AEX Fear & Greed Index

Image

Download jouw GRATIS exemplaar van ons boek en doe er je voordeel mee:

Handleiding AEX Fear & Greed Index

Download Nu


Index Data

Download GF Index Data (.xslx)
Download Extra Hours GF Index Data (.xslx)
id Date GF Index Momentum Price Strength Price Breadth Put Call Ratio Volatility Safe Haven Demand Junk Bond Demand Close Price
$data['id'] 21-06-24 11:00 61 66.6667 93.4308 49.0451 59.0868 50.2283 49.2901 61.0222
$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
$data['id'] 28-03-24 11:00 66 83.3333 100 58.9015 58.4658 49.7715 50.7332 63.706 882.35
$data['id'] 27-03-24 11:00 63 66.6667 100 56.7235 61.2934 49.8206 50.7351 61.6742 878.86
$data['id'] 26-03-24 11:00 64 66.6667 100 57.1023 67.0881 49.5968 50.7357 59.5481 879.16
$data['id'] 25-03-24 11:00 61 66.6667 98.9801 56.25 47.9895 49.5896 50.7367 62.9412 877.38
$data['id'] 22-03-24 11:00 63 66.6667 98.6634 54.9242 60.1373 49.5545 50.7351 62.655 876.43
$data['id'] 21-03-24 11:00 63 66.6667 100 56.0606 58.912 50.3575 50.7312 62.7422 875.66
$data['id'] 20-03-24 11:00 67 66.6667 91.4809 53.5038 100 50.1878 50.7468 61.5525 860.78
$data['id'] 19-03-24 11:00 60 66.6667 88.1821 51.1364 56.2497 51.3358 50.7463 59.7009 860.05
$data['id'] 18-03-24 11:00 61 66.6667 85.7569 51.4881 67.0818 49.9315 50.7459 61.9953 854.38
$data['id'] 15-03-24 11:00 65 66.6667 89.0761 51.6098 68.5705 51.4968 50.7475 76.8583 854.85
$data['id'] 14-03-24 10:00 63 66.6667 93.3512 54.6402 69.0509 49.7236 50.7482 61.1675 858.22
$data['id'] 13-03-24 10:00 62 66.6667 91.4603 54.072 64.1056 49.699 50.7478 59.9826 860.36
$data['id'] 12-03-24 10:02 61 66.6667 85.5308 52.3674 63.9614 50.1335 50.7418 60.5998 860.74
$data['id'] 11-03-24 10:02 61 66.6667 85.2841 50.5952 69.7996 49.465 50.7421 60.7659 852.44
$data['id'] 08-03-24 10:00 68 83.3333 100 53.0303 78.8697 49.9923 50.7364 61.0431 862.39
$data['id'] 07-03-24 10:00 63 66.6667 97.6581 51.5152 64.997 52.1452 50.7397 61.1503 868.82
$data['id'] 06-03-24 10:00 64 66.6667 96.0084 51.7045 71.8045 49.5778 50.7425 63.7777 857.22
$data['id'] 05-03-24 10:00 61 66.6667 92.8472 51.2311 56.3261 49.6266 50.7414 60.1042 851.37
$data['id'] 04-03-24 12:00 61 66.6667 98.5002 52.0833 54.9192 49.6422 50.7418 60.602 856.3
$data['id'] 01-03-24 12:00 62 66.6667 89.4324 52.0833 65.4432 49.7288 50.7496 60.7828 854.03
$data['id'] 29-02-24 12:00 60 66.6667 84.5985 51.0417 58.4209 49.654 50.7508 63.0079 849.71
$data['id'] 28-02-24 12:00 61 66.6667 87.3443 51.9022 59.1668 49.6773 50.7508 61.9936 847.68
$data['id'] 27-02-24 12:00 63 66.6667 94.324 51.2311 71.6882 49.8708 50.7504 59.543 853.71
$data['id'] 26-02-24 12:00 61 66.6667 93.055 50.7576 57.0545 49.848 50.7517 62.1288 852.6
$data['id'] 23-02-24 12:00 65 83.3333 98.4657 53.3854 61.4792 50.1748 50.7502 60.9058 855.31
$data['id'] 22-02-24 12:00 64 83.3333 96.8505 53.0382 59.1767 51.5825 50.7438 59.3246 858.07
$data['id'] 21-02-24 12:00 63 66.6667 87.3327 52.4457 71.5228 51.8248 50.7495 62.4042 846.49
$data['id'] 20-02-24 12:00 65 83.3333 91.8205 52.4621 70.3094 49.0205 50.7498 61.3706 848.01
$data['id'] 19-02-24 12:00 67 100 96.4468 54.6402 62.59 49.2791 50.7478 61.3706 856.36
$data['id'] 16-02-24 12:00 68 100 100 55.2951 62.6729 49.5532 50.7445 60.2476 857.36
