icici 12 12

Date Open Price (in Rs.) High Price (in Rs.) Low Price (in Rs.) Last Traded Price (in Rs.) Close Price (in Rs.) Total Traded Quantity (in Rs.) Turnover (in Rs.)

1-Oct-12 1060 1060.9 1046 1053.5 1050.65 2161848 2273452000

28-Sep-12 1063 1073.6 1053.85 1062 1058.8 4152852 4422678000

27-Sep-12 1069 1072 1051.65 1053.25 1055.35 4693251 4976806000

26-Sep-12 1062.65 1071.1 1053.7 1064.4 1065.5 3015167 3203897000

25-Sep-12 1074.7 1081.25 1063.85 1067.85 1066.9 3732705 3993341000

24-Sep-12 1065.5 1086.9 1058.55 1070.5 1070.95 4806754 5161382000

21-Sep-12 1030 1086.25 1029.6 1066.55 1065.5 5932945 6319296000

20-Sep-12 1031 1041.9 1019.35 1021.25 1022.55 3070333 3162738000

18-Sep-12 1049.95 1056 1041.35 1049.65 1049.05 2860612 3000853000

17-Sep-12 1030 1069.7 1030 1058.85 1060.65 7767639 8179900000

14-Sep-12 987.75 1055.4 985.1 1005 1008 8251013 8328908000

13-Sep-12 955.8 965 955 959 959.45 3668211 3518751000

12-Sep-12 950.9 959.8 941.5 949.3 949.1 3246995 3088588000

11-Sep-12 930.6 949.9 928 947 945.8 2364984 2219723000

10-Sep-12 942.65 945.9 925.45 932 934.3 2421574 2259844000

8-Sep-12 939.9 943.95 938.35 942.95 941 254413 239286000

7-Sep-12 917.85 941 917 937.5 937.85 4723355 4401679000

6-Sep-12 891 902.4 886.05 896.6 896.45 2793538 2495604000

5-Sep-12 906.6 909.3 876.65 880 879.65 6081210 5398105000

4-Sep-12 902.8 914.8 892.5 914.75 912.65 2568220 2319718000

3-Sep-12 905.2 915.8 895.65 901.85 902.8 2494202 2256584000

31-Aug-12 915.55 922.6 895.05 903 902.15 3541523 3213820000

30-Aug-12 912.7 942.75 905 925.75 919.95 5543970 5075277000

29-Aug-12 925.25 931.85 914.3 914.65 916.4 2536659 2336684000

28-Aug-12 937 939.7 918.6 921.1 922.35 3467428 3212702000

27-Aug-12 957.8 957.8 932.5 935.15 935.25 2525729 2378390000

24-Aug-12 968.9 971.5 952.2 953.75 954.35 2634504 2524552000

23-Aug-12 977.35 988.9 969.05 972.8 973.85 4113639 4024787000

22-Aug-12 968.2 982.7 966.8 974.3 973.85 2159525 2102611000

21-Aug-12 966 979 958.65 978.5 975.2 2083236 2016614000

17-Aug-12 957.7 969 952.25 961.6 962.15 2954026 2844563000

16-Aug-12 971.4 975.8 953.05 957.5 956.4 2653273 2561796000

14-Aug-12 952.2 973.45 950.1 971 969.8 2356084 2273906000

13-Aug-12 951 954.5 936.2 950.5 948.95 3605178 3406061000

10-Aug-12 957 961.7 935 957.5 954.75 4404557 4177223000


9-Aug-12 964.1 974 948.85 954.4 952.65 3666571 3524991000

8-Aug-12 978 980 956.05 957.9 958.25 3433726 3315194000

7-Aug-12 960 976.95 954.55 972.5 974.3 3903345 3784208000

6-Aug-12 952.45 960 950.2 954.3 954 3425041 3269712000

3-Aug-12 950 952 932.5 938.95 939.95 3655721 3436137000

2-Aug-12 957.9 963.5 954.05 960 958.9 2455189 2353942000

1-Aug-12 952 965 952 956.75 959.6 3086481 2960666000

31-Jul-12 971.5 973.25 950.5 960.95 961.4 5877510 5649157000

30-Jul-12 943 969.6 943 963.35 964.5 7388947 7106727000

27-Jul-12 932 948.9 922.05 930.45 928.25 7069793 6606392000

26-Jul-12 923.95 925 901 911.45 906.75 6308737 5767523000

25-Jul-12 915.9 922.4 907.35 919.1 917.95 2102695 1923944000

