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BESI.AS Stock Data

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id Date GF Index Momentum Price Strength Price Breadth Volatility Close Price
$data['id'] 11-02-25 11:00 29 16.6667 19.0597 34.0909 47.8564 115.75
$data['id'] 10-02-25 11:00 30 16.6667 21.9822 34.0909 48.1565 116.6
$data['id'] 07-02-25 11:00 28 16.6667 23.6341 27.0833 47.1071 115.1
$data['id'] 06-02-25 11:00 30 16.6667 26.3024 31.25 47.1474 118.3
$data['id'] 05-02-25 11:00 31 16.6667 28.5012 34.0909 47.68 119.4
$data['id'] 04-02-25 11:00 33 16.6667 35.8722 34.0909 47.3565 120.4
$data['id'] 03-02-25 11:00 34 16.6667 33.6609 38.6364 49.7998 121.45
$data['id'] 31-01-25 11:00 49 16.6667 45.086 38.6364 97.4436 125.15
$data['id'] 30-01-25 11:00 47 16.6667 40.172 36.9565 97.9616 122.7
$data['id'] 29-01-25 11:00 48 16.6667 45.8231 34.0909 95.7636 122.5
$data['id'] 28-01-25 11:00 55 50 42.5061 32.5 98.2124 120.6
$data['id'] 27-01-25 11:00 53 50 36.1179 30.9524 95.7322 125.25
$data['id'] 24-01-25 11:00 55 66.6667 78.2555 35.7143 41.5068 136
$data['id'] 23-01-25 11:00 56 66.6667 83.7838 35.7143 38.1929 138.3
$data['id'] 22-01-25 11:00 58 66.6667 93.7346 37.5 36.3081 145.4
$data['id'] 21-01-25 11:00 64 83.3333 99.7763 39.4737 35.93 143.9
$data['id'] 20-01-25 11:00 66 83.3333 99.6728 44.7368 39.2062 146.65
$data['id'] 17-01-25 11:00 66 83.3333 99.5763 45.2381 39.6424 147.7
$data['id'] 16-01-25 11:00 67 83.3333 100 47.5 40.6922 147.8
$data['id'] 15-01-25 11:00 59 66.6667 86.4782 47.5 35.9459 142
$data['id'] 14-01-25 11:00 64 83.3333 88.8343 50 35.9602 139
$data['id'] 13-01-25 11:00 64 83.3333 84.4294 50 39.1194 141
$data['id'] 10-01-25 11:00 71 100 94.4684 54.7619 35.9047 144.25
$data['id'] 09-01-25 11:00 66 83.3333 92.6245 54.7619 36.6445 144.35
$data['id'] 08-01-25 11:00 74 100 100 62.5 35.0976 144.65
$data['id'] 07-01-25 11:00 74 100 100 60.5263 37.9735 146.85
$data['id'] 06-01-25 11:00 72 100 100 60.5263 30.4146 142.55
$data['id'] 03-01-25 11:00 70 83.3333 100 67.5 32.8643 135.3
$data['id'] 02-01-25 11:00 70 83.3333 98.5139 69.0476 32.6519 135.85
$data['id'] 31-12-24 11:00 67 66.6667 98.7841 72.5 31.918 132.3
$data['id'] 30-12-24 11:00 72 83.3333 97.4331 76.3158 31.9877 133.4
$data['id'] 24-12-24 11:00 77 100 100 75 33.752 134.95
$data['id'] 23-12-24 11:00 72 83.3333 99.8512 73.8095 34.5713 133.4
$data['id'] 20-12-24 11:00 69 83.3333 90.479 71.7391 33.9091 131.8
$data['id'] 19-12-24 11:00 69 83.3333 88.6938 67.3913 36.9622 127.15
