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ASRNL.AS Stock Data

Download ASRNL.AS GF Data (.xslx)
id Date GF Index Momentum Price Strength Price Breadth Volatility Close Price
$data['id'] 11-02-25 11:00 60 66.6667 90.566 52.2727 32.6355 47.62
$data['id'] 10-02-25 11:00 63 66.6667 99.1913 52.2727 34.4625 48.06
$data['id'] 07-02-25 11:00 62 66.6667 100 47.9167 36.1987 47.96
$data['id'] 06-02-25 11:00 60 66.6667 90.566 47.9167 36.2018 47.92
$data['id'] 05-02-25 11:00 57 66.6667 74.9326 47.7273 38.9792 47.01
$data['id'] 04-02-25 11:00 56 66.6667 71.9676 47.7273 39.2582 47.14
$data['id'] 03-02-25 11:00 58 66.6667 77.8976 50 39.097 47.15
$data['id'] 31-01-25 11:00 61 66.6667 87.6011 54.5455 38.1789 47.62
$data['id'] 30-01-25 11:00 68 83.3333 98.1132 56.5217 36.4876 47.77
$data['id'] 29-01-25 11:00 65 66.6667 100 59.0909 35.4526 47.97
$data['id'] 28-01-25 11:00 65 66.6667 100 55 38.6213 47.53
$data['id'] 27-01-25 11:00 61 66.6667 90.2632 52.381 36.6763 47.27
$data['id'] 24-01-25 11:00 57 66.6667 78.1579 47.619 38.3592 46.63
$data['id'] 23-01-25 11:00 62 66.6667 87.1053 57.1429 37.6193 46.77
$data['id'] 22-01-25 11:00 64 66.6667 93.9474 60 36.6532 46.93
$data['id'] 21-01-25 11:00 63 66.6667 91.579 57.8947 36.7459 47.18
$data['id'] 20-01-25 11:00 70 83.3333 100 63.1579 37.0564 47.25
$data['id'] 17-01-25 11:00 70 83.3333 99.2106 61.9048 36.4367 47.31
$data['id'] 16-01-25 11:00 67 66.6667 100 60 41.7983 47.34
$data['id'] 15-01-25 11:00 66 66.6667 100 60 40.2192 46.85
$data['id'] 14-01-25 11:00 55 50 75.3165 57.8947 37.7056 46.33
$data['id'] 13-01-25 11:00 50 50 62.6582 52.6316 35.9527 45.51
$data['id'] 10-01-25 11:00 56 50 82.595 57.1429 34.9231 45.79
$data['id'] 09-01-25 11:00 53 50 75.3165 52.381 34.4134 46.07
$data['id'] 08-01-25 11:00 47 50 57.2785 50 34.005 45.32
$data['id'] 07-01-25 11:00 50 50 67.0886 52.6316 32.4818 45.95
$data['id'] 06-01-25 11:00 47 50 61.076 44.7368 35.8412 45.71
$data['id'] 03-01-25 11:00 52 50 68.9874 47.5 42.938 45.7
$data['id'] 02-01-25 11:00 50 50 62.6582 45.2381 43.2923 45.7
$data['id'] 31-12-24 11:00 49 50 56.962 47.5 41.5786 45.78
$data['id'] 30-12-24 11:00 47 50 52.8482 44.7368 43.9977 45.2
$data['id'] 24-12-24 11:00 40 33.3333 40.5063 43.1818 43.3732 44.67
$data['id'] 23-12-24 11:00 42 50 31.3292 40.4762 49.115 44.55
$data['id'] 20-12-24 11:00 46 33.3333 11.7088 41.3043 99.577 44.42
$data['id'] 19-12-24 11:00 48 33.3333 20.8861 41.3043 99.6445 44.39
$data['id'] 18-12-24 11:00 53 50 27.9763 36.9565 99.8717 44.56
$data['id'] 17-12-24 11:00 54 50 31.25 38.6364 99.7523 44.265
$data['id'] 16-12-24 11:00 49 50 59.5238 40.4762 49.4204 44.73
$data['id'] 13-12-24 11:00 53 50 64.3454 50 50.1698 45.57
$data['id'] 12-12-24 11:00 51 50 61.2814 45.6522 50.3434 45.2
$data['id'] 11-12-24 11:00 55 50 69.6379 50 50.5889 45.51
$data['id'] 10-12-24 11:00 56 50 71.3092 50 52.8455 45.57
$data['id'] 09-12-24 11:00 59 50 86.0724 50 52.5755 45.9
$data['id'] 06-12-24 11:00 63 50 97.2145 54.3478 52.4998 46.23
$data['id'] 05-12-24 11:00 64 50 100 54.3478 52.2925 46.71
$data['id'] 04-12-24 11:00 63 50 100 50 52.1775 46.04
$data['id'] 03-12-24 11:00 57 50 77.8627 52.2727 51.267 44.99
$data['id'] 02-12-24 11:00 54 50 68.7023 50 51.2588 45.11
$data['id'] 29-11-24 11:00 49 50 51.9084 43.75 50.696 45.2