$data['id'] 15-02-24 12:00 66 100 90.305 52.8646 60.3832 49.6132 50.749 63.5696 846.94
$data['id'] 14-02-24 12:00 68 100 88.1122 52.5362 77.6183 49.5643 50.7502 59.2668 843.91
$data['id'] 13-02-24 12:00 65 100 88.6209 52.8409 57.8203 49.2111 50.7694 61.6985 842.4
$data['id'] 12-02-24 12:00 69 100 100 52.5568 72.2206 50.4361 50.7604 60.7619 854.21
$data['id'] 09-02-24 12:00 69 100 100 52.2569 72.4226 49.9641 50.756 59.858 851.28
$data['id'] 08-02-24 12:00 69 100 100 51.1285 72.7573 51.3494 50.7516 59.9149 843.44
$data['id'] 07-02-24 12:00 67 100 97.8485 50.8152 59.9152 52.5558 50.7576 61.8512 830.03
$data['id'] 06-02-24 12:00 67 100 100 50.0947 58.1452 52.7588 50.7572 57.4271 831.78
$data['id'] 05-02-24 12:00 69 100 100 52.4621 67.2354 52.2269 50.7579 61.8986 823.82
$data['id'] 02-02-24 12:00 70 100 100 51.9965 75.8477 52.0906 50.7553 62.1025 821.84
$data['id'] 01-02-24 12:00 70 100 100 50.4529 77.3928 51.7946 50.7583 65.1991 821.46
$data['id'] 31-01-24 12:00 68 100 99.1907 51.1364 60.0736 52.2696 50.7576 63.1417 819.35
$data['id'] 30-01-24 12:00 68 100 100 50.9921 61.2634 51.3927 50.7539 63.1417 820
$data['id'] 29-01-24 12:00 67 100 100 51.0913 60.2998 50.2549 50.757 60.4734 819.67
$data['id'] 26-01-24 12:00 67 100 100 50.2841 63.0878 50.2594 50.7575 60.4734 817.97
$data['id'] 25-01-24 12:00 66 100 100 48.7103 62.8563 51.8981 50.7582 52.7514 815.38
$data['id'] 24-01-24 12:02 63 66.6667 100 49.1667 67.1987 60.8899 50.7463 52.7514 806.86
$data['id'] 23-01-24 12:02 60 50 84.5216 47.5877 69.6966 67.8796 50.7519 52.7514 788.61
$data['id'] 22-01-24 12:00 60 50 83.4039 49.4518 66.3416 68.6098 50.7501 52.7514 785.81
$data['id'] 19-01-24 12:00 59 50 78.9501 49.6032 56.3885 69.72 50.7485 60.4795 779.29
$data['id'] 18-01-24 12:00 60 50 65.6224 48.8095 71.4126 73.0227 50.7532 61.6762 778.15
$data['id'] 17-01-24 12:00 55 33.3333 61.3209 46.9792 65.3809 72.5583 50.7608 58.2779 771.12
$data['id'] 16-01-24 12:00 59 50 76.8402 48.136 57.8332 74.6924 50.7605 59.9838 778.5
$data['id'] 15-01-24 12:00 61 50 83.5797 49.6711 64.9728 74.5006 50.7611 59.9838 779.39
$data['id'] 12-01-24 12:00 62 50 85.3968 51.3889 59.6817 74.2669 50.7602 63.2649 781.86
$data['id'] 11-01-24 12:00 62 50 81.5043 52.1825 64.1034 77.7811 50.7677 58.1431 774.89
$data['id'] 10-01-24 12:00 57 33.3333 79.1311 50.3125 48.4826 75.2656 50.7714 62.5852 775.11
$data['id'] 09-01-24 12:00 59 33.3333 78.8925 50.5482 66.2404 75.2045 50.7716 60.7181 778.56
$data['id'] 08-01-24 12:00 61 50 78.3275 51.6447 65.4023 75.312 50.7694 59.3124 779.35
$data['id'] 05-01-24 12:00 55 33.3333 73.0412 53.0754 46.7914 71.2239 50.7709 59.5017 778.51
$data['id'] 04-01-24 12:14 65 66.6667 82.0065 55.754 59.9144 75.1952 50.7706 65.6664 780.35
$data['id'] 03-01-24 12:00 63 66.6667 84.0532 56.1458 56.207 75.8331 50.7741 57.8207 779.19
$data['id'] 02-01-24 12:00 66 66.6667 92.3531 57.8947 59.9359 75.7202 50.7735 62.0255 782.52
$data['id'] 29-12-23 12:00 67 66.6667 93.8599 60.119 61.4836 75.7285 50.7744 60.3925 786.06
$data['id'] 28-12-23 12:00 68 66.6667 91.7252 59.4246 70.8262 75.8246 50.7742 61.8046 787.32
$data['id'] 27-12-23 12:00 67 66.6667 93.5962 58.9286 70.1999 74.5535 50.7735 60.8919 786.43
$data['id'] 22-12-23 12:00 66 66.6667 87.3556 59.058 68.3459 73.0192 50.7788 59.8001 785.55
