AEX Fear & Greed Index

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Index Data

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id Date GF Index Momentum Price Strength Price Breadth Put Call Ratio Volatility Safe Haven Demand Junk Bond Demand Close Price
$data['id'] 26-02-25 17:31 62 66.6667 78.564 55.5652 100 36.6644 50.5006 45.3847 932.09
$data['id'] 18-02-25 11:00 72 100 98.6187 52.9091 100 40.3479 49.495 61.1674 947.6
$data['id'] 17-02-25 11:00 72 100 99.7594 54.9091 100 40.8746 49.4952 61.1674 948.48
$data['id'] 14-02-25 11:00 73 100 100 59.1667 100 40.8895 49.4975 60.203 945.43
$data['id'] 13-02-25 11:00 70 83.3333 93.4896 59.0833 100 42.6821 49.4907 61.0042 945.96
$data['id'] 12-02-25 11:00 74 100 100 59.1304 100 45.9621 49.4922 60.0939 942.03
$data['id'] 11-02-25 11:00 69 66.6667 100 58.0909 100 46.7254 49.4937 60.0939 939.71
$data['id'] 10-02-25 11:00 69 66.6667 100 57.2727 100 46.1169 49.4899 63.0157 932.9
$data['id'] 07-02-25 11:00 68 66.6667 100 54.5833 100 47.3826 49.4858 59.1913 923.09
$data['id'] 06-02-25 11:00 69 66.6667 100 55 100 48.5833 49.4881 61.8766 925.76
$data['id'] 05-02-25 11:00 67 66.6667 89.1431 54.5455 100 50.0724 49.4852 60.6383 917.89
$data['id'] 04-02-25 11:00 67 66.6667 85.2769 54 100 50.1443 49.4853 60.6383 919.62
$data['id'] 03-02-25 11:00 66 66.6667 80.7322 55.1818 100 50.5901 49.4843 61.8073 915.32
$data['id'] 31-01-25 11:00 72 83.3333 100 57.1818 100 51.1015 49.4722 61.0009 921.89
$data['id'] 30-01-25 11:00 67 66.6667 88.4459 58.7826 100 46.0512 49.4782 61.0009 919.71
$data['id'] 29-01-25 11:00 66 66.6667 82.6434 57.9091 100 48.1051 49.4732 60.6709 905.43
$data['id'] 28-01-25 11:00 65 66.6667 73.5323 58.1 100 48.0604 49.4638 60.7642 899.28
$data['id'] 27-01-25 11:00 62 66.6667 49.5928 55.3333 100 50.626 49.4672 60.7642 894.37
$data['id'] 24-01-25 11:00 66 66.6667 83.1862 57.4286 100 45.8581 49.4561 60.8749 901.07
$data['id'] 23-01-25 11:00 66 66.6667 83.2711 58.381 100 46.4198 49.4524 59.9922 908.57
$data['id'] 22-01-25 11:00 71 83.3333 99.4061 61.1 100 44.7367 49.4617 61.486 914.08
$data['id'] 21-01-25 11:00 71 83.3333 100 60.8421 100 45.0408 49.4584 61.6619 914.93
$data['id'] 20-01-25 11:00 72 83.3333 100 60.9474 100 50.3499 49.4607 61.6619 917.81
$data['id'] 17-01-25 11:00 72 83.3333 100 56.7619 100 50.2482 49.4597 61.3659 914.72
$data['id'] 16-01-25 11:00 66 50 100 52.7 100 48.3538 49.4626 59.9098 906.43
$data['id'] 15-01-25 11:00 62 50 78.8395 51.8 100 44.2504 49.4533 59.9098 896.24
$data['id'] 14-01-25 11:00 64 50 85.1743 52.1053 100 44.9528 49.452 62.9595 884.47
$data['id'] 13-01-25 11:00 59 50 58.3977 48.5263 100 46.1428 49.4472 59.9601 885.61
$data['id'] 10-01-25 11:00 64 50 93.4362 50.1905 100 42.5987 49.449 62.1627 890.64
$data['id'] 09-01-25 11:00 62 50 79.7019 48.7619 100 40.9965 49.4474 62.1627 895.68