24-Jul-12 914 921.75 910 917 916.35 2036996 1869399000

23-Jul-12 929 929.7 909.6 913.5 913 3205981 2941372000

20-Jul-12 955.5 957 932.2 935.05 935.15 3550699 3336100000

19-Jul-12 947 956.9 945.55 950.75 950.85 3131459 2979991000

18-Jul-12 923.15 942 923.15 938.7 939.2 3517782 3282042000

17-Jul-12 928.8 932 918.4 921.05 922.9 2245644 2079687000

16-Jul-12 930 935 916.95 917.5 920.1 2172859 2015986000

13-Jul-12 929.9 936.5 923.25 925.55 926.05 2162883 2012114000

12-Jul-12 928.5 935 922.1 925.5 927.85 3207519 2977911000

11-Jul-12 936 940 930.5 935.95 936.55 3642298 3408111000

10-Jul-12 935 945 931.4 942.8 942.9 4681039 4401393000

9-Jul-12 929.5 942.8 924.1 930 930 4801462 4479840000

6-Jul-12 920.85 938 911.4 936 935.1 5090413 4716234000

5-Jul-12 901.85 923.9 894 922.25 920.85 3747357 3419423000

4-Jul-12 909 912.3 896.45 899.25 902.8 3565284 3220097000

3-Jul-12 899.9 910.85 898 899 901.6 3186840 2887578000

2-Jul-12 901 904 884.1 891.5 894.4 4684247 4182110000

29-Jun-12 870 904.95 870 889.45 899.5 4776815 4251579000

28-Jun-12 860.1 870 852.5 854.9 856.95 3967471 3402863000

27-Jun-12 850.05 862.35 849.3 850 852.5 2980070 2550067000

26-Jun-12 842.5 850.7 838.35 846 844.1 2225774 1880680000

25-Jun-12 855.9 870.7 843 843.9 846.9 3137980 2702737000

22-Jun-12 838.95 854 833 852.8 851.7 3008778 2539540000

21-Jun-12 832 854 827.8 850 849.65 3552483 2992747000

20-Jun-12 829.25 839.4 826.8 834 833 2308908 1924481000

19-Jun-12 813 829.3 808 827 826.8 3065365 2513625000

18-Jun-12 858 864.2 810.2 819.45 816.55 4866246 4032584000

15-Jun-12 823.6 855.55 823.15 841.7 845.7 3968080 3345122000

14-Jun-12 847 849 816 816.6 818.85 3549689 2946013000

13-Jun-12 838.7 857.7 835.15 849.4 849.35 4672227 3956107000

12-Jun-12 816.75 841.5 815.05 837.7 839.05 3252044 2706750000

11-Jun-12 838.6 848.5 823 825.05 826.75 3282784 2751681000

8-Jun-12 835.7 835.7 813 830.35 829.15 3425638 2813419000

7-Jun-12 818 837.5 815 837 830.05 4551601 3749388000

6-Jun-12 797 810.75 796.4 808.5 808.4 5121312 4119471000

5-Jun-12 796.7 803.5 787.2 792 792.05 3700081 2946128000

4-Jun-12 769.95 794.9 767.4 792.9 788.85 3598258 2810828000

1-Jun-12 784 795.8 778.9 781.45 781.7 4030963 3170554000

31-May-12 798.75 798.75 781 785.4 783.25 7258671 5705062000

30-May-12 833.9 837.45 813.1 815.5 817.25 3309512 2735258000

29-May-12 837.5 843.95 834 839.5 838.7 2595349 2179411000

28-May-12 817.15 836.6 817 835.95 834.4 2744949 2276851000

25-May-12 818 824.4 805.25 816.7 814.6 3489464 2843535000

24-May-12 801 826 791.8 820.85 820.6 3076915 2484354000


23-May-12 793 804.85 790.2 791.45 793.3 2656987 2118093000

22-May-12 820.05 824.85 798.4 799.9 800.8 4181621 3406687000

21-May-12 797.1 818.8 797.1 808.5 811.1 3120508 2531291000

18-May-12 770.15 810 768.35 809.2 805.2 4433011 3493450000

17-May-12 797.9 806.8 780.6 785.5 787.45 3260903 2586406000

16-May-12 799 802.15 780 796.55 794.4 4669137 3692918000

15-May-12 794.2 821.5 791 818 816.85 3488933 2832022000

