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MT.AS Stock Data

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id Date GF Index Momentum Price Strength Price Breadth Volatility Close Price
$data['id'] 06-09-24 11:00 60 50 36.4162 56.25 99.6146 20.01
$data['id'] 05-09-24 11:00 60 50 36.0308 56.25 99.6943 20.24
$data['id'] 04-09-24 11:00 60 50 33.8053 58.6957 99.6849 20
$data['id'] 03-09-24 11:00 53 50 62.2764 61.3636 39.2115 20.26
$data['id'] 02-09-24 11:00 59 66.6667 69.1057 61.3636 39.1607 21.34
$data['id'] 30-08-24 11:00 55 50 69.0226 60.4167 42.5868 21.22
$data['id'] 29-08-24 11:00 52 50 58.1955 52.0833 48.8804 21.15
$data['id'] 28-08-24 11:00 54 50 60.3007 54.3478 51.6986 21.08
$data['id'] 27-08-24 11:00 55 50 62.406 56.8182 51.6918 20.87
$data['id'] 26-08-24 11:00 57 66.6667 56.391 56.8182 51.7009 20.98
$data['id'] 23-08-24 11:00 67 66.6667 51.579 52.0833 98.3413 20.85
$data['id'] 22-08-24 11:00 67 66.6667 52.822 52.0833 98.4633 20.66
$data['id'] 21-08-24 11:00 61 50 46.4632 50 98.546 20.93
$data['id'] 20-08-24 11:00 59 50 38.9349 52.2727 98.4968 20.54
$data['id'] 19-08-24 11:00 58 50 33.3333 52.2727 98.5942 20.68
$data['id'] 16-08-24 11:00 55 50 26.1984 47.9167 98.7386 20.21
$data['id'] 15-08-24 11:00 52 50 18.0602 43.75 98.8583 20.13
$data['id'] 14-08-24 11:00 50 50 11.041 41.3043 98.9345 19.73
$data['id'] 13-08-24 11:00 51 50 14.3803 43.1818 98.8993 19.805
$data['id'] 12-08-24 11:00 54 50 21.6651 47.7273 98.5491 20.1
$data['id'] 09-08-24 11:00 52 33.3333 25.0709 52.0833 98.21 20.1
$data['id'] 08-08-24 11:00 47 33.3333 12.299 47.9167 97.8047 20.01
$data['id'] 07-08-24 11:00 44 16.6667 12.772 50 98.2632 20.04
$data['id'] 06-08-24 11:00 43 16.6667 9.36611 47.7273 98.323 19.545
$data['id'] 05-08-24 11:00 35 0 0 43.1818 98.4783 19.05
$data['id'] 02-08-24 11:00 45 33.3333 0 47.9167 99.2996 19.355
$data['id'] 01-08-24 11:00 36 50 2.65253 47.9167 44.0494 19.85
$data['id'] 31-07-24 11:00 40 50 14.3236 50 46.1663 20.93
$data['id'] 30-07-24 11:00 36 50 2.91779 47.7273 44.0124 20.69
$data['id'] 29-07-24 11:00 38 50 10.0796 50 45.0479 20.76
$data['id'] 26-07-24 11:00 37 50 5.30506 50 44.1958 20.76
$data['id'] 25-07-24 11:00 35 50 0.265258 45.6522 45.1278 20.77
$data['id'] 24-07-24 11:00 35 50 1.85676 45.6522 43.5267 20.82
$data['id'] 23-07-24 11:00 34 50 0.831044 43.1818 45.4683 20.53
$data['id'] 22-07-24 11:00 36 50 6.09416 45.2381 46.4182 20.88
$data['id'] 19-07-24 11:00 36 50 3.04711 45.6522 45.3536 20.76