$data['id'] 18-12-24 11:00 75 100 100 67.3913 33.2323 131.5
$data['id'] 17-12-24 11:00 74 100 100 65.9091 33.9421 128
$data['id'] 16-12-24 11:00 70 83.3333 100 64.2857 36.3745 127.65
$data['id'] 13-12-24 11:00 70 83.3333 100 58.6957 39.849 127.5
$data['id'] 12-12-24 11:00 68 83.3333 96.3491 54.3478 39.866 124.55
$data['id'] 11-12-24 11:00 69 83.3333 96.6204 54.3478 43.6034 126.85
$data['id'] 10-12-24 11:00 76 100 100 59.5238 46.2436 125.35
$data['id'] 09-12-24 11:00 76 100 100 59.5238 46.1572 125.5
$data['id'] 06-12-24 11:00 71 83.3333 99.7926 58.6957 46.1402 123.7
$data['id'] 05-12-24 11:00 66 66.6667 94.9706 58.6957 46.5481 121.7
$data['id'] 04-12-24 11:00 69 66.6667 100 63.0435 48.8852 121.65
$data['id'] 03-12-24 11:00 64 66.6667 84.723 61.3636 46.9783 115.5
$data['id'] 02-12-24 11:00 61 66.6667 76.1782 54.7619 47.2618 114.85
$data['id'] 29-11-24 11:00 58 66.6667 66.8565 52.0833 47.0184 113.65
$data['id'] 28-11-24 11:00 63 66.6667 83.4283 52.0833 50.6264 111
$data['id'] 27-11-24 11:00 56 66.6667 57.7939 50 50.403 108.4
$data['id'] 26-11-24 11:00 64 83.3333 71.7763 52.2727 50.755 111.75
$data['id'] 25-11-24 11:00 68 83.3333 84.723 56.8182 50.7545 112.9
$data['id'] 22-11-24 11:00 58 83.3333 53.9099 50 48.5192 113.95
$data['id'] 21-11-24 11:00 51 66.6667 41.74 47.9167 48.5338 107.7
$data['id'] 20-11-24 11:00 61 83.3333 56.2403 54.3478 51.5829 107.75
$data['id'] 19-11-24 11:00 65 66.6667 43.5525 52.2727 97.5552 108.05
$data['id'] 18-11-24 11:00 59 66.6667 67.1155 52.2727 50.9919 110.8
$data['id'] 15-11-24 11:00 69 83.3333 86.2765 56.25 50.5085 115.05
$data['id'] 14-11-24 11:00 68 83.3333 87.3751 56.25 47.6998 118.15
$data['id'] 13-11-24 11:00 61 66.6667 78.9584 54.3478 45.9733 110.7
$data['id'] 12-11-24 11:00 67 83.3333 82.2144 56.8182 46.2815 114.4
$data['id'] 11-11-24 11:00 56 50 62.4248 56.8182 56.9548 109.9
$data['id'] 08-11-24 11:00 52 50 48.0135 56.25 57.5949 108.3
$data['id'] 07-11-24 11:00 52 33.3333 26.8808 54.1667 94.2069 108
$data['id'] 06-11-24 11:00 50 33.3333 23.7109 52.1739 93.8838 102.5
$data['id'] 05-11-24 11:00 46 33.3333 11.2426 47.7273 94.2277 101.95
$data['id'] 04-11-24 11:00 43 33.3333 1.43701 45.4545 93.882 100.65
$data['id'] 01-11-24 11:00 40 16.6667 4.74242 45.8333 94.9061 101.55
$data['id'] 31-10-24 11:00 38 16.6667 0 41.6667 95.6955 97.66
$data['id'] 30-10-24 11:00 40 16.6667 7.28197 43.4783 95.7984 101.85
$data['id'] 29-10-24 11:00 42 16.6667 17.4429 40.9091 95.5996 104.25