14-May-12 815 829.9 796.1 797.1 800.7 4695108 3798420000

11-May-12 809 823 803.6 812.95 813.2 2851045 2315200000

10-May-12 824 836.5 806.55 820.2 814.15 3726052 3068974000

9-May-12 822 828 810.05 822.3 821.95 5163648 4230721000

8-May-12 851.5 854 826 827.55 830.15 3923490 3299113000

7-May-12 819.75 854 797 850.2 848.25 6596861 5417275000

4-May-12 850.25 853.15 815.25 831.3 833.35 5525767 4607466000

3-May-12 875.1 879.7 851.05 861 857.55 4688549 4034872000

2-May-12 885.8 895 876.8 877 882.05 3864474 3430878000

30-Apr-12 870.5 889 870.5 882.3 882.35 5264315 4640278000

28-Apr-12 864.9 871 864.05 870.7 868.75 450887 391402000

27-Apr-12 845.5 875 841.05 860.4 860.85 14658969 12612774000

26-Apr-12 840.15 845.65 835.5 843.55 841.45 4378334 3681217000

25-Apr-12 845.05 855.5 827.25 839.95 838.4 5316160 4452304000

24-Apr-12 850 853.45 838.3 852.8 847.8 3247663 2746659000

23-Apr-12 850 868.5 836.1 837 843.9 3261817 2785292000

20-Apr-12 873 879 855.5 859.1 861.05 2909247 2522432000


19-Apr-12 882 883.65 866.2 880 877.85 2915224 2547172000

18-Apr-12 893.05 898.9 876.8 878 881.25 3464234 3086370000

17-Apr-12 881 892.95 852.5 886.1 885.45 7214244 6340169000

16-Apr-12 858.15 876.45 858.15 875 873.6 3638741 3170231000

13-Apr-12 885 900.8 850.5 862.4 865 4415153 3881386000

12-Apr-12 871.15 884.9 870.1 877.5 879.35 3166756 2783648000

11-Apr-12 855.1 875 851 867.95 864.7 5876793 5065380000

10-Apr-12 870.85 874.6 855.05 863.8 863.8 3737743 3227519000

9-Apr-12 877.35 878.3 863.75 867.75 867.05 2084814 1814999000

4-Apr-12 899 900.85 880.4 892.15 890.25 2710841 2411828000

3-Apr-12 901 918.8 898 909 908.2 3216592 2924219000

2-Apr-12 887.8 893.25 881.05 888 890.45 2000263 1777166000

30-Mar-12 864 894.2 863.05 887 890.2 5896714 5206691000

29-Mar-12 851 870.35 847.15 862.2 855.75 8410108 7204474000

28-Mar-12 874.75 874.75 852.7 858 859.35 6752823 5823502000

27-Mar-12 887 888.35 852 883 877.9 8277621 7194344000

26-Mar-12 903.7 905 866.1 874 872.5 3935999 3460294000

23-Mar-12 906.8 923.4 897.1 914.65 910.55 3408332 3100336000

22-Mar-12 936.05 939.8 893.1 895.95 899.65 3637804 3343709000

21-Mar-12 902.1 939.8 897.25 938.25 934.05 3540711 3259901000

20-Mar-12 909.75 922 900.05 905 908.6 2734449 2491568000

19-Mar-12 927 930.55 895.1 911 907.9 3157545 2872657000

16-Mar-12 936 953.9 910.45 915 917.7 4773792 4470007000

15-Mar-12 955 956.6 923.6 933 930.2 3189504 2983957000

14-Mar-12 946.8 957.6 944.65 954.8 953.9 5248382 4995540000

13-Mar-12 935.3 943.2 927.6 932.25 929.85 2798670 2616995000

12-Mar-12 944 944 919.05 928.15 928.95 5578910 5190087000

9-Mar-12 876.95 917.1 875.95 915.85 914.2 6051905 5467784000

7-Mar-12 851 867.9 843.45 861.45 860.15 6106939 5220126000

6-Mar-12 870 891 850 852.9 853.25 7898282 6874083000

5-Mar-12 896.8 896.8 868.55 871 870.35 4095006 3592539000

3-Mar-12 903.05 909.4 902.7 904.25 904.9 170619 154579000

2-Mar-12 891 914.75 875 901 902.7 4204021 3777426000

1-Mar-12 902.5 902.5 870.1 881 883.5 4161650 3668295000