$data['id'] 18-07-24 11:00 38 50 14.1274 45.6522 45.9222 21.19
$data['id'] 17-07-24 11:00 40 50 12.4654 50 47.961 21.29
$data['id'] 16-07-24 11:00 44 33.3333 0 45.2381 99.4718 21.11
$data['id'] 15-07-24 11:00 43 50 28.2549 50 45.8334 21.71
$data['id'] 12-07-24 11:00 37 33.3333 24.0997 45.6522 45.9656 21.59
$data['id'] 11-07-24 11:00 30 33.3333 6.09416 41.3043 41.3859 21.01
$data['id'] 10-07-24 11:00 22 16.6667 0 32.6087 40.9925 20.83
$data['id'] 09-07-24 11:00 26 33.3333 0.623067 34.0909 38.6207 20.72
$data['id'] 08-07-24 11:00 32 33.3333 12.4611 40.4762 41.9314 21.21
$data['id'] 05-07-24 11:00 31 33.3333 15.8879 36.9565 41.6235 21.48
$data['id'] 04-07-24 11:00 31 33.3333 15.2648 36.9565 41.362 21.7
$data['id'] 03-07-24 11:00 30 33.3333 12.7726 32.6087 42.3709 21.58
$data['id'] 02-07-24 11:00 22 16.6667 1.2862 30.9524 41.3675 21.12
$data['id'] 01-07-24 11:00 31 33.3333 13.5048 35.7143 43.9189 21.32
$data['id'] 28-06-24 11:00 28 16.6667 11.5756 39.5833 45.1148 21.4
$data['id'] 27-06-24 11:00 25 16.6667 0.335514 39.5833 43.7969 21.24
$data['id'] 26-06-24 11:00 25 16.6667 0 36.9565 49.2879 21.39
$data['id'] 25-06-24 11:00 40 16.6667 4.10256 40.4762 99.5438 21.9
$data['id'] 24-06-24 11:00 42 16.6667 11.2821 43.1818 99.3032 22.22
$data['id'] 21-06-24 11:00 41 16.6667 8.97437 39.5833 99.6331 21.99
$data['id'] 20-06-24 11:00 41 16.6667 9.99999 39.5833 99.8864 22.38
$data['id'] 19-06-24 11:00 42 16.6667 12.0513 41.3043 99.8973 22.02
$data['id'] 18-06-24 11:00 20 0 0 34.0909 48.1579 22.11
$data['id'] 17-06-24 11:00 19 0 0 29.5455 47.9753 21.81
$data['id'] 14-06-24 11:00 27 33.3333 0 31.25 47.1091 21.86
$data['id'] 13-06-24 11:00 28 33.3333 0 35.4167 46.5526 22.19
$data['id'] 12-06-24 11:00 34 50 0 38.6364 48.6056 22.58
$data['id'] 07-06-24 11:00 37 50 7.08663 47.9167 46.6536 23.43
$data['id'] 06-06-24 11:00 35 50 0 43.75 46.7067 23.5
$data['id'] 05-06-24 11:00 37 50 10.2362 45.6522 45.6827 23.35
$data['id'] 04-06-24 11:00 44 50 38.189 47.7273 42.8781 23.88
$data['id'] 03-06-24 11:00 48 50 48.8189 52.2727 44.3417 24.37
$data['id'] 31-05-24 11:00 44 50 35.0394 50 43.1538 24.1
$data['id'] 30-05-24 11:00 38 50 19.2913 47.7273 38.8837 23.92
$data['id'] 29-05-24 11:00 33 50 1.77782 43.1818 38.0055 23.21
$data['id'] 28-05-24 11:00 40 50 23.1111 50 38.2334 23.95
$data['id'] 27-05-24 11:00 39 50 20.4445 47.5 39.1514 23.97
$data['id'] 24-05-24 11:00 37 50 13.3334 47.7273 39.4159 23.82
$data['id'] 23-05-24 11:00 39 50 19.5556 47.7273 39.0561 23.71
$data['id'] 22-05-24 11:00 39 50 22.2222 47.7273 39.0765 23.92
