Wavelet based sample entropy analysis: A new method to test weak form market efficiency
In this article, we analyze informational efficiency in daily returns of NASDAQ, DJIA and S&P 500 indices ranging from 04-01-1980 to 12-09-2013.We replace the traditional coarse graining method used in multi-scale entropy analysis by a Maximal Overlap Discreet Wavelet Transform decomposition and...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
General Association of Economists from Romania
2014-08-01
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| Series: | Theoretical and Applied Economics |
| Subjects: | |
| Online Access: |
http://store.ectap.ro/articole/1007.pdf
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| _version_ | 1811296874264526848 |
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| author | Anoop S. KUMAR B. KAMAIAH |
| author_facet | Anoop S. KUMAR B. KAMAIAH |
| author_sort | Anoop S. KUMAR |
| collection | DOAJ |
| description | In this article, we analyze informational efficiency in daily returns of
NASDAQ, DJIA and S&P 500 indices ranging from 04-01-1980 to 12-09-2013.We
replace the traditional coarse graining method used in multi-scale entropy analysis
by a Maximal Overlap Discreet Wavelet Transform decomposition and extract
Sample entropy measure across different timescales. To compare against efficient
market behavior, we simulate an i.i.d. normal series with the same mean and
variance of the underlying series and repeat the procedure. Next, we plot both of
these estimates to see how the values differ from each other across the scales. It
is found that the three markets under study are not weak form efficient at high to
medium frequencies (up to semi-annual period). They are informationally
efficient in the long run (annual-biannual period). Here, efficiency of a financial
market is closely related with the time horizons under which the agents operate.
As time horizon increases, the markets move towards an informationally efficient
state. It could be due to the fact that agents with a long investment horizon make
use of the information set available in a comparatively efficient manner due to
their comparatively high tolerance for price fluctuations as opposed to their
high-frequency counterparts. |
| first_indexed | 2024-04-13T05:56:02Z |
| format | Article |
| id | doaj.art-7f555a1c25214150a87df2a23b1e7dff |
| institution | Directory Open Access Journal |
| issn | 1841-8678 1844-0029 |
| language | English |
| last_indexed | 2024-04-13T05:56:02Z |
| publishDate | 2014-08-01 |
| publisher | General Association of Economists from Romania |
| record_format | Article |
| series | Theoretical and Applied Economics |
| spelling | doaj.art-7f555a1c25214150a87df2a23b1e7dff2022-12-22T02:59:38ZengGeneral Association of Economists from RomaniaTheoretical and Applied Economics1841-86781844-00292014-08-01XXI8172418418678Wavelet based sample entropy analysis: A new method to test weak form market efficiencyAnoop S. KUMAR0B. KAMAIAH1 University of Hyderabad, Hyderabad, India University of Hyderabad, Hyderabad, India In this article, we analyze informational efficiency in daily returns of NASDAQ, DJIA and S&P 500 indices ranging from 04-01-1980 to 12-09-2013.We replace the traditional coarse graining method used in multi-scale entropy analysis by a Maximal Overlap Discreet Wavelet Transform decomposition and extract Sample entropy measure across different timescales. To compare against efficient market behavior, we simulate an i.i.d. normal series with the same mean and variance of the underlying series and repeat the procedure. Next, we plot both of these estimates to see how the values differ from each other across the scales. It is found that the three markets under study are not weak form efficient at high to medium frequencies (up to semi-annual period). They are informationally efficient in the long run (annual-biannual period). Here, efficiency of a financial market is closely related with the time horizons under which the agents operate. As time horizon increases, the markets move towards an informationally efficient state. It could be due to the fact that agents with a long investment horizon make use of the information set available in a comparatively efficient manner due to their comparatively high tolerance for price fluctuations as opposed to their high-frequency counterparts. http://store.ectap.ro/articole/1007.pdf EMHefficiencytransfer entropywaveletsequity markets |
| spellingShingle | Anoop S. KUMAR B. KAMAIAH Wavelet based sample entropy analysis: A new method to test weak form market efficiency Theoretical and Applied Economics EMH efficiency transfer entropy wavelets equity markets |
| title | Wavelet based sample entropy analysis: A new method to test weak form market efficiency |
| title_full | Wavelet based sample entropy analysis: A new method to test weak form market efficiency |
| title_fullStr | Wavelet based sample entropy analysis: A new method to test weak form market efficiency |
| title_full_unstemmed | Wavelet based sample entropy analysis: A new method to test weak form market efficiency |
| title_short | Wavelet based sample entropy analysis: A new method to test weak form market efficiency |
| title_sort | wavelet based sample entropy analysis a new method to test weak form market efficiency |
| topic | EMH efficiency transfer entropy wavelets equity markets |
| url |
http://store.ectap.ro/articole/1007.pdf
|
| work_keys_str_mv | AT anoopskumar waveletbasedsampleentropyanalysisanewmethodtotestweakformmarketefficiency AT bkamaiah waveletbasedsampleentropyanalysisanewmethodtotestweakformmarketefficiency |