29-Feb-12 915 921.95 897.35 905.5 906.3 4991052 4541511000

28-Feb-12 896 919.8 895.2 909.9 910.8 4932052 4492409000

27-Feb-12 932.4 932.4 881.7 888.95 887.45 4923294 4415335000

24-Feb-12 941.2 943.9 918.1 933.5 931.65 4389737 4074658000

23-Feb-12 952 959.1 932.1 944 943.95 5656901 5351290000

22-Feb-12 990 990 951.25 961.6 957.7 4774611 4632368000

21-Feb-12 977 998.8 976 990.05 991.3 3251673 3219072000

17-Feb-12 984.8 997.3 975.5 983 981.6 4343447 4278157000

16-Feb-12 981 981.9 961 970 968.8 3176454 3074360000

15-Feb-12 952.1 986.95 952.1 979.2 981.15 5608388 5447509000

14-Feb-12 927 950 926.7 948 943.7 3963195 3738097000

13-Feb-12 929 945.8 919 930.55 934.65 4862336 4534746000

10-Feb-12 933 939 916.3 928.2 930.45 3979616 3695541000

9-Feb-12 916.1 944.75 913.15 944.4 939.8 5764099 5337800000

8-Feb-12 927.9 929.85 911.1 918.4 920.45 22410138 20697768000


7-Feb-12 939.7 946.2 926 939.3 937.75 3983428 3732455000

6-Feb-12 925 936.85 919.3 926.2 928.05 5841145 5424182000

3-Feb-12 904 918.75 892.1 915.3 916.3 4939885 4471470000

2-Feb-12 899 911.8 879.25 901 902.35 8497255 7639368000

1-Feb-12 908 910.35 878 889 889.9 7967012 7078371000

31-Jan-12 859.75 906.85 858.95 901.65 902.15 10270953 9141072000

30-Jan-12 877 881.25 848 850.8 852.2 4388723 3772502000

27-Jan-12 888 890.5 864.15 889.95 887.95 4594831 4032771000

25-Jan-12 891.8 895 869.3 875.45 880.05 5656183 4973642000

24-Jan-12 860 895 847.05 883.85 888.05 8473587 7442382000

23-Jan-12 843 871.6 843 856 856.75 4588076 3945209000

20-Jan-12 814 851.6 814 847 842.45 9647998 8063636000

19-Jan-12 780.5 801.9 780.5 800 797.2 4393175 3478725000

18-Jan-12 779.8 781.95 762 764.6 769.65 4425870 3403447000

17-Jan-12 800 804.4 783.4 785 785.55 4321203 3429928000

16-Jan-12 782 796.4 777.3 794 791.6 5080475 4005867000

13-Jan-12 787.8 809.7 780.8 790 789.45 5996956 4757090000

12-Jan-12 779.9 796.8 774.1 783.5 781.4 5013352 3933432000

11-Jan-12 778.1 790 773.15 781.5 780.15 4961288 3882373000

10-Jan-12 750.7 779 750.05 774.4 774.5 4043643 3112737000

9-Jan-12 746 755 731 744 747.8 3337783 2482776000

7-Jan-12 748.5 748.5 742.85 744.85 745.2 260405 194195000

6-Jan-12 742 763 728 754.2 751.7 4049806 3007228000

5-Jan-12 745 756.8 739 748.3 748.1 4218791 3158039000

4-Jan-12 733.4 749 730.4 741.75 743.1 5991317 4436393000

3-Jan-12 705 729 705 723 725.8 3363693 2418614000

2-Jan-12 690.15 699.5 685.1 696.25 696.55 2714114 1883203000

Arithmetic

Mean890.231 902.845 878.457 890.598 890.557 4288040.351 3817464859

S.D Values 73.62910882 73.02491953 72.96966161 72.40225315 72.3422924 2244451.433 2042293296

Median 899 909.3 879.25 892.15 896.45 3864474.000 3403447000

Max 1074.7 1086.9 1063.85 1070.5 1070.95 22410138 20697768000

Min 690.15 699.5 685.1 696.25 696.55 170619 154579000

Ist Quartile 839.55 853.725 827.025 840.825 841.95 3134719.5 2740958500

3rd Quartile 936.525 945.85 925.725 936.75 935.9 4927673 4444348500

Avg. Dev. 58.86611935 57.52482936 58.38661221 57.63667389 57.66062608 1411219.592 1281189822