$data['id'] 21-05-24 11:00 43 50 28.6652 50 43.6897 24.09
$data['id'] 20-05-24 11:00 50 50 49.8948 57.5 44.7355 24.23
$data['id'] 17-05-24 11:00 48 50 37.2632 61.3636 44.2355 24.24
$data['id'] 16-05-24 11:00 46 50 21.6843 56.8182 57.2658 24.29
$data['id'] 15-05-24 11:00 48 50 28.4211 56.8182 57.1087 23.85
$data['id'] 14-05-24 11:00 47 50 31.3685 59.5238 47.3197 24.13
$data['id'] 13-05-24 11:00 44 50 24.6316 57.5 47.3656 23.97
$data['id'] 10-05-24 11:00 45 50 33.8947 52.2727 47.042 23.87
$data['id'] 09-05-24 11:00 38 50 8.21059 47.7273 47.4411 23.7
$data['id'] 08-05-24 11:00 41 50 14.9474 52.2727 47.4743 23.56
$data['id'] 07-05-24 11:00 45 50 29.6842 54.7619 47.5576 23.99
$data['id'] 06-05-24 11:00 52 50 54.1053 57.5 47.2911 24.45
$data['id'] 03-05-24 11:00 43 33.3333 36.0001 56.8182 47.3194 24.34
$data['id'] 02-05-24 11:00 41 33.3333 25.0527 61.3636 47.908 24.41
$data['id'] 30-04-24 11:00 40 33.3333 19.579 59.5238 48.2979 23.55
$data['id'] 29-04-24 11:00 42 33.3333 27.579 62.5 48.356 24.03
$data['id'] 26-04-24 11:00 41 33.3333 24.2106 61.3636 48.3277 23.74
$data['id'] 25-04-24 11:00 36 33.3333 9.10542 56.8182 48.3876 23.58
$data['id'] 24-04-24 11:00 38 33.3333 13.6364 59.5238 48.2736 23.65
$data['id'] 23-04-24 11:00 38 33.3333 15.8308 57.5 48.7802 23.45
$data['id'] 22-04-24 11:00 39 33.3333 15.2038 60 48.9638 24.18
$data['id'] 19-04-24 11:00 38 33.3333 9.24765 61.3636 48.7868 23.84
$data['id'] 18-04-24 11:00 40 33.3333 14.8903 65.9091 48.7346 23.88
$data['id'] 17-04-24 11:00 46 50 17.0846 69.0476 48.9418 23.6
$data['id'] 16-04-24 11:00 46 50 18.3386 67.5 49.6723 23.83
$data['id'] 15-04-24 11:00 67 50 72.257 72.5 76.0788 25.44
$data['id'] 12-04-24 11:00 69 50 89.8119 70.4545 69.1688 25.68
$data['id'] 11-04-24 11:00 70 50 82.6019 75 74.1493 25.52
$data['id'] 10-04-24 11:00 73 66.6667 86.3637 73.8095 65.8039 25.63
$data['id'] 09-04-24 11:00 65 50 73.1975 72.5 67.2483 25.72
$data['id'] 08-04-24 11:02 63 50 62.2257 72.5 68.2676 25.61
$data['id'] 05-04-24 11:00 63 50 60.9718 73.8095 68.5886 25.23
$data['id'] 04-04-24 11:00 67 50 74.1379 75 70.6701 25.66
$data['id'] 03-04-24 11:00 60 50 57.21 69.0476 64.7926 25.51
$data['id'] 02-04-24 11:00 71 66.6667 82.6019 72.5 63.0981 25.55
$data['id'] 28-03-24 11:00 67 66.6667 70.0627 68.1818 65.2951 25.5
$data['id'] 27-03-24 11:00 57 50 54.232 59.0909 66.1415 25.475
$data['id'] 26-03-24 11:00 62 66.6667 53.4483 63.6364 65.2358 25.185
$data['id'] 25-03-24 11:00 61 66.6667 50.6269 61.9048 65.1201 25.17