$data['id'] 21-12-23 12:00 66 66.6667 92.3406 58.7862 60.752 74.4506 50.7734 62.2915 789.74
$data['id'] 20-12-23 12:00 73 100 98.3055 60.1449 63.4729 78.084 50.7722 63.9934 793.96
$data['id'] 19-12-23 12:00 73 100 98.9378 61.0795 63.499 78.6278 50.772 59.4677 792.12
$data['id'] 18-12-23 12:00 72 100 98.3688 60.7143 63.0879 80.1355 50.7732 54.7101 788.44
$data['id'] 15-12-23 12:00 73 100 100 59.1486 67.6225 80.3315 50.7668 59.5838 793.07
$data['id'] 14-12-23 12:00 74 100 100 60.779 68.1704 76.6771 50.7542 63.037 790.1
$data['id'] 13-12-23 12:00 73 100 100 60.6884 64.695 72.5609 50.7748 63.7655 787.32
$data['id'] 12-12-23 12:00 71 100 100 60.7955 59.8365 72.2839 50.7759 59.9899 786.4
$data['id'] 11-12-23 12:00 69 83.3333 99.646 59.9206 63.0452 72.0571 50.7736 59.9626 786.31
$data['id'] 08-12-23 12:00 70 83.3333 100 61.5942 68.4634 70.781 50.7647 59.5207 781.85
$data['id'] 07-12-23 12:00 70 83.3333 100 51.9318 73.0656 70.247 49.2329 63.9451 776.34
$data['id'] 06-12-23 12:00 68 83.3333 100 51.9398 69.0543 61.7518 49.2336 62.9674 776.18
$data['id'] 05-12-23 12:00 66 66.6667 97.767 51.8844 69.405 61.1961 49.2324 62.6371 774.07
$data['id'] 04-12-23 12:00 65 66.6667 98.1158 51.8869 64.7052 61.272 49.2304 61.5903 770.61
$data['id'] 01-12-23 12:00 66 83.3333 100 51.8005 61.6862 61.4047 49.229 56.3491 771.37
$data['id'] 30-11-23 12:00 65 66.6667 100 51.7656 68.3988 61.8998 49.2265 57.6265 765.04
$data['id'] 29-11-23 12:00 64 66.6667 96.7448 51.792 66.5917 55.787 49.2261 57.7173 761.99
$data['id'] 28-11-23 12:00 66 83.3333 91.3195 51.7677 72.3129 55.6754 49.2271 60.4365 761.37
$data['id'] 27-11-23 12:00 66 83.3333 98.7406 51.7968 66.6642 56.8362 49.2274 55.879 764.22
$data['id'] 24-11-23 12:00 67 83.3333 100 51.7778 73.2449 56.9868 49.2267 56.7931 765.66
$data['id'] 23-11-23 12:00 66 83.3333 93.9512 51.7426 70.079 54.6263 49.2264 56.7931 762.32
$data['id'] 22-11-23 12:00 67 83.3333 94.6893 51.7664 76.3123 53.9257 49.227 57.6917 760.04
$data['id'] 21-11-23 12:00 67 83.3333 94.1972 51.7339 76.3506 54.1472 49.2279 57.8592 758.56
$data['id'] 20-11-23 12:00 65 83.3333 92.1468 51.7524 64.246 54.226 49.2277 56.9838 759.47
$data['id'] 17-11-23 12:00 67 83.3333 91.5317 51.7655 75.0646 54.343 49.2301 60.4615 758.59
$data['id'] 16-11-23 12:00 63 83.3333 87.9639 51.7355 60.9915 50.1811 49.2346 55.6727 753.91
$data['id'] 15-11-23 12:00 69 100 100 51.7595 72.9984 51.4785 49.2395 59.8917 762.82
$data['id'] 14-11-23 12:00 66 83.3333 97.2308 51.7131 71.9046 49.9671 49.2335 57.8868 758.15
$data['id'] 13-11-23 12:00 66 83.3333 100 51.7019 71.5548 50.2941 49.2324 56.0229 753.41
$data['id'] 10-11-23 12:00 60 66.6667 85.7022 51.6228 62.9778 50.7384 49.2278 56.0662 746.31
$data['id'] 09-11-23 12:00 64 66.6667 92.0612 51.6739 76.5604 53.2766 49.2195 59.2687 749.16
$data['id'] 08-11-23 12:00 55 50 53.8945 51.5858 66.7023 56.2678 49.2185 60.193 734.64
$data['id'] 07-11-23 12:00 56 50 63.9306 51.6076 64.1935 56.7878 49.2186 56.9293 735.74
$data['id'] 06-11-23 12:00 54 50 66.1174 51.5962 55.1647 50.817 49.2181 56.7866 735.34
$data['id'] 03-11-23 12:00 55 50 64.4098 51.5929 61.6552 50.8051 49.2179 55.4573 736.31
$data['id'] 02-11-23 12:00 53 33.3333 57.7892 51.565 67.9236 52.504 49.2222 59.7471 736.03
$data['id'] 01-11-23 12:00 45 16.6667 11.2043 51.4822 70.8716 57.5035 49.2154 55.5976 722.23