Range 384.55 387.4 378.75 374.25 374.4 22239519 20543189000

Quartile Dev. 48.4875 46.0625 49.35 47.9625 46.975 896476.75 851695000

Coef. Of Var. 8.271 8.088 8.307 8.130 8.123 52.342 53.499

Coef. Of Q.D. 5.393 5.066 5.613 5.376 5.240 23.198 25.024

Coef. Of M.D. 6.612 6.372 6.646 6.472 6.475 32.911 33.561

Moment

Skewness 0.423 0.563 0.486 0.537 0.531 2.278 2.127

Open Price High Price Low Price Last Traded Price Close Price Total Traded Quantity Turnover (in Lakhs)

Open Price 1

High Price 0.988331119 1

Low Price 0.989874148 0.989999347 1

Last Traded Price 0.976817442 0.991200443 0.990945822 1

Close Price 0.977748978 0.992188479 0.991917101 0.999411999 1

Total Traded Quantity -0.028982348 0.01534966 -0.044279991 -0.001313062 -0.00156192 1

Turnover (in Lakhs) 0.114592885 0.160930482 0.101473091 0.143694997 0.143983113 0.987543941 1

SUMMARY OUTPUT

Regression Statistics

Multiple R 0.988331119

R Square 0.976798401

Adjusted R Square 0.976675641

Standard Error 11.15259532

Observations 191

ANOVA

df SS MS F Significance F

Regression 1 989693.49 989693.5 7956.990284 2.04E-156

Residual 189 23507.892 124.3804

Total 190 1013201.4

Coefficients Standard Error t Stat P-value Lower 95% Upper 95%Lower 95.0%Upper 95.0%

Intercept 30.22 9.8157875 3.078891 0.002387114 10.8591665 49.58431 10.85917 49.58431

X Variable 1 0.98 0.0109888 89.20196 2.04E-156 0.958544605 1.001897 0.958545 1.001897

Regression Equation of High Price on Open Price: y=0.98x+30.22

0

200

400

600

800

1000

1200

0 200 400 600 800 1000 1200

Hig

h P

rice

Open Price

High Price vs. Open Price

SUMMARY OUTPUT


Multiple R 0.988331

R Square 0.976798



Observations 191

ANOVA


Regression 1 1006138.2 1006138.2 7956.990284 2.04E-156

Residual 189 23898.498 126.44708

Total 190 1030036.7

CoefficientsStandard Error t Stat P-value Lower 95% Upper 95%Lower 95.0%Upper 95.0%

Intercept -9.461423 10.118786 -0.935035 0.350963197 -29.4216908 10.49884 -29.42169 10.49884

X Variable 1 0.996508 0.0111714 89.201963 2.04E-156 0.974471722 1.018545 0.974472 1.018545

Regression Equation of open price on high price: x=0.997y+-9.46

0

200

400

600

800

1000

1200

0 200 400 600 800 1000 1200

Op

en

Pri

ce (

x)

High Price (Y)

Open Price vs. High Price

SUMMARY OUTPUT


Multiple R 0.989874

R Square 0.979851

Adjusted R Square0.979744

Standard Error10.38525

Observations 191

ANOVA


Regression 1 991284.3 991284.3 9191.038 3.3E-162

Residual 189 20384.28 107.8534

Total 190 1011669


Intercept 5.132484 9.140417 0.561515 0.575112 -12.89786 23.16283 -12.89786 23.16283

X Variable 1 0.981009 0.010233 95.8699 3.3E-162 0.960824 1.001193 0.960824 1.001193

Regression Equation of Low Price on Open Price: y=0.98x+5.13

0

200

400

600

800

1000

1200

0 200 400 600 800 1000 1200

Low

Pri

ce

Open Price

Low Price vs. Open Price

SUMMARY OUTPUT


Multiple R 0.989874

R Square 0.979851



Observations 191

ANOVA


Regression 1 1009282 1009282 9191.038 3.3E-162

Residual 189 20754.39 109.8116

Total 190 1030037


Intercept 12.811 9.183554 1.394993 0.164655 -5.30444 30.92643 -5.30444 30.92643

X Variable 1 0.99882 0.010418 95.8699 3.3E-162 0.978268 1.019371 0.978268 1.019371

Regression Equation of Open Price (x) on Low Price (y): x=0.999y+12.81

0

200

400

600

800

1000

1200

0 200 400 600 800 1000 1200

Op

en

Pri

ce (

x)

Low Price (y)

