XLON:ARS
Asiamet Resources Limited Stock Price (Quote)
£1.53
+0 (+0%)
At Close: May 28, 2024
Range | Low Price | High Price | Comment |
---|---|---|---|
30 days | £0.82 | £1.60 | Tuesday, 28th May 2024 ARS.L stock ended at £1.53. During the day the stock fluctuated 0% from a day low at £1.53 to a day high of £1.53. |
90 days | £0.515 | £1.60 | |
52 weeks | £0.500 | £1.63 |
Date | Open | High | Low | Close | Volume |
Sep 15, 2023 | £1.15 | £1.20 | £1.10 | £1.10 | 578 735 |
Sep 14, 2023 | £1.11 | £1.15 | £1.11 | £1.13 | 2 392 966 |
Sep 13, 2023 | £1.10 | £1.18 | £1.10 | £1.18 | 1 105 530 |
Sep 12, 2023 | £1.16 | £1.19 | £1.15 | £1.18 | 398 088 |
Sep 11, 2023 | £1.17 | £1.20 | £1.15 | £1.18 | 977 505 |
Sep 08, 2023 | £1.17 | £1.17 | £1.13 | £1.15 | 2 641 920 |
Sep 07, 2023 | £1.19 | £1.19 | £1.19 | £1.19 | 0 |
Sep 06, 2023 | £1.20 | £1.22 | £1.17 | £1.19 | 1 053 949 |
Sep 05, 2023 | £1.20 | £1.23 | £1.20 | £1.23 | 315 993 |
Sep 04, 2023 | £1.23 | £1.23 | £1.20 | £1.20 | 130 653 |
Sep 01, 2023 | £1.24 | £1.24 | £1.20 | £1.23 | 614 626 |
Aug 31, 2023 | £1.22 | £1.23 | £1.20 | £1.23 | 528 917 |
Aug 30, 2023 | £1.23 | £1.23 | £1.23 | £1.23 | 0 |
Aug 29, 2023 | £1.22 | £1.25 | £1.20 | £1.20 | 1 478 118 |
Aug 25, 2023 | £1.22 | £1.25 | £1.20 | £1.23 | 2 220 241 |
Aug 24, 2023 | £1.25 | £1.28 | £1.20 | £1.20 | 1 985 121 |
Aug 23, 2023 | £1.30 | £1.30 | £1.20 | £1.25 | 329 492 |
Aug 22, 2023 | £1.35 | £1.35 | £1.25 | £1.30 | 2 046 995 |
Aug 21, 2023 | £1.35