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 74 83.3333 100 64.5833 48.8593
UNA.AS 75 100 96.6178 70.8333 32.8618
UMG.AS 45 50 43.1818 52.0833 37.6225
TKWY.AS 35 50 17.8678 35.4167 37.23
SHELL.AS 40 50 28.3401 47.9167 37.7359
REN.AS 77 100 100 66.6667 44.8543
RAND.AS 25 16.6667 15.2397 39.5833 32.4496
PRX.AS 47 50 71.411 39.5833 29.1305
PHIA.AS 50 50 84.4297 45.8333 23.6768
NN.AS 33 33.3333 24.5496 37.5 38.3659
MT.AS 41 16.6667 8.97437 39.5833 99.6331
LIGHT.AS 45 16.6667 8.60928 58.3333 97.1798
KPN.AS 75 83.3333 100 66.6667 50.0861
INGA.AS 55 33.3333 42.0886 47.9167 99.3265
IMCD.AS 28 16.6667 8.11876 43.75 46.8169
HEIA.AS 51 50 66.5988 39.5833 49.9731
DSFIR.AS 53 50 62.6866 52.0833 48.4929
BESI.AS 70 83.3333 87.5 66.6667 44.5186
ASML.AS 71 83.3333 91.4929 60.4167 50.4915
ASM.AS 69 83.3333 93.6448 56.25 44.655
AKZA.AS 25 16.6667 11.3379 33.3333 41.7785
AGN.AS 58 50 45.4338 39.5833 99.7132
ADYEN.AS 25 33.3333 5.21527 33.3333 29.2212
AD.AS 36 33.3333 45.5109 39.5833 29.1765

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.