A Statistical Analysis of the Indian Stock Market. (Part II)
In continuation to our study we compare the values of R2 obtained by taking everyday data with the values obtained by considering only those dates which are just before the release of the quarterly reports of Infosys.
The data regarding the report release dates (henceforth referred to as RR) are also gathered from the BSE Ltd. Website http://www.bseindia.com/
We consider 3 sets of data for this analysis which are 3, 2 and 1 working day(s) before the RR. (referred to as RR-3, RR-2 and RR-1 respectively)
2.0 Analysis: Identifying Correlations in stock market data just before the report releases.
2.1 Data Selected for Study
- SENSEX value.
- Sectoral Index Value of the sector corresponding to the stock under consideration.
- Share Price (in Rs.) of the particular stock under consideration.
- High – Low (H – L) spread of the Share Price (in Rs.) in a day, of the particular stock under consideration.
- Close – Open (C – O) spread of the Share Price (in Rs.) in a day, of the particular stock under consideration.
Company chosen : INFOSYS (BSE Scrip Code: 500209)
Sectoral Index : BSE – IT
Period of Study : 1st April 2005 to 31st May 2010.
No of Report Releases during the period of study : 21
Total No. of Data points : RR - 3 : 63
RR - 2 : 42
RR - 1 : 21
2.2 Results of the Study :
Predictor Variables | INFOSYS | |||||||||||
Share Price | No of Shares traded | No of Trades | ||||||||||
normal | RR - 3 | RR - 2 | RR - 1 | normal | RR - 3 | RR - 2 | RR - 1 | normal | RR - 3 | RR - 2 | RR - 1 | |
BSE SENSEX | 0.90% | 1.72% | 1.72% | 1.50% | 0.21% | 0.38% | 0.05% | 3.21% | 0.00% | 0.02% | 0.00% | 0.55% |
BSE- IT | 13.90% | 13.04% | 13.25% | 14.37% | 0.62% | 1.35% | 0.34% | 0.10% | 0.07% | 3.24% | 2.93% | 6.52% |
Share Price | 2.30% | 3.86% | 2.41% | 1.77% | 2.40% | 0.17% | 0.17% | 0.33% | ||||
BSE SENSEX and BSE IT | 39.00% | 42.42% | 42.90% | 43.78% | 0.64% | 1.43% | 1.14% | 4.94% | 0.17% | 7.16% | 5.66% | 8.66% |
BSE- IT and Share Price | 2.40% | 4.09% | 2.41% | 2.55% | 2.60% | 3.31% | 2.99% | 6.70% | ||||
BSE SENSEX,BSE-IT and Share Price | 2.90% | 4.80% | 2.41% | 5.06% | 3.00% | 10.15% | 7.81% | 11.15% | ||||
Spread HL | 17.34% | 6.94% | 11.38% | 24.25% | 25.11% | 22.66% | 20.23% | 26.94% | ||||
Spread CO | 0.05% | 1.42% | 2.77% | 3.87% | 0.01% | 1.76% | 0.73% | 0.59% | ||||
Spread Hl and sp CO | 17.36% | 7.01% | 11.90% | 24.40% | 25.21% | 22.84% | 20.45% | 33.66% | ||||
SP and sp HL | 21.33% | 12.22% | 15.36% | 26.28% | 29.65% | 22.69% | 20.26% | 27.17% | ||||
SP and sp CO | 2.39% | 5.74% | 5.46% | 5.51% | 2.48% | 1.84% | 0.86% | 0.90% | ||||
SP, spHL and sp CO | 21.37% | 12.36% | 15.93% | 26.40% | 29.82% | 22.86% | 20.47% | 33.81% | ||||
ALL 5 factors | 24.13% | 14.27% | 18.24% | 31.05% | 34.36% | 42.76% | 42.57% | 59.78% |
2.3 Obsevations:
- There is a significant difference in the values of R2 for the everyday data and the data just before the RR.
- Some of the values are nearby to 50% and 1 value is almost 60%.
2.4 Conclusions:
- Variations when considering the data which are close to the RR are following a different trend compared to the whole data.
- The R2 value (in %) of the No of Trades on the day just before the report release which is almost 60% when we consider all the 5 predictor variables, may not be of much use in predictions as this is a lag indicator. (since the High – low spread and the close – open spread are available only at the end of the day).
- By analyzing the reason for these higher values of R2 we may be able to understand the trend followed by the market as a whole and the behavior of the particular stock under consideration on the days before reports of the company are released.
- We need to compare these values with other stocks from the same sector, for a better understanding of the trends.
- Since Infosys is one of the major stocks in the IT sector, we need to consider other stocks which will account for the rest of the stocks in the IT sector.
14 comments:
had to post the blog on the network site of my company whr im doin my intern.. and was not able to publish it directly so published here and did copy paste there..
by the way did u understand it?? :P
did not try to... :P
dont think i would if i did try...
The conclusions seems to be premature and only based on R^2. Do you think a high value of R^2 suggests a causal relationship? No statistical tests to know if the predictor variables are actually significant??...
umm its a totally technical thing...
but i have a qn...
how do u put graphs in a blog????
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