$data['id'] 28-10-24 11:00 50 33.3333 25.6986 47.619 95.1621 104.95
$data['id'] 25-10-24 11:00 46 16.6667 24.4285 47.8261 95.195 105.8
$data['id'] 24-10-24 11:00 44 16.6667 10.4572 52.1739 97.2131 105.3
$data['id'] 23-10-24 11:00 41 16.6667 2.41321 50 96.6426 100.85
$data['id'] 22-10-24 11:00 43 16.6667 7.91703 54.5455 96.6356 101.6
$data['id'] 21-10-24 11:00 45 16.6667 14.2676 52.381 96.9068 100.95
$data['id'] 18-10-24 11:00 45 16.6667 20.8298 50 93.6199 103.85
$data['id'] 17-10-24 11:00 41 16.6667 8.12873 47.8261 95.2061 100.8
$data['id'] 16-10-24 11:00 40 16.6667 0 50 93.8836 100.025
$data['id'] 15-10-24 11:00 40 33.3333 31.8988 50 45.3318 101.25
$data['id'] 14-10-24 11:00 41 33.3333 37.4684 52.381 41.7524 113.65
$data['id'] 11-10-24 11:00 38 33.3333 26.3291 52.1739 41.7803 109.6
$data['id'] 10-10-24 11:00 38 33.3333 26.3291 52.1739 42.104 108.65
$data['id'] 09-10-24 11:00 37 16.6667 36.7089 52.1739 43.5881 111.65
$data['id'] 08-10-24 11:00 37 33.3333 24.3038 47.7273 46.2462 110.7
$data['id'] 07-10-24 11:00 41 33.3333 35.6962 50 45.3754 111.1
$data['id'] 04-10-24 11:00 45 33.3333 47.5949 54.3478 44.7397 113.1
$data['id'] 03-10-24 11:00 37 33.3333 20.3252 50 48.0436 112.65
$data['id'] 02-10-24 11:00 37 33.3333 16.5165 50 48.2228 113.45
$data['id'] 01-10-24 11:00 38 33.3333 21.9219 52.2727 46.7968 110.1
$data['id'] 30-09-24 11:00 56 50 20.9209 56.8182 99.8185 113.15
$data['id'] 27-09-24 11:00 56 50 20.02 56.25 99.8528 113.65
$data['id'] 26-09-24 11:00 55 50 20.1155 52.0833 98.3546 113
$data['id'] 25-09-24 11:00 45 33.3333 5.16432 45.6522 99.7701 109.8
$data['id'] 24-09-24 11:00 47 33.3333 8.75472 47.7273 99.3353 108.4
$data['id'] 23-09-24 11:00 40 16.6667 4.45283 43.1818 99.5534 107.05
$data['id'] 20-09-24 11:00 34 33.3333 16.0755 43.75 45.3711 112.05
$data['id'] 19-09-24 11:00 35 33.3333 16.6038 47.9167 42.7324 116.8
$data['id'] 18-09-24 11:00 29 16.6667 12.5283 45.6522 41.2827 112.1
$data['id'] 17-09-24 11:00 29 16.6667 12.5283 47.7273 40.9349 113.2
$data['id'] 16-09-24 11:00 34 33.3333 14.1887 50 40.509 111.4
$data['id'] 13-09-24 11:00 31 16.6667 12.4528 56.25 40.2699 113.2
$data['id'] 12-09-24 11:00 37 33.3333 15.7736 56.25 45.2533 111.9
$data['id'] 11-09-24 11:00 28 16.6667 5.0566 54.3478 38.948 107.4
$data['id'] 09-09-24 11:00 29 16.6667 4.07547 56.8182 38.5638 104.65
$data['id'] 06-09-24 11:00 23 0 1.90549 56.25 37.5087 103.85
$data['id'] 05-09-24 11:00 25 0 4.57317 60.4167 36.9641 107
$data['id'] 04-09-24 11:00 30 16.6667 6.93597 63.0435 37.1288 110.45
