده ﺷﺪه اﺳﺖ)ﮔﻮو، 3002 :104(: +Power Ratio= α +β1GDPGrowtht+ β2Inflationt+ β3Annual returnt 2β 4 σ t+ β 5 σ t )1( ﺑﺮای ﺑﺮرﺳﻲ راﺑﻄﻪی ﺑﻴﻦ ﺗﻐﻴﻴﺮات GDPﺑﺎ ﺑﺎزده ﻓﻮقاﻟﻌﺎده ﻓﺼﻠﻲ ﻣﻮرداﻧﺘﻈﺎر در ﺳـﺎل آﻳﻨﺪه از رﮔﺮﺳﻴﻮن ﭼﻨﺪ ﻣﺘﻐﻴﺮه زﻳﺮ اﺳﺘﻔﺎده ﺷﺪه اﺳﺖ)ﮔﻮو، 3002 :104(: 1+Power Ratio= α +β1GDPGrowtht+1+ β2Inflationt+1+ β3Annual returnt 1+2+ β4σt+1 + β5σt )2( : Power Ratioﺑﺎزده ﻓﻮقاﻟﻌﺎده ﻓﺼﻠﻲ :GDP Growthرﺷﺪ GDPدر ﺳﺎل ﻣﻮرد ﻧﻈﺮ :Inflationﻧﺮخ ﺗﻮرم در ﺳﺎل ﻣﻮرد ﻧﻈﺮ :Annual Returnﺗﻐﻴﻴﺮات ﺑﺎزده ﺳﺎﻻﻧﻪ : βб2t،βбtﺗﻐﻴﻴﺮات رﻳﺴﻚ )اﻧﺤﺮاف ﺑﺎزده ﺳﻬﺎم( ارﺗﺒﺎط روزﻫﺎ و ﻣﺎهﻫﺎی ﺳﺎل، ﻣﺘﻐﻴﺮﻫﺎی ﻛﻼن اﻗﺘﺼﺎدی و ﺑﺎزده ﺳﻬﺎم در ...
ﺑﺎ ﺗﻮﺟﻪ ﺑﻪ ﺳﻄﺢ ﻣﻌﻨـﺎداری در ﻫـﺮ ﭼﻬـﺎر ﻓﺼـﻞ ﺗﻔـﺎوت ﻣﻌﻨﺎداری ﺑﻴﻦ ﻓﺼﻮل و ﺑﻘﻴﻪی ﻣﺎهﻫﺎی ﺳﺎل دﻳﺪه ﻣﻲﺷﻮد؛ اﻣﺎ ﺑﻴﺶﺗﺮﻳﻦ ﻣﻴﺎﻧﮕﻴﻦ ﺑﺎزده روزاﻧﻪ ﻣﺠﻠﻪ ﭘﻴﺸﺮﻓﺖﻫﺎی ﺣﺴﺎﺑﺪاری، دوره ﭼﻬﺎرم، ﺷﻤﺎره دوم، ﭘﺎﻳﻴﺰ و زﻣﺴﺘﺎن 1931 61 ﺳﻬﺎم ﻣﺘﻌﻠﻖ ﺑﻪ ﺳﻪ ﻣﺎﻫﻪی دوم )112/0 درﺻﺪ( و ﻛﻢﺗﺮﻳﻦ ﻣﻴﺎﻧﮕﻴﻦ ﺑﺎزده روزاﻧﻪ ﺳﻬﺎم ﻣﺘﻌﻠﻖ ﺑﻪ ﺳﻪ ﻣﺎﻫﻪی ﭼﻬﺎرم )110/0درﺻﺪ( ﻫﺴﺘﻨﺪ."