$data['id'] 08-01-25 11:00 62 50 82.6584 49.6 100 40.5664 49.4471 59.3804 888.99
$data['id'] 07-01-25 11:00 62 50 83.3291 50.2105 100 40.5103 49.4468 63.3859 894.17
$data['id'] 06-01-25 11:00 60 50 76.9193 48.1053 100 39.917 49.4476 58.5978 890.03
$data['id'] 03-01-25 11:00 60 50 71.4534 50 100 38.8433 49.4469 60.8141 884.59
$data['id'] 02-01-25 11:00 53 33.3333 43.5995 49.2381 100 35.8268 49.4406 62.72 886.47
$data['id'] 31-12-24 11:00 50 16.6667 35.4817 48.8 100 35.6941 49.4385 62.7138 878.63
$data['id'] 30-12-24 11:00 54 50 40.2096 48.1053 100 34.3144 49.4343 58.7467 872.17
$data['id'] 24-12-24 11:00 53 50 28.926 49.5455 100 33.921 49.4378 59.8911 876.26
$data['id'] 23-12-24 11:00 50 33.3333 21.2144 46.9524 100 33.521 49.4335 64.8588 872.35
$data['id'] 20-12-24 11:00 50 33.3333 19.2476 50.3478 100 35.4338 49.4323 59.5526 875.63
$data['id'] 19-12-24 11:00 55 50 37.7615 49.4783 100 36.7264 49.4231 59.0476 877.78
$data['id'] 18-12-24 11:00 57 50 52.763 49.7391 100 33.0138 49.4238 62.3068 892.32
$data['id'] 17-12-24 11:00 54 50 49.797 49.6364 100 33.9717 49.4223 47.0471 889.21
$data['id'] 16-12-24 11:00 50 50 51.1396 49.9048 64.5723 34.8691 49.4211 47.0471 890.98
$data['id'] 13-12-24 11:00 52 50 57.6647 54.5217 62.1613 34.1147 49.4213 57.8416 892.74
$data['id'] 12-12-24 11:00 53 50 54.0431 52.1739 60.101 42.1017 49.4181 60.6163 894.2
$data['id'] 11-12-24 11:00 57 66.6667 56.4003 52.2609 66.4882 45.4931 49.4177 60.6163 896.48
$data['id'] 10-12-24 11:00 58 66.6667 52.1698 52.0952 74.5102 46.4174 49.4164 61.9364 893
$data['id'] 09-12-24 11:00 56 66.6667 53.1533 52.1905 60.6356 50.3748 49.4169 61.9364 894.31
$data['id'] 06-12-24 11:00 57 66.6667 54.6363 53.4783 65.127 50.3916 49.4161 59.8961 890.84
$data['id'] 05-12-24 11:00 58 66.6667 56.369 52.7826 70.3546 50.5207 49.4195 59.6481 893.55
$data['id'] 04-12-24 11:00 54 50 52.4508 52.6957 64.5375 50.5409 49.4191 60.8136 891.5
$data['id'] 03-12-24 11:00 56 66.6667 51.8108 52.6364 61.3371 50.8616 49.4209 62.5285 889.85
$data['id'] 02-12-24 11:00 57 33.3333 36.1692 50.8571 67.6535 99.2857 49.421 62.1822 886.81
$data['id'] 29-11-24 11:00 56 33.3333 27.0683 46.75 73.8872 99.3309 49.4182 61.0122 882.06
$data['id'] 28-11-24 11:00 57 33.3333 34.9672 47.6667 75.6723 98.7799 49.4272 61.0122 876.3
$data['id'] 27-11-24 11:00 55 33.3333 24.0088 46 71.8637 98.7356 49.4178 63.0116 874.63
$data['id'] 26-11-24 11:00 54 33.3333 27.5367 45.6364 61.0719 98.1309 49.419 60.9256 875.8
$data['id'] 25-11-24 11:00 55 33.3333 38.1361 47.3636 58.9929 98.0764 49.4154 62.4724 879.88
$data['id'] 22-11-24 11:00 52 33.3333 15.8757 44.8696 58.0527 98.9798 49.4077 60.9147 881.01
$data['id'] 21-11-24 11:00 48 16.6667 0 42.9167 63.0044 99.3451 49.3998 61.4595 866.29