$data['id'] 03-09-24 11:00 37 33.3333 18.5213 65.9091 32.2772 112.1
$data['id'] 02-09-24 11:00 39 33.3333 21.9512 70.4545 33.1053 117.95
$data['id'] 30-08-24 11:00 38 33.3333 21.875 64.5833 32.9119 118
$data['id'] 29-08-24 11:00 53 33.3333 20.1982 60.4167 99.723 122.15
$data['id'] 28-08-24 11:00 54 33.3333 23.0183 63.0435 98.7366 118.85
$data['id'] 27-08-24 11:00 53 33.3333 19.5122 61.3636 98.3657 117.7
$data['id'] 26-08-24 11:00 59 50 23.1707 65.9091 98.3099 119.2
$data['id'] 23-08-24 11:00 57 50 21.6463 60.4167 97.2289 119.2
$data['id'] 22-08-24 11:00 60 50 29.0396 64.5833 97.7625 122.55
$data['id'] 21-08-24 11:00 52 33.3333 26.9817 63.0435 85.9818 123.65
$data['id'] 20-08-24 11:00 52 33.3333 29.8018 65.9091 82.7881 122.6
$data['id'] 19-08-24 11:00 50 33.3333 25.2287 61.3636 82.8217 122.05
$data['id'] 16-08-24 11:00 49 33.3333 26.0671 56.25 82.0258 121.55
$data['id'] 15-08-24 11:00 42 16.6667 19.0549 52.0833 82.9482 120.75
$data['id'] 14-08-24 11:00 45 33.3333 18.064 50 82.5282 115.95
$data['id'] 13-08-24 11:00 39 16.6667 16.5396 43.1818 81.2684 115.2
$data['id'] 12-08-24 11:00 40 16.6667 15.625 47.7273 81.6508 115.4
$data['id'] 09-08-24 11:00 40 16.6667 14.253 47.9167 81.6878 112.3
$data['id'] 08-08-24 11:00 37 16.6667 9.83231 43.75 81.6962 112.55
$data['id'] 07-08-24 11:00 39 16.6667 12.5762 45.6522 82.0742 114.35
$data['id'] 06-08-24 11:00 32 0 5.18293 43.1818 83.0818 109
$data['id'] 05-08-24 11:00 29 0 0 34.0909 84.3651 108
$data['id'] 02-08-24 11:00 31 0 0 39.5833 85.8522 105
$data['id'] 01-08-24 11:00 32 0 1.03577 43.75 86.7704 115.2
$data['id'] 31-07-24 11:00 34 0 5.74387 45.6522 86.4112 119.6
$data['id'] 30-07-24 11:00 33 0 5.58823 47.7273 82.6705 117.3
$data['id'] 29-07-24 11:00 31 0 0 45.2381 82.2914 119.15
$data['id'] 26-07-24 11:00 34 0 6.80894 50 82.859 123.35
$data['id'] 25-07-24 11:00 34 0 0 50 88.1207 120.8
$data['id'] 24-07-24 11:00 49 16.6667 32.0312 54.3478 94.9702 141.5
$data['id'] 23-07-24 11:00 53 50 54.6753 56.8182 52.0363 153
$data['id'] 22-07-24 11:00 61 50 44.026 54.7619 98.0765 151.6
$data['id'] 19-07-24 11:00 66 66.6667 47.6313 54.3478 97.8522 146.55
$data['id'] 18-07-24 11:00 59 66.6667 66.8578 52.1739 50.9031 148.3
$data['id'] 17-07-24 11:00 61 66.6667 79.5872 56.5217 44.5696 156.7
$data['id'] 16-07-24 11:00 71 83.3333 100 61.9048 39.572 168
$data['id'] 15-07-24 11:00 75 100 100 61.9048 39.5477 169.5
$data['id'] 12-07-24 11:00 68 83.3333 92.1218 56.5217 40.3176 168.9