Open Price Vs. Low Price

SUMMARY OUTPUT


Multiple R 0.976817

R Square 0.954172



Observations 191

ANOVA


Regression 1 950352.2 950352.2 3935.145 1.8E-128

Residual 189 45644.21 241.5037

Total 190 995996.4


Intercept 35.49459 13.67764 2.595081 0.010199 8.514143 62.47503 8.514143 62.47503

X Variable 1 0.960541 0.015312 62.73073 1.8E-128 0.930336 0.990746 0.930336 0.990746

Regression Equation of LTP on Open : y=0.96x+35.49

0

200

400

600

800

1000

1200

0 200 400 600 800 1000 1200

Last

Tra

din

g P

rice

Open Price

Last Trading Price Vs. Open Price

SUMMARY OUTPUT


Multiple R 0.976817

R Square 0.954172



Observations 191

ANOVA


Regression 1 982832.5 982832.5 3935.145 1.8E-128

Residual 189 47204.2 249.7577

Total 190 1030037


Intercept 5.538002 14.14931 0.391397 0.695945 -22.37287 33.44887 -22.37287 33.44887

X Variable 1 0.99337 0.015835 62.73073 1.8E-128 0.962133 1.024607 0.962133 1.024607

Regression Equation of Open Price (x) on LTP(y) x=0.993y+5.54

0

200

400

600

800

1000

1200

0 200 400 600 800 1000 1200

Op

en

Pri

ce (

x)

Last Traded Price (y)

Open Price Vs. Last Traded Price

SUMMARY OUTPUT


Multiple R 0.977749

R Square 0.955993



Observations 191

ANOVA


Regression 1 950589.2 950589.2 4105.777 3.9E-130

Residual 189 43758.18 231.5248

Total 190 994347.4


Intercept 35.34634 13.39208 2.639347 0.009 8.929193 61.76348 8.929193 61.76348

X Variable 1 0.960661 0.014992 64.07634 3.9E-130 0.931087 0.990235 0.931087 0.990235

Regression Equation of Close Price on Open Price y=0.96x+35.35

0

200

400

600

800

1000

1200

0 200 400 600 800 1000 1200

Clo

se P

rice

Open Price

Close Price vs. Open Price

SUMMARY OUTPUT


Multiple R 0.977749

R Square 0.955993



Observations 191

ANOVA


Regression 1 984707.9 984707.9 4105.777 3.9E-130

Residual 189 45328.76 239.8347

Total 190 1030037


Intercept 4.001765 13.87616 0.288391 0.773363 -23.37028 31.37381 -23.37028 31.37381

X Variable 1 0.995141 0.015531 64.07634 3.9E-130 0.964506 1.025777 0.964506 1.025777

Regression Equation of Open Price (x) on Close Price (y) x=0.995y+4

0

200

400

600

800

1000

1200

0 200 400 600 800 1000 1200

Op

en

Pri

ce (

x)

Close Price (y)

Open Price Vs. Close Price

SUMMARY OUTPUT


Multiple R 0.989999

R Square 0.980099



Observations 191

ANOVA


Regression 1 991535.08 991535.1 9307.870564 1.0274E-162

Residual 189 20133.513 106.5265

Total 190 1011668.6


Intercept -14.68283 9.2875871 -1.580909 0.115570966 -33.00347548 3.637821 -33.00348 3.637821

X Variable 1 0.98925 0.0102537 96.47731 1.0274E-162 0.9690238 1.009477 0.969024 1.009477

Regression Equation of Low Price on High Price y=0.99x-14.68

0

200

400

600

800

1000

1200

0 200 400 600 800 1000 1200

Low

Pri

ce

High Price

Low Price Vs. High Price

SUMMARY OUTPUT


Multiple R 0.989999

R Square 0.980099



Observations 191

ANOVA


Regression 1 993037.4 993037.4 9307.871 1E-162

Residual 189 20164.02 106.6879

Total 190 1013201


Intercept 32.51479 9.051997 3.592001 0.000418 14.65886 50.37071 14.65886 50.37071

X Variable 1 0.990749 0.010269 96.47731 1E-162 0.970492 1.011006 0.970492 1.011006

Regression Equation of High Price (x) on Low Price (y) x=0.991y+32.51

0

200

400

600

800

1000

1200

0 200 400 600 800 1000 1200

Hig

h P

rice

(x)

Low Price (y)

