Just what my model is calculating from the data inputs.
I've gone back over multiple financial years worth of daily trade data and calculated the daily % price movements to work of the standard deviation for the period I'm assessing. I've the taken the square root on total trading days in my assessible period and multiplied by the St.Dev for a vol %.
The year lending up to issue was a higher volatility however I took the midpoint at 73%.
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Last
5.0¢ |
Change
0.001(2.04%) |
Mkt cap ! $86.37M |
Open | High | Low | Value | Volume |
4.9¢ | 5.1¢ | 4.9¢ | $119.9K | 2.412M |
Buyers (Bids)
No. | Vol. | Price($) |
---|---|---|
2 | 86483 | 5.0¢ |
Sellers (Offers)
Price($) | Vol. | No. |
---|---|---|
5.1¢ | 75153 | 1 |
View Market Depth
No. | Vol. | Price($) |
---|---|---|
2 | 86483 | 0.050 |
2 | 74629 | 0.049 |
1 | 43478 | 0.048 |
7 | 589792 | 0.046 |
15 | 1129060 | 0.045 |
Price($) | Vol. | No. |
---|---|---|
0.051 | 75153 | 1 |
0.052 | 250000 | 1 |
0.055 | 82510 | 1 |
0.057 | 25000 | 1 |
0.059 | 423800 | 1 |
Last trade - 16.10pm 30/08/2024 (20 minute delay) ? |
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