$data['id'] 11-07-24 11:00 77 100 100 65.2174 43.0218 166.75
$data['id'] 10-07-24 11:00 65 66.6667 92.9622 60.8696 42.8424 168.1
$data['id'] 09-07-24 11:00 68 66.6667 96.3235 68.1818 43.0215 165.05
$data['id'] 08-07-24 11:00 79 100 98.5294 71.4286 47.3688 165.7
$data['id'] 05-07-24 11:00 80 100 99.7899 73.913 47.3228 167.65
$data['id'] 04-07-24 11:00 81 100 100 78.2609 47.7909 167.35
$data['id'] 03-07-24 11:00 77 83.3333 100 78.2609 49.0945 168
$data['id'] 02-07-24 11:00 69 66.6667 90.7217 76.1905 42.6226 156.6
$data['id'] 01-07-24 11:00 68 66.6667 88.2732 76.1905 43.0497 155.15
$data['id'] 28-06-24 11:00 67 66.6667 93.8144 66.6667 43.3988 156.2
$data['id'] 27-06-24 11:00 66 66.6667 89.5618 66.6667 44.424 156.15
$data['id'] 26-06-24 11:00 71 83.3333 91.4948 65.2174 47.5598 154.9
$data['id'] 25-06-24 11:00 66 83.3333 72.9381 61.9048 47.6309 153.6
$data['id'] 24-06-24 11:00 67 83.3333 80.0258 59.0909 45.6555 149
$data['id'] 21-06-24 11:00 70 83.3333 87.5 66.6667 44.5186 152.95
$data['id'] 20-06-24 11:00 72 83.3333 97.9381 66.6667 43.9009 156.45
$data['id'] 19-06-24 11:00 70 83.3333 90.3351 63.0435 43.6902 155.6
$data['id'] 18-06-24 11:00 68 83.3333 84.0206 61.3636 43.8231 155.3
$data['id'] 17-06-24 11:00 71 83.3333 91.366 65.9091 44.2485 153.65
$data['id'] 14-06-24 11:00 76 100 96.9072 68.75 41.4958 153.7
$data['id'] 13-06-24 11:00 78 100 100 72.9167 40.7571 158.6
$data['id'] 12-06-24 11:00 77 100 100 70.4545 40.6101 159.25
$data['id'] 07-06-24 11:00 62 66.6667 81.2598 64.5833 35.804 147.55
$data['id'] 06-06-24 11:00 58 66.6667 66.9291 64.5833 34.2551 143.5
$data['id'] 05-06-24 11:00 48 50 50.2362 63.0435 32.3682 139.75
$data['id'] 04-06-24 11:00 45 50 40.4724 61.3636 31.5712 133.25
$data['id'] 03-06-24 11:00 50 66.6667 40.7874 61.3636 31.3754 133.1
$data['id'] 31-05-24 11:00 51 66.6667 47.0866 63.0435 30.6616 134.6
$data['id'] 30-05-24 11:00 57 66.6667 65.6693 68.1818 29.3494 137.6
$data['id'] 29-05-24 11:00 57 66.6667 61.8898 65.9091 36.8005 140.95
$data['id'] 28-05-24 11:00 63 83.3333 63.4646 69.0476 36.693 142.2
$data['id'] 27-05-24 11:00 62 83.3333 62.2047 67.5 38.6885 139.55
$data['id'] 24-05-24 11:00 60 83.3333 57.0079 56.8182 43.7953 140
$data['id'] 23-05-24 11:00 65 83.3333 69.9213 61.3636 45.9196 140.35
$data['id'] 22-05-24 11:00 47 50 31.9444 61.3636 47.7094 139
$data['id'] 21-05-24 11:00 47 50 31.5104 59.5238 47.7237 137.7
$data['id'] 20-05-24 11:00 47 50 30.2951 62.5 47.2884 139.45
$data['id'] 17-05-24 11:00 38 33.3333 23.4375 47.7273 49.3112 135.4