High Price Vs. Low Price

SUMMARY OUTPUT


Multiple R 0.9912

R Square 0.982478



Observations 191

ANOVA


Regression 1 978544.9 978544.9 10597.64 6.1E-168

Residual 189 17451.53 92.33615

Total 190 995996.4


Intercept 3.328388 8.646889 0.384923 0.700727 -13.7284 20.3852 -13.7284 20.3852

X Variable 1 0.982749 0.009546 102.9448 6.1E-168 0.963918 1.00158 0.963918 1.00158

Regression Equation of LTP on High Price y=0.98x+3.33

0

200

400

600

800

1000

1200

0 200 400 600 800 1000 1200

Last

Tra

de

d P

rice

High Price

LTP vs. High Price

SUMMARY OUTPUT


Multiple R 0.9912

R Square 0.982478



Observations 191

ANOVA


Regression 1 995448.4 995448.4 10597.64 6.1E-168

Residual 189 17752.99 93.93118

Total 190 1013201


Intercept 12.4919 8.677225 1.439619 0.15163 -4.62476 29.60855 -4.62476 29.60855

X Variable 1 0.999725 0.009711 102.9448 6.1E-168 0.980568 1.018881 0.980568 1.018881

Regression Equation of High Price(x) on LTP(y) x=0.9997y+12.49

0

200

400

600

800

1000

1200

0 200 400 600 800 1000 1200

Hig

h P

rice

Last Traded Price

High Price vs. Last Traded Price

SUMMARY OUTPUT


Multiple R 0.992188

R Square 0.984438



Observations 191

ANOVA


Regression 1 978873.3 978873.3 11955.95 8.3E-173

Residual 189 15474.06 81.87332

Total 190 994347.4


Intercept 3.137863 8.142265 0.38538 0.70039 -12.92353 19.19925 -12.92353 19.19925

X Variable 1 0.982914 0.008989 109.3433 8.3E-173 0.965181 1.000646 0.965181 1.000646

Regression Equation of Close Price on High Price y=0.98x+3.14

0

200

400

600

800

1000

1200

0 200 400 600 800 1000 1200

Clo

se P

rice

High Price

Close Price Vs. High Price

SUMMARY OUTPUT


Multiple R 0.992188

R Square 0.984438



Observations 191

ANOVA


Regression 1 997433.9 997433.9 11955.95 8.3E-173

Residual 189 15767.46 83.42573

Total 190 1013201


Intercept 10.90737 8.183956 1.332775 0.18421 -5.236262 27.051 -5.236262 27.051

X Variable 1 1.001551 0.00916 109.3433 8.3E-173 0.983482 1.019619 0.983482 1.019619

Regression Equation of High Price (x) on Close Price (y): x=1.0016y+10.91

0

200

400

600

800

1000

1200

0 200 400 600 800 1000 1200

Hig

h P

rice

(x)

Close Price (y)

High Price vs. Close Price

SUMMARY OUTPUT


Multiple R 0.990946

R Square 0.981974



Observations 191

ANOVA


Regression 1 978042.2 978042.2 10295.64 8.9E-167

Residual 189 17954.21 94.99581

Total 190 995996.4


Intercept 26.86406 8.541595 3.145087 0.001929 10.01495 43.71317 10.01495 43.71317

X Variable 1 0.98324 0.00969 101.4674 8.9E-167 0.964125 1.002355 0.964125 1.002355

Regression Equation of LTP on Low Price y=0.98x+26.86

0

200

400

600

800

1000

1200

0 200 400 600 800 1000 1200

Last

Tra

de

d P

rice

Low Price

LTP vs. Low Price

SUMMARY OUTPUT


Multiple R 0.990946

R Square 0.981974



Observations 191

ANOVA


Regression 1 993431.9 993431.9 10295.64 8.9E-167

Residual 189 18236.72 96.49058

Total 190 1011669


Intercept -10.9941 8.794648 -1.25008 0.212814 -28.3423 6.354227 -28.3423 6.354227

X Variable 1 0.998712 0.009843 101.4674 8.9E-167 0.979296 1.018127 0.979296 1.018127

Regression Equation of Low Price (x) on LTP (y) x=0.999y-10.99

0

200

400

600

800

1000

1200

0 200 400 600 800 1000 1200

Low

Pri

ce (

x)

Last Traded Price (y)

Low Price Vs. Last Traded Price

SUMMARY OUTPUT


Multiple R 0.991917

R Square 0.9839



Observations 191

ANOVA


Regression 1 978337.9 978337.9 11549.79 2.1E-171

Residual 189 16009.45 84.70611

Total 190 994347.4


Intercept 26.69186 8.065739 3.309289 0.00112 10.78142 42.60229 10.78142 42.60229

X Variable 1 0.983389 0.00915 107.47 2.1E-171 0.965339 1.001439 0.965339 1.001439