$data['id'] 22-03-24 11:00 56 50 54.3887 59.0909 63.9401 24.955
$data['id'] 21-03-24 11:00 54 50 44.5141 59.0909 64.9127 24.91
$data['id'] 20-03-24 11:00 50 50 32.7586 54.5455 65.77 24.485
$data['id'] 19-03-24 11:00 45 50 21.3166 45.4545 64.5975 24.405
$data['id'] 18-03-24 11:00 50 50 41.8496 47.619 61.9598 24.37
$data['id'] 15-03-24 11:00 47 50 34.1693 45.4545 60.0301 24.225
$data['id'] 14-03-24 10:00 50 50 41.8496 50 58.9735 24.475
$data['id'] 13-03-24 10:00 45 50 30.0941 45.4545 58.1887 24.73
$data['id'] 12-03-24 10:02 47 50 31.5047 45.4545 63.2327 24.64
$data['id'] 11-03-24 10:02 39 50 13.3229 38.0952 58.1462 23.9
$data['id'] 08-03-24 10:00 41 50 16.1442 40.9091 58.2838 23.87
$data['id'] 07-03-24 10:00 32 33.3333 0 36.3636 60.6041 23.8
$data['id'] 06-03-24 10:00 31 33.3333 6.26962 36.3636 49.3459 23.425
$data['id'] 05-03-24 10:00 29 33.3333 0 36.3636 49.3813 23.38
$data['id'] 04-03-24 12:00 30 33.3333 0 38.0952 49.1886 23.76
$data['id'] 01-03-24 12:00 30 33.3333 0 40.9091 48.8086 24.09
$data['id'] 29-02-24 12:00 31 33.3333 0 43.75 48.758 24.195
$data['id'] 28-02-24 12:00 33 33.3333 6.60004 45.6522 48.7909 24.115
$data['id'] 27-02-24 12:00 39 50 9.62675 47.7273 48.7843 24.4
$data['id'] 26-02-24 12:00 31 33.3333 0 43.1818 48.7317 24.005
$data['id'] 23-02-24 12:00 39 50 10 47.9167 48.8866 24.26
$data['id'] 22-02-24 12:00 41 50 21.0714 47.9167 48.8815 24.385
$data['id'] 21-02-24 12:00 46 50 31.1973 54.3478 48.8524 24.395
$data['id'] 20-02-24 12:00 46 50 34.0641 52.2727 48.5163 24.415
$data['id'] 19-02-24 12:00 51 50 51.6447 56.8182 48.8742 24.89
$data['id'] 16-02-24 12:00 56 50 70.5592 56.25 49.13 25.645
$data['id'] 15-02-24 12:00 52 50 59.6405 52.0833 49.1872 25.19
$data['id'] 14-02-24 12:00 53 50 64.2961 50 49.1761 25.19
$data['id'] 13-02-24 12:00 61 50 88.799 52.2727 53.4024 25.375
$data['id'] 12-02-24 12:00 70 66.6667 100 61.3636 53.7272 26.55
$data['id'] 09-02-24 12:00 68 66.6667 99.7452 52.0833 54.044 26.495
$data['id'] 08-02-24 12:00 67 66.6667 91.3706 52.0833 61.2867 26.435
$data['id'] 07-02-24 12:00 58 50 71.8987 50 63.8079 25.175
$data['id'] 06-02-24 12:00 60 50 72.5219 52.2727 66.6856 25.555
$data['id'] 05-02-24 12:00 63 50 83.3902 52.2727 67.5306 25.01
$data['id'] 02-02-24 12:00 64 50 87.7133 52.0833 67.5175 25.705
$data['id'] 01-02-24 12:00 64 50 85.6655 54.3478 67.7951 25.53
$data['id'] 31-01-24 12:00 64 50 91.6666 52.2727 66.0085 25.65
$data['id'] 30-01-24 12:00 60 50 78.9583 45.2381 66.5665 25.365