$data['id'] 16-05-24 11:00 39 33.3333 25.3472 47.7273 49.6695 134
$data['id'] 15-05-24 11:00 32 16.6667 18.1424 43.1818 50.2608 133.1
$data['id'] 14-05-24 11:00 35 33.3333 18.316 40.4762 50.0335 131.25
$data['id'] 13-05-24 11:00 36 33.3333 20.3993 42.5 50.0974 130.9
$data['id'] 10-05-24 11:00 35 33.3333 19.618 38.6364 50.9244 134
$data['id'] 09-05-24 11:00 35 33.3333 20.5729 38.6364 49.6536 131.25
$data['id'] 08-05-24 11:00 28 16.6667 10.4167 34.0909 54.487 126.5
$data['id'] 07-05-24 11:00 29 16.6667 12.934 35.7143 51.7695 127.95
$data['id'] 06-05-24 11:00 27 16.6667 9.98264 32.5 52.7449 126.5
$data['id'] 03-05-24 11:00 27 16.6667 4.42708 34.0909 56.2669 124.95
$data['id'] 02-05-24 11:00 27 16.6667 0 34.0909 59.2476 120.1
$data['id'] 30-04-24 11:00 27 16.6667 0 38.0952 55.9212 125.4
$data['id'] 29-04-24 11:00 27 16.6667 0 37.5 55.3092 127.5
$data['id'] 26-04-24 11:00 27 16.6667 0 38.6364 55.4351 130.7
$data['id'] 25-04-24 11:00 33 16.6667 15.7497 43.1818 58.4569 136.65
$data['id'] 24-04-24 11:00 32 16.6667 13.2686 45.2381 55.7617 138.45
$data['id'] 23-04-24 11:00 29 16.6667 4.31499 42.5 55.755 132.95
$data['id'] 22-04-24 11:00 27 16.6667 0 37.5 56.8853 131.35
$data['id'] 19-04-24 11:00 30 33.3333 0 38.6364 49.8652 133.6
$data['id'] 18-04-24 11:00 33 33.3333 10.119 38.6364 50.9843 138.75
$data['id'] 17-04-24 11:00 35 33.3333 15 40.4762 51.2174 143.1
$data['id'] 16-04-24 11:00 32 33.3333 7.49999 37.5 50.1434 144.05
$data['id'] 15-04-24 11:00 36 33.3333 18.3333 42.5 51.5198 141.5
$data['id'] 12-04-24 11:00 39 33.3333 26.1905 47.7273 51.271 143.45
$data['id'] 11-04-24 11:00 38 33.3333 21.5476 47.7273 51.4335 144.4
$data['id'] 10-04-24 11:00 40 33.3333 28.6905 50 48.5684 145.2
$data['id'] 09-04-24 11:00 39 33.3333 31.7857 47.5 43.8572 145.45
$data['id'] 08-04-24 11:02 41 50 37.5 47.5 30.5842 151.65
$data['id'] 05-04-24 11:00 33 33.3333 27.7381 45.2381 29.3878 151.9
$data['id'] 04-04-24 11:00 36 33.3333 35.5952 47.7273 29.277 151.3
$data['id'] 03-04-24 11:00 30 33.3333 20.119 40.4762 29.6282 149.2
$data['id'] 02-04-24 11:00 37 50 27.2619 42.5 28.3915 144.65
$data['id'] 28-03-24 11:00 33 33.3333 24.0534 47.7273 29.1714 141.75
$data['id'] 27-03-24 11:00 32 16.6667 36.6667 47.7273 29.1756 144.1
$data['id'] 26-03-24 11:00 33 16.6667 34.7475 52.2727 29.5668 148.15
$data['id'] 25-03-24 11:00 32 16.6667 31.6161 50 29.9487 142.25
$data['id'] 22-03-24 11:00 33 16.6667 35.0505 52.2727 28.0117 147.05
$data['id'] 21-03-24 11:00 35 16.6667 40.5352 56.8182 26.5952 148.2