$data['id'] 20-11-24 11:00 51 33.3333 1.69832 46.9565 64.6951 99.0908 49.403 61.8756 859.56
$data['id'] 19-11-24 11:00 45 16.6667 0 45 43.4831 98.8191 49.3997 61.6395 861.91
$data['id'] 18-11-24 11:00 48 16.6667 0 44.5455 67.4649 99.0799 49.4 60.9719 864.77
$data['id'] 15-11-24 11:00 51 16.6667 11.1148 46.3333 69.8692 99.4575 49.3998 60.9984 862.74
$data['id'] 14-11-24 11:00 51 16.6667 8.71754 45.9167 76.1326 99.9289 49.3994 60.0018 874.76
$data['id'] 13-11-24 11:00 50 16.6667 0 45.0435 76.0706 99.8999 49.4021 60.3014 861.33
$data['id'] 12-11-24 11:00 44 33.3333 0.227008 45.9091 71.57 47.0636 49.3998 60.3014 865.09
$data['id'] 11-11-24 11:00 52 16.6667 13.4365 49.0909 72.3411 98.4128 49.4034 62.1964 878.22
$data['id'] 08-11-24 11:00 47 16.6667 0 49 50.8966 98.4196 49.4049 61.1644 873.06
$data['id'] 07-11-24 11:00 50 16.6667 8.62908 50.5 69.4823 98.2932 49.4023 59.0223 879.31
$data['id'] 06-11-24 11:00 56 33.3333 32.7217 50.8696 62.403 98.1601 49.3875 63.2048 874.26
$data['id'] 05-11-24 11:00 53 33.3333 16.9959 50.4545 65.6942 98.3021 49.3897 59.8335 882.97
$data['id'] 04-11-24 11:00 56 33.3333 19.6572 51 75.0367 98.3931 49.3885 61.8341 881.1
$data['id'] 01-11-24 11:00 51 16.6667 9.13312 49.5833 72.3366 98.7166 49.3909 62.0041 885.04
$data['id'] 31-10-24 11:00 48 16.6667 0 48 62.5157 98.9074 49.3799 61.6908 872.83
$data['id'] 30-10-24 11:00 50 16.6667 14.3628 49.2174 63.6967 99.2171 49.3804 60.6015 881.44
$data['id'] 29-10-24 11:00 61 33.3333 47.4713 54.3636 80.5987 99.1611 49.3885 59.8423 894.38
$data['id'] 28-10-24 11:00 57 33.3333 34.3448 52.7619 70.0532 99.1886 49.3868 61.2924 897.08
$data['id'] 25-10-24 11:00 56 16.6667 32.0073 51.4783 78.6566 99.1251 49.3868 61.7063 898.74
$data['id'] 24-10-24 11:00 58 33.3333 48.9098 52.8696 64.0572 98.5696 49.3928 62.1992 896.35
$data['id'] 23-10-24 11:00 54 33.3333 34.6145 52.9091 49.4478 99.1347 49.377 58.5822 889.78
$data['id'] 22-10-24 11:00 57 33.3333 40.3236 53.0909 63.9138 99.1489 49.3784 61.0071 897.14
$data['id'] 21-10-24 11:00 55 50 57.3162 55.9048 61.5041 50.8241 49.381 61.8981 898.51
$data['id'] 18-10-24 11:00 60 50 52.3714 54.4545 56.6041 99.0708 49.3802 59.7395 902.54
$data['id'] 17-10-24 11:00 63 50 51.2614 52.3551 80.1105 97.9603 49.3744 61.6912 897.76
$data['id'] 16-10-24 11:00 57 33.3333 46.3559 53.2727 57.6603 97.8584 49.3726 63.3383 893.14
$data['id'] 15-10-24 11:00 62 66.6667 95.1215 53.9091 56.7684 50.0992 49.3828 59.6894 900.62
$data['id'] 14-10-24 11:00 59 50 89.8326 53.0476 59.7493 49.8563 49.386 62.3137 922.39
$data['id'] 11-10-24 11:00 59 50 80.5336 54.087 70.2164 50.0202 49.3816 59.8529 915.88
$data['id'] 10-10-24 11:00 57 50 80.6599 54.087 56.7404 50.157 49.3804 59.8529 911.28
$data['id'] 09-10-24 11:00 58 50 77.3444 51.913 66.9796 50.2447 49.3839 61.9516 915.28