Regression Equation of Close Price on Low Price y=0.98x+26.69

0

200

400

600

800

1000

1200

0 500 1000 1500

Clo

se P

rice

Low Price

Close Price Vs. Low Price

Close Price Vs. Low Price

SUMMARY OUTPUT


Multiple R 0.991917

R Square 0.9839



Observations 191

ANOVA


Regression 1 995380.3 995380.3 11549.79 2.1E-171

Residual 189 16288.33 86.18166

Total 190 1011669


Intercept -12.56215 8.318035 -1.51023 0.132655 -28.97026 3.845966 -28.97026 3.845966

X Variable 1 1.000519 0.00931 107.47 2.1E-171 0.982155 1.018884 0.982155 1.018884

Regression Equation of Low Price (x) on Close Price (y) x=1.001y-12.56

0

200

400

600

800

1000

1200

0 200 400 600 800 1000 1200

Low

Pri

ce (

x)

Close Price (y)

Low Price vs. Close Price

SUMMARY OUTPUT


Multiple R 0.999412

R Square 0.998824



Observations 191

ANOVA


Regression 1 993178.4 993178.4 160572.3 8E-279

Residual 189 1169.01 6.185241

Total 190 994347.4


Intercept 1.219175 2.226662 0.547535 0.584657 -3.17313 5.611478 -3.17313 5.611478

X Variable 1 0.998584 0.002492 400.7147 8E-279 0.993669 1.0035 0.993669 1.0035

Regression Equation of Close Price on Last Traded Price y=0.999x+1.22

0

200

400

600

800

1000

1200

0 200 400 600 800 1000 1200

Clo

se P

rice

Last Traded Price

Close Price vs. Last Traded Price

SUMMARY OUTPUT


Multiple R 0.999412

R Square 0.998824



Observations 191

ANOVA


Regression 1 994825.4 994825.4 160572.3085 8.0329E-279

Residual 189 1170.949 6.195498

Total 190 995996.4


Intercept -0.172431 2.230239 -0.077315 0.938454793 -4.571789268 4.226928 -4.571789 4.226928

X Variable 1 1.00024 0.002496 400.7147 8.0329E-279 0.995316485 1.005164 0.995316 1.005164

Regression Equation of LTP on Close Price x=1y-0.17

0

200

400

600

800

1000

1200

0 200 400 600 800 1000 1200

Last

Tra

de

d P

rice

(x)

Close Price (y)

Last Traded Price Vs. Close Price

SUMMARY OUTPUT


Multiple R 0.987544

R Square 0.975243



Observations 191

ANOVA


Regression 1 9.33E+14 9.33E+14 7445.216 9.4E-154

Residual 189 2.37E+13 1.25E+11

Total 190 9.57E+14


Intercept 144957.9 54423.68 2.663508 0.008401 37602.01 252313.8 37602.01 252313.8

X Variable 1 0.001085 1.26E-05 86.28566 9.4E-154 0.00106 0.00111 0.00106 0.00111

Regression Equation of Turn Over on Total Traded Quantity y=0.001x+144957.89

0

5E+09

1E+10

1.5E+10

2E+10

2.5E+10

0 5000000 10000000 15000000 20000000 25000000

Turn

ove

r

Total Traded Quantity

Turn over Vs. Total Traded Quantity

SUMMARY OUTPUT


Multiple R 0.987544

R Square 0.975243


Standard Error3.22E+08

Observations 191

ANOVA


Regression 1 7.73E+20 7.73E+20 7445.216 9.4E-154

Residual 189 1.96E+19 1.04E+17

Total 190 7.92E+20


Intercept -3.6E+07 50375514 -0.70966 0.478787 -1.4E+08 63620794 -1.4E+08 63620794

X Variable 1 898.5957 10.41419 86.28566 9.4E-154 878.0527 919.1387 878.0527 919.1387

Regression Equation of Total Traded Quantity (x) on Turnover (y) x=898.596y-35749694.91

0

5000000

10000000

15000000

20000000

25000000

0 1E+10 2E+10

Tota

l Tra

de

d Q

uan

tity

(x)

Turnover (y)

Total Traded Quantity vs. Turnover

icici 12 12

Documents

traded price

high price

low price

close price

dateopen price

date open price

total traded quantity