$data['id'] 20-03-24 11:00 31 16.6667 24.5788 56.8182 27.2157 139.4
$data['id'] 19-03-24 11:00 34 16.6667 34.4896 61.3636 26.9021 141.5
$data['id'] 18-03-24 11:00 33 16.6667 31.219 59.5238 26.5554 143.25
$data['id'] 15-03-24 11:00 30 16.6667 26.9231 52.2727 26.5418 141.85
$data['id'] 14-03-24 10:00 33 16.6667 28.7968 61.3636 25.8646 140.8
$data['id'] 13-03-24 10:00 32 16.6667 27.3175 61.3636 25.7287 141.6
$data['id'] 12-03-24 10:02 39 50 18.3432 61.3636 26.7555 143.25
$data['id'] 11-03-24 10:02 37 50 15.9763 59.5238 26.069 135.45
$data['id'] 08-03-24 10:00 60 66.6667 73.57 61.3636 39.2559 149.5
$data['id'] 07-03-24 10:00 66 66.6667 93.7025 61.3636 43.2198 177.65
$data['id'] 06-03-24 10:00 64 66.6667 85.9935 61.3636 43.0284 170.7
$data['id'] 05-03-24 10:00 72 83.3333 97.937 65.9091 44.0947 167.6
$data['id'] 04-03-24 12:00 74 83.3333 100 69.0476 44.1829 173.55
$data['id'] 01-03-24 12:00 68 66.6667 97.1322 65.9091 44.1411 168.05
$data['id'] 29-02-24 12:00 69 66.6667 96.5087 68.75 44.2104 167.45
$data['id'] 28-02-24 12:00 71 83.3333 92.1447 67.3913 43.941 166.15
$data['id'] 27-02-24 12:00 74 83.3333 100 70.4545 44.1181 167.35
$data['id'] 26-02-24 12:00 72 83.3333 96.8055 65.9091 44.7621 162.2
$data['id'] 23-02-24 12:00 69 83.3333 81.6666 64.5833 48.265 153.35
$data['id'] 22-02-24 12:00 75 100 100 64.5833 38.8763 163.7
$data['id'] 21-02-24 12:00 69 83.3333 81.9364 63.0435 50.0268 156.45
$data['id'] 20-02-24 12:00 69 83.3333 80.3468 61.3636 51.374 153.25
$data['id'] 19-02-24 12:00 74 83.3333 95.8093 65.9091 53.2137 159.2
$data['id'] 16-02-24 12:00 81 100 100 72.9167 53.353 162.05
$data['id'] 15-02-24 12:00 75 83.3333 92.2137 68.75 55.7623 155.95
$data['id'] 14-02-24 12:00 65 66.6667 80.916 67.3913 48.1885 154.7
$data['id'] 13-02-24 12:00 60 66.6667 65.1908 65.9091 44.88 152.9
$data['id'] 12-02-24 12:00 78 100 97.9971 65.9091 49.3753 158.35
$data['id'] 09-02-24 12:00 75 83.3333 100 68.75 50.6702 159.9
$data['id'] 08-02-24 12:00 71 66.6667 100 68.75 51.2633 153.1
$data['id'] 07-02-24 12:00 69 66.6667 97.6015 63.0435 51.2221 148.95
$data['id'] 06-02-24 12:00 74 83.3333 100 65.9091 49.6103 148.9
$data['id'] 05-02-24 12:00 70 83.3333 82.483 65.9091 50.2118 145.4
$data['id'] 02-02-24 12:00 67 83.3333 76.8707 60.4167 50.3388 142.9
$data['id'] 01-02-24 12:00 66 83.3333 74.1497 58.6957 50.2018 140.55
$data['id'] 31-01-24 12:00 65 83.3333 72.6384 56.8182 49.4866 139.55
$data['id'] 30-01-24 12:00 67 83.3333 79.1531 59.5238 48.3859 142.2