$data['id'] 08-10-24 11:00 55 50 70.3347 50 56.481 50.5263 49.38 60.7652 909.99
$data['id'] 07-10-24 11:00 55 50 78.9232 50.5714 42.9187 50.4777 49.3814 60.1239 912.52
$data['id'] 04-10-24 11:00 57 50 76.9497 51.8261 63.5458 50.7451 49.382 59.9209 912.11
$data['id'] 03-10-24 11:00 57 50 78.4496 49.8261 58.4817 51.5198 49.3812 59.0692 909.63
$data['id'] 02-10-24 11:00 61 50 90.543 49.913 70.311 51.4962 49.3877 66.5115 916.12
$data['id'] 01-10-24 11:00 63 66.6667 85.2067 50.5455 73.8911 51.9576 49.3901 61.9377 909.41
$data['id'] 30-09-24 11:00 60 66.6667 83.4859 51.6364 53.6882 52.2632 49.3827 61.9514 911.13
$data['id'] 27-09-24 11:00 60 50 86.2646 53.3333 68.1064 52.1645 49.3902 57.8979 917.35
$data['id'] 26-09-24 11:00 60 66.6667 82.1124 52.5833 57.8085 52.2426 49.3926 62.4316 912.02
$data['id'] 25-09-24 11:00 57 50 60.9749 50.8696 74.5626 52.7212 49.3866 61.0413 906.41
$data['id'] 24-09-24 11:00 56 50 59.8209 52.2727 66.4758 52.7374 49.3878 61.3519 907.33
$data['id'] 23-09-24 11:00 60 50 46.0874 51.5455 63.9409 97.3951 49.386 63.0946 903.4
$data['id'] 20-09-24 11:00 51 33.3333 50.2427 53.6667 62.6368 52.319 49.3868 57.9231 896.54
$data['id'] 19-09-24 11:00 55 33.3333 51.1306 54.3333 82.7367 51.7469 49.3971 59.9304 907.98
$data['id'] 18-09-24 11:00 55 16.6667 42.8436 53.8949 65.1143 98.9233 49.385 61.4711 892.76
$data['id'] 17-09-24 11:00 59 33.3333 47.8395 55.6818 69.5815 98.8405 49.3927 61.6285 900.77
$data['id'] 16-09-24 11:00 58 33.3333 45.3297 55.0189 64.246 98.879 49.3887 59.8872 895.41
$data['id'] 13-09-24 11:00 58 33.3333 42.4056 57.8125 59.3876 98.9603 49.3882 62.7011 899.45
$data['id'] 12-09-24 11:00 58 33.3333 43.6132 57.5521 63.8085 98.6209 49.3867 62.7011 892.96
$data['id'] 11-09-24 11:00 53 16.6667 29.5016 56.25 58.3098 98.267 49.38 62.0121 884.57
$data['id'] 10-09-24 11:00 54 16.6667 33.5267 57.6555 60.7053 98.4603 49.3782 62.3815 882.73
$data['id'] 09-09-24 11:00 55 16.6667 30.1645 58.5227 68.8196 98.5614 49.3809 60.7577 886.57
$data['id'] 06-09-24 11:00 55 33.3333 30.5552 58.4201 49.7427 99.2633 49.365 62.0138 878.95
$data['id'] 05-09-24 11:00 61 50 41.9202 59.2014 63.744 99.5389 49.3708 63.4938 893.69
$data['id'] 04-09-24 11:00 60 50 41.1507 58.6957 61.0328 99.3257 49.3676 62.7685 896.82
$data['id'] 03-09-24 11:00 60 66.6667 69.3856 62.2159 63.5632 50.4701 49.3697 61.102 907.84
$data['id'] 02-09-24 11:00 61 66.6667 69.0541 60.7955 68.9352 50.4705 49.3716 61.102 920.71
$data['id'] 30-08-24 11:00 62 66.6667 74.4288 58.5938 73.0108 52.1231 49.3668 59.3285 918.57
$data['id'] 29-08-24 11:00 61 66.6667 66.1655 58.0729 71.7119 54.5395 49.3662 62.6092 923.24
$data['id'] 28-08-24 11:00 64 50 60.7198 57.971 75.3621 95.0198 49.3628 59.5362 910.56
$data['id'] 27-08-24 11:00 62 50 57.2866 56.5341 66.875 94.6065 49.3614 60.4927 908.37