$data['id'] 29-01-24 12:00 63 50 84.6539 54.7619 66.1272 25.355
$data['id'] 26-01-24 12:00 62 50 86.3322 47.7273 65.6764 25.425
$data['id'] 25-01-24 12:00 61 50 84.3203 45.2381 66.1043 25.39
$data['id'] 24-01-24 12:02 62 50 82.6522 47.5 68.2338 25.425
$data['id'] 23-01-24 12:02 59 50 73.8949 44.7368 70.9734 24.895
$data['id'] 22-01-24 12:00 58 50 72.3103 39.4737 70.8768 24.615
$data['id'] 19-01-24 12:00 59 50 69.6413 45.2381 74.2504 24.195
$data['id'] 18-01-24 12:00 58 50 68.8907 40.4762 74.2761 24.4
$data['id'] 17-01-24 12:00 47 33.3333 63.3027 37.5 56.4992 24.065
$data['id'] 16-01-24 12:00 48 33.3333 65.1376 39.4737 55.9855 24.215
$data['id'] 15-01-24 12:00 54 50 70.6422 44.7368 51.8882 24.43
$data['id'] 12-01-24 12:00 50 33.3333 67.4958 50 51.9774 24.375
$data['id'] 11-01-24 12:00 51 33.3333 69.3201 50 52.5954 24.295
$data['id'] 10-01-24 12:00 59 50 77.8607 57.5 53.2325 24.78
$data['id'] 09-01-24 12:00 64 66.6667 81.3433 55.2632 56.0515 24.89
$data['id'] 08-01-24 12:00 65 66.6667 84.0796 55.2632 56.7202 25.415
$data['id'] 05-01-24 12:00 65 66.6667 81.4262 59.5238 55.8052 25.425
$data['id'] 04-01-24 12:14 72 83.3333 89.7181 59.5238 57.0299 25.54
$data['id'] 03-01-24 12:00 66 66.6667 83.9967 57.5 56.6355 25.27
$data['id'] 02-01-24 12:00 78 100 93.9469 60.5263 58.9482 25.81
$data['id'] 29-12-23 12:00 79 100 93.3665 64.2857 59.8119 25.63
$data['id'] 28-12-23 12:00 80 100 93.6153 69.0476 59.9462 25.86
$data['id'] 27-12-23 12:00 84 100 97.4295 78.5714 61.0019 26.005
$data['id'] 22-12-23 12:00 84 100 96.0199 80.4348 61.1931 26.08
$data['id'] 21-12-23 12:00 84 100 95.3565 80.4348 61.3793 25.93
$data['id'] 20-12-23 12:00 85 100 99.0879 80.4348 62.6154 26.255
$data['id'] 19-12-23 12:00 86 100 100 84.0909 62.8902 26.165
$data['id'] 18-12-23 12:00 89 100 100 83.3333 75.8328 26.315
$data['id'] 15-12-23 12:00 89 100 100 80.4348 76.0544 25
$data['id'] 14-12-23 12:00 88 100 100 80.4348 75.164 24.705
$data['id'] 13-12-23 12:00 89 100 100 80.4348 77.1369 23.965
$data['id'] 12-12-23 12:00 88 100 100 79.5455 74.8495 24.005
$data['id'] 11-12-23 12:00 86 100 100 78.5714 67.9763 23.945
$data['id'] 08-12-23 12:00 84 100 99.3074 71.7391 67.9214 23.735
$data['id'] 07-12-23 12:00 67 66.6667 92.5208 51.3228 59.3209 23.57
$data['id'] 06-12-23 12:00 71 83.3333 94.7368 51.2583 57.0206 23.585
$data['id'] 05-12-23 12:00 66 66.6667 92.1053 51.3263 56.6807 23.495
$data['id'] 04-12-23 12:00 65 66.6667 90.0277 51.2616 55.2628 23.54

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.