$data['id'] 29-01-24 12:00 66 83.3333 78.7557 54.7619 48.3757 141.25
$data['id'] 26-01-24 12:00 67 83.3333 84.8617 52.2727 48.6186 143.3
$data['id'] 25-01-24 12:00 74 100 99.2647 50 49.8468 148.9
$data['id'] 24-01-24 12:02 75 100 100 52.5 49.6539 147.4
$data['id'] 23-01-24 12:02 70 83.3333 96.0894 50 51.0669 143.35
$data['id'] 22-01-24 12:00 76 100 100 55.2632 50.9075 146.5
$data['id'] 19-01-24 12:00 72 83.3333 100 54.7619 51.3601 144.25
$data['id'] 18-01-24 12:00 68 66.6667 91.0162 54.7619 62.1572 142.7
$data['id'] 17-01-24 12:00 65 66.6667 79.1495 52.5 63.9258 132.95
$data['id'] 16-01-24 12:00 54 33.3333 67.1216 50 66.9781 128.15
$data['id'] 15-01-24 12:00 59 50 71.527 50 67.1045 128.25
$data['id'] 12-01-24 12:00 61 50 73.1521 54.7619 66.4515 128.65
$data['id'] 11-01-24 12:00 60 50 70.4561 54.7619 66.4991 128.5
$data['id'] 10-01-24 12:00 60 50 73.3768 52.5 66.6317 127.4
$data['id'] 09-01-24 12:00 60 50 76.2222 50 66.8097 131.05
$data['id'] 08-01-24 12:00 60 50 75.7501 50 66.1664 129.2
$data['id'] 05-01-24 12:00 61 50 73.3798 54.7619 66.1347 128.65
$data['id'] 04-01-24 12:14 61 50 72.2576 59.5238 63.5248 126.85
$data['id'] 03-01-24 12:00 70 66.6667 85.1737 62.5 67.6776 130.4
$data['id'] 02-01-24 12:00 75 66.6667 96.7255 71.0526 67.9033 135.75
$data['id'] 29-12-23 12:00 73 66.6667 93.9967 64.2857 69.4718 136.4
$data['id'] 28-12-23 12:00 84 100 97.2712 73.8095 67.222 138.3
$data['id'] 27-12-23 12:00 84 100 97.2712 73.8095 67.2012 138.8
$data['id'] 22-12-23 12:00 78 83.3333 92.1775 71.7391 67.0957 137.8
$data['id'] 21-12-23 12:00 72 66.6667 90.2674 67.3913 66.9442 136.9
$data['id'] 20-12-23 12:00 72 66.6667 91.086 67.3913 66.5439 136.25
$data['id'] 19-12-23 12:00 83 100 94.4515 70.4545 67.1968 137.7
$data['id'] 18-12-23 12:00 84 100 98.7266 69.0476 68.8829 137.45
$data['id'] 15-12-23 12:00 85 100 100 71.7391 69.2699 140.95
$data['id'] 14-12-23 12:00 86 100 100 76.087 69.8627 137.45
$data['id'] 13-12-23 12:00 86 100 100 76.087 69.2603 138.05
$data['id'] 12-12-23 12:00 85 100 100 75 68.9346 136.65
$data['id'] 11-12-23 12:00 85 100 100 73.8095 69.2065 135.65
$data['id'] 08-12-23 12:00 86 100 100 76.087 68.9335 133.2
$data['id'] 07-12-23 12:00 80 100 97.3404 55.1587 69.3176 131.1
$data['id'] 06-12-23 12:00 79 100 95.1241 55.0993 69.5798 129.4
$data['id'] 05-12-23 12:00 69 66.6667 89.1401 54.9072 69.0371 127.5
$data['id'] 04-12-23 12:00 82 100 99.4459 54.9801 75.9177 126.6

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.