$data['id'] 26-08-24 11:00 66 66.6667 56.8604 55.5871 76.2659 94.5657 49.3607 60.4927 907.46
$data['id'] 23-08-24 11:00 64 66.6667 56.1857 54.4271 69.9538 94.5331 49.36 58.967 908.03
$data['id'] 22-08-24 11:00 66 66.6667 61.0039 54.6875 71.5851 94.3293 49.3642 62.2001 908.46
$data['id'] 21-08-24 11:00 60 33.3333 51.0477 52.9891 73.0769 94.3303 49.3618 62.8937 907.95
$data['id'] 20-08-24 11:00 60 33.3333 56.4579 52.8409 70.4372 94.0698 49.3617 62.8937 903.32
$data['id'] 19-08-24 11:00 60 33.3333 51.5568 53.8826 76.5799 94.0785 49.3607 59.5531 908.58
$data['id'] 16-08-24 11:00 59 33.3333 54.5046 53.0382 68.2225 93.8241 49.3634 59.6095 905.9
$data['id'] 15-08-24 11:00 57 33.3333 39.8367 51.9965 67.3186 94.2837 49.3629 60.9509 905.65
$data['id'] 14-08-24 11:00 56 33.3333 38.0372 50.9058 65.9141 94.2958 49.3627 61.9015 889.03
$data['id'] 13-08-24 11:00 51 16.6667 30.0343 48.7689 59.3658 93.8652 49.3581 60.5569 888.62
$data['id'] 12-08-24 11:00 51 16.6667 29.9633 48.6742 57.5347 93.8656 49.3593 61.8997 885.41
$data['id'] 09-08-24 11:00 55 16.6667 32.26 51.3021 80.5006 93.7837 49.3598 61.1448 883.17
$data['id'] 08-08-24 11:00 48 16.6667 16.7515 49.0451 54.2344 93.3506 49.3451 56.5277 884.03
$data['id'] 07-08-24 11:00 52 16.6667 17.0711 50.8152 78.674 94.5667 49.367 58.2641 886.22
$data['id'] 06-08-24 11:00 47 0 3.52786 48.8636 69.0743 94.6961 49.3639 64.5252 866.77
$data['id'] 05-08-24 11:00 45 0 0 48.0114 59.1373 94.3903 49.3224 66.2145 859.4
$data['id'] 02-08-24 11:00 49 16.6667 0 51.5625 70.4023 97.1174 49.3294 61.253 879.06
$data['id'] 01-08-24 11:00 54 16.6667 40.9151 54.0799 57.9249 98.2262 49.3379 63.5791 905.28
$data['id'] 31-07-24 11:00 53 33.3333 51.0143 56.0688 65.2377 51.9879 49.3573 60.5812 920.44
$data['id'] 30-07-24 11:00 53 16.6667 21.5364 54.6402 66.7852 98.6595 49.339 62.7338 909.23
$data['id'] 29-07-24 11:00 54 16.6667 24.6223 55.1587 70.6061 98.6973 49.3327 62.0657 904.14
$data['id'] 26-07-24 11:00 53 16.6667 10.0345 53.3514 79.8525 98.9843 49.3283 62.2613 906.58
$data['id'] 25-07-24 11:00 50 16.6667 0 51.5399 70.9037 98.9863 49.3258 61.1994 899.09
$data['id'] 24-07-24 11:00 53 16.6667 16.8632 51.8116 74.3214 99.55 49.3187 61.0775 902.49
$data['id'] 23-07-24 11:00 62 50 36.9882 53.9773 83.3113 99.6576 49.3207 60.2998 914.03
$data['id'] 22-07-24 11:00 60 50 31.8761 53.9683 77.0779 99.8027 49.3229 60.1079 917.89
$data['id'] 19-07-24 11:00 53 50 27.7817 53.9855 81.9813 46.3352 49.3103 60.6409 907.56
$data['id'] 18-07-24 11:00 56 50 48.5986 54.529 80.7567 49.6972 49.3103 62.2482 916.4
$data['id'] 17-07-24 11:00 54 50 48.5544 53.6232 66.5816 46.6922 49.2997 62.4612 917.31
$data['id'] 16-07-24 11:00 62 66.6667 80.2854 54.3651 76.3017 44.5374 49.3029 60.3877 934.28
$data['id'] 15-07-24 11:00 63 66.6667 100 56.5476 66.7841 38.7312 49.31 60.3877 939.96
$data['id'] 12-07-24 11:00 64 66.6667 97.0613 53.0797 84.309 36.2084 49.3101 60.06 946.21
$data['id'] 11-07-24 11:00 63 66.6667 100 55.9783 71.37 37.8481 49.3156 62.5517 936
$data['id'] 10-07-24 11:00 62 66.6667 96.3465 51.9022 73.0052 36.7659 49.3125 61.2611 939.29
$data['id'] 09-07-24 11:00 62 66.6667 100 52.2727 67.0828 41.2806 49.3126 59.8888 930.53
$data['id'] 08-07-24 11:00 62 66.6667 100 52.6786 60.8474 41.9355 49.3099 61.1941 933.39
$data['id'] 05-07-24 11:00 62 66.6667 100 53.1703 58.1977 41.6426 49.3126 63.383 932.7
$data['id'] 04-07-24 11:00 62 66.6667 100 54.1667 59.9411 41.6463 49.3126 63.383 936.09
$data['id'] 03-07-24 11:00 62 66.6667 97.8018 52.0833 64.7915 42.274 49.3113 59.754 931.67
$data['id'] 02-07-24 11:00 59 50 80.1435 49.9008 71.7961 50.1896 49.3044 60.5158 923.89
$data['id'] 01-07-24 11:00 61 66.6667 88.9204 51.2897 57.1461 50.1606 49.3058 60.8927 923.21
$data['id'] 28-06-24 11:00 63 66.6667 93.485 51.0417 68.8032 50.1722 49.3071 60.484 923.51
$data['id'] 27-06-24 11:00 62 66.6667 90.5188 49.8264 65.2322 50.22 49.306 60.524 925.45
$data['id'] 26-06-24 11:00 61 66.6667 97.6567 50.9058 50.9257 50.1915 49.3041 60.9601 923.63
$data['id'] 25-06-24 11:00 63 66.6667 84.9383 49.2063 77.9926 50.4473 49.3015 59.7592 926.05
$data['id'] 24-06-24 11:00 64 66.6667 91.7377 50.4735 78.632 50.4766 49.3038 61.9436 926.84
$data['id'] 21-06-24 11:00 61 66.6667 93.4308 49.0451 59.0868 50.2283 49.2901 61.0222 926.3
$data['id'] 20-06-24 11:00 62 66.6667 96.8516 48.9583 64.7695 48.8405 49.29 60.5708 932.98
$data['id'] 19-06-24 11:00 60 66.6667 92.1984 47.1014 53.9331 48.2651 49.287 60.5708 924.62
$data['id'] 18-06-24 11:00 59 66.6667 90.4013 46.4962 53.8419 47.4669 49.2861 60.9093 927.44
$data['id'] 17-06-24 11:00 58 66.6667 87.0438 46.5909 45.9402 47.8146 49.2881 65.3014 923.68
$data['id'] 14-06-24 11:00 60 66.6667 89.6908 48.8715 54.8387 45.9436 49.2924 62.9903 918.49
$data['id'] 13-06-24 11:00 60 66.6667 97.9382 49.9132 53.7248 43.6957 49.2856 58.7483 923.96
$data['id'] 12-06-24 11:00 61 66.6667 100 50.3788 64.7678 38.7641 49.2778 59.5972 932.18
$data['id'] 07-06-24 11:00 57 66.6667 100 53.2986 52.1185 38.8408 49.2771 61.2549 923.95
$data['id'] 06-06-24 11:00 58 66.6667 100 55.7292 63.8401 40.2161 49.2787 61.2534 922.89
$data['id'] 05-06-24 11:00 54 66.6667 87.3817 54.7101 61.5034 28.4761 49.2679 61.4453 919.1
$data['id'] 04-06-24 11:00 51 66.6667 70.9084 53.4091 63.6902 26.3306 49.2593 62.0935 902.11
$data['id'] 03-06-24 11:00 56 66.6667 90.0233 56.4394 68.7644 31.1666 49.2636 62.0106 905.54
$data['id'] 31-05-24 11:00 53 66.6667 82.8196 55.0725 55.1568 29.0997 49.2581 62.3542 903.64
$data['id'] 30-05-24 11:00 54 66.6667 83.8158 55.5871 61.1728 32.4547 49.2581 60.4863 905.78