$data['id'] 28-11-24 11:00 52 50 63.2107 43.75 53.3811 44.62
$data['id'] 27-11-24 11:00 59 50 50.5017 41.3043 96.5711 44.36
$data['id'] 26-11-24 11:00 60 50 97.9934 43.1818 52.4673 44.6
$data['id'] 25-11-24 11:00 61 50 97.5439 47.7273 52.3999 45.91
$data['id'] 22-11-24 11:00 54 50 72.1854 41.3043 52.7093 45.06
$data['id'] 21-11-24 11:00 48 50 57.2849 35.4167 52.7358 44.87
$data['id'] 20-11-24 11:00 56 50 82.1193 41.3043 52.5276 44.51
$data['id'] 19-11-24 11:00 55 50 80.7948 38.6364 52.6923 44.99
$data['id'] 18-11-24 11:00 60 50 100 38.6364 52.6359 45.59
$data['id'] 15-11-24 11:00 52 50 71.6846 37.5 52.0687 44.92
$data['id'] 14-11-24 11:00 56 50 44.0861 33.3333 98.3997 44.36
$data['id'] 13-11-24 11:00 55 50 41.9355 30.4348 97.8966 43.57
$data['id'] 12-11-24 11:00 52 50 79.5699 31.8182 50.2109 43.88
$data['id'] 11-11-24 11:00 59 50 100 36.3636 49.8198 45.42
$data['id'] 08-11-24 11:00 55 50 83.0326 41.6667 49 44.85
$data['id'] 07-11-24 11:00 60 50 100 41.6667 50.1195 45.24
$data['id'] 06-11-24 11:00 60 50 100 43.4783 50.0296 45.05
$data['id'] 05-11-24 11:00 56 50 81.763 45.4545 48.9638 45.12
$data['id'] 04-11-24 11:00 56 50 84.1945 43.1818 48.7977 45.23
$data['id'] 01-11-24 11:00 39 50 34.0426 41.6667 32.4858 45.48
$data['id'] 31-10-24 11:00 37 50 25.4743 41.6667 33.9745 43.64
$data['id'] 30-10-24 11:00 40 50 30.6233 43.4783 36.8599 43.82
$data['id'] 29-10-24 11:00 50 50 67.4797 50 34.5564 44.29
$data['id'] 28-10-24 11:00 44 50 48.7805 47.619 31.7974 44.81
$data['id'] 25-10-24 11:00 45 50 48.7805 52.1739 30.9415 44.14
$data['id'] 24-10-24 11:00 46 50 57.4526 47.8261 32.6317 44.47
$data['id'] 23-10-24 11:00 45 50 50.6775 50 31.554 44.41
$data['id'] 22-10-24 11:00 47 50 59.0786 50 29.6376 44.47
$data['id'] 21-10-24 11:00 52 50 71.5448 57.1429 30.8643 45.03
$data['id'] 18-10-24 11:00 50 50 66.6667 52.2727 32.1788 45.13
$data['id'] 17-10-24 11:00 47 50 58.8076 50 29.9925 44.99
$data['id'] 16-10-24 11:00 44 50 44.4169 47.7273 36.4341 44.32
$data['id'] 15-10-24 11:00 49 50 61.7866 52.2727 35.9123 44.46
$data['id'] 14-10-24 11:00 45 50 46.8983 50 35.6539 44.41
$data['id'] 11-10-24 11:00 43 50 39.7023 50 35.4628 44.09
$data['id'] 10-10-24 11:00 43 50 36.7397 50 37.6635 43.78
$data['id'] 09-10-24 11:00 35 33.3333 27.0455 45.6522 36.7722 43.76
$data['id'] 08-10-24 11:00 34 33.3333 19.7728 43.1818 40.1389 43.48
$data['id'] 07-10-24 11:00 41 50 28.1818 45.2381 43.1314 43.55
$data['id'] 04-10-24 11:00 42 50 26.8182 50 42.3156 43.67
$data['id'] 03-10-24 11:00 40 50 27.7273 45.6522 40.2769 43.19
$data['id'] 02-10-24 11:00 45 50 40.6818 50 42.6039 43.77
$data['id'] 01-10-24 11:00 47 50 41.8182 52.2727 46.3548 44
$data['id'] 30-09-24 11:00 48 50 46.8182 52.2727 46.1609 43.93
$data['id'] 27-09-24 11:00 44 33.3333 48.6364 47.9167 46.2283 44.42
$data['id'] 26-09-24 11:00 41 33.3333 43.6364 43.75 45.905 44.13
$data['id'] 25-09-24 11:00 37 33.3333 30.9091 41.3043 45.0346 43.78
$data['id'] 24-09-24 11:00 39 33.3333 35.9091 43.1818 46.6444 43.92
$data['id'] 23-09-24 11:00 31 16.6667 20.2273 43.1818 46.9191 43.17
$data['id'] 20-09-24 11:00 39 33.3333 32.7273 43.75 47.6308 43.31
$data['id'] 19-09-24 11:00 37 33.3333 25 47.9167 44.7661 43.69

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.