$data['id'] 29-05-24 11:00 55 66.6667 92.4526 55.2083 67.1141 29.2272 49.2557 59.6029 906.35
$data['id'] 28-05-24 11:00 58 83.3333 100 57.8373 69.8707 28.7383 49.2577 61.1428 912.02
$data['id'] 27-05-24 11:00 57 66.6667 98.9752 57.7083 67.6337 29.0343 49.2574 61.1428 914.98
$data['id'] 24-05-24 11:00 57 66.6667 90.2169 55.6818 70.3315 37.7147 49.257 60.093 914.95
$data['id'] 23-05-24 11:00 58 83.3333 99.5725 56.9129 53.3954 36.7703 49.26 61.1005 913.78
$data['id'] 22-05-24 11:00 59 83.3333 94.9026 58.8068 64.3529 36.5811 49.2617 61.1423 910.15
$data['id'] 21-05-24 11:00 59 83.3333 92.2906 59.127 60.3247 39.1238 49.2622 59.361 911.16
$data['id'] 20-05-24 11:00 61 100 99.0544 60.9375 58.3812 37.8645 49.2594 59.361 914.67
$data['id'] 17-05-24 11:00 59 66.6667 93.2692 60.1326 66.1874 41.8494 49.2592 61.0462 913.69
$data['id'] 16-05-24 11:00 65 83.3333 94.3275 59.5644 64.8061 58.4882 50.7402 62.8072 912.97
$data['id'] 15-05-24 11:00 65 100 99.8109 57.197 67.2295 54.3345 50.7419 59.9024 913.38
$data['id'] 14-05-24 11:00 64 100 99.519 57.3413 67.4801 49.9999 50.7422 60.8518 911.02
$data['id'] 13-05-24 11:00 65 100 100 57.1875 100 50.0829 50.7417 61.6969 911.97
$data['id'] 10-05-24 11:00 64 100 100 55.4924 67.4111 50.5669 50.7423 61.6483 910.92
$data['id'] 09-05-24 11:00 63 83.3333 100 54.5455 65.8426 50.7307 50.7491 61.2783 904.39
$data['id'] 08-05-24 11:00 62 83.3333 100 53.4091 56.2879 50.0749 50.7494 58.6668 899.09
$data['id'] 07-05-24 11:00 61 66.6667 100 53.5714 63.0373 50.7206 50.7474 61.0724 900.35
$data['id'] 06-05-24 11:00 60 50 100 51.6667 64.2913 49.8116 50.7403 61.0724 891.63
$data['id'] 03-05-24 11:00 59 50 96.64 50 53.7316 52.2648 50.7478 61.7135 886.92
$data['id'] 02-05-24 11:00 57 50 76.3039 49.2424 67.6842 53.9391 50.7504 62.5051 879.58
$data['id'] 30-04-24 11:00 58 50 87.3119 49.8016 63.7776 54.1465 50.7549 62.2308 878.49
$data['id'] 29-04-24 11:00 61 50 100 51.7708 65.754 52.4457 50.7526 60.6609 882.96
$data['id'] 26-04-24 11:00 59 50 81.3848 51.1364 63.2454 57.4324 50.7499 61.5759 883.38
$data['id'] 25-04-24 11:00 59 50 75.2327 51.7045 79.5148 60.9578 50.7557 61.0324 870.15
$data['id'] 24-04-24 11:00 60 50 88.8991 52.0833 57.6439 58.9018 50.7558 59.369 873.31
$data['id'] 23-04-24 11:00 58 50 71.3735 51.5625 67.5817 61.5879 50.7588 60.123 875.5
$data['id'] 22-04-24 11:00 56 33.3333 62.186 49.5833 67.4803 65.4349 50.747 60.7615 866.74
$data['id'] 19-04-24 11:00 52 33.3333 50.0354 50.0947 66.0874 55.1707 50.7444 59.9686 859.66
$data['id'] 18-04-24 11:00 57 50 68.3232 53.0303 76.2827 57.1779 50.7404 62.7866 865.92
$data['id'] 17-04-24 11:00 61 66.6667 79.6227 53.9683 75.4086 59.6416 50.7471 61.2005 867.04
$data['id'] 16-04-24 11:00 60 66.6667 78.6777 51.9792 75.7684 58.0881 50.7462 59.7793 874.46
$data['id'] 15-04-24 11:00 65 66.6667 97.5168 55.2083 75.9777 61.8023 50.7403 62.9734 882.72
$data['id'] 12-04-24 11:00 64 66.6667 100 54.8295 63.4589 59.1552 50.7263 62.9899 882.6
$data['id'] 11-04-24 11:00 66 83.3333 100 55.9659 61.5013 62.1682 50.7376 59.0596 883.91
$data['id'] 10-04-24 11:00 65 83.3333 100 56.746 68.7229 57.6752 50.7287 62.2561 886.71
$data['id'] 09-04-24 11:00 64 83.3333 98.7284 54.5833 70.8 56.1333 50.7362 60.137 881.29
$data['id'] 08-04-24 11:02 63 83.3333 96.2066 55 54.4943 54.4202 50.7353 59.7402 884.74
$data['id'] 05-04-24 11:00 62 66.6667 90.706 57.1429 61.087 49.5131 50.7367 61.5039 880.25
$data['id'] 04-04-24 11:00 66 83.3333 100 58.428 62.5423 50.3341 50.7317 62.1867 884.5
$data['id'] 03-04-24 11:00 64 66.6667 98.3186 56.4484 67.3636 49.7963 50.736 61.6432 884.07
$data['id'] 02-04-24 11:00 68 100 100 59.0625 57.0001 49.6071 50.7227 60.5968 882.28

Nota: De weergegeven waardes zijn genormaliseerd. De genormaliseerde waarden zijn zo ingesteld dat een waarde van 50 een neutraal marktsentiment aangeeft. Waarden boven de 50 wijzen op een positief (bullish) sentiment (hebzucht), terwijl waarden onder de 50 een negatief (bearish) sentiment (angst) aanduiden.

Stock Data

Download Individual Stock GF Data (.xslx)
Ticker GF Index Momentum Price Strength Price Breadth Volatility Close Price
WKL.AS 32 0 0 39.1304 89.0748 153.65
UNA.AS 46 16.6667 24.3478 58.6957 84.6814 53.0472
UMG.AS 59 66.6667 71.6867 56.5217 42.7135 27.48
SHELL.AS 66 66.6667 88.294 63.0435 47.0424 32.155
REN.AS 42 33.3333 40.6452 50 46.8383 45.96
RAND.AS 52 16.6667 51.751 50 93.3432 39.98
PRX.AS 75 83.3333 78.8915 80.4348 59.7836 43.29
PHIA.AS 54 50 51.0753 65.2174 50.6393 25.73
NN.AS 81 100 100 71.7391 53.7854 48.81
MT.AS 68 66.6667 100 45.6522 59.9636 27.97
KPN.AS 58 50 88.4422 45.6522 50.5301 3.642
INGA.AS 77 100 100 63.0435 45.4147 16.95
IMCD.AS 57 33.3333 49.0567 50 99.3702 144.6
HEIA.AS 83 100 100 54.3478 78.5471 82.28
EXO.AS 58 50 69.8324 56.5217 57.7884 93.75
DSFIR.AS 62 66.6667 71.5994 45.6522 64.6161 103.6
BESI.AS 25 33.3333 1.63446 41.3043 26.8754 114.7
ASRNL.AS 76 100 100 58.6957 47.3773 51.1
ASML.AS 55 66.6667 68.4219 54.3478 33.1476 714.5
ASM.AS 39 33.3333 35.8657 54.3478 33.0999 555.6
AKZA.AS 73 83.3333 99.1501 54.3478 55.6091 60.52
AGN.AS 50 33.3333 54.4828 58.6957 54.7217 6.08
ADYEN.AS 66 83.3333 73.7258 50 59.6695 1726.4
AD.AS 60 50 70.1987 58.6957 63.8758 34.33
ABN.AS 80 100 100 63.0435 59.2109 18.44

Nota: De weergegeven waardes zijn genormaliseerd. De genormaliseerde waarden zijn zo ingesteld dat een waarde van 50 een neutraal marktsentiment aangeeft. Waarden boven de 50 wijzen op een positief (bullish) sentiment (hebzucht), terwijl waarden onder de 50 een negatief (bearish) sentiment (angst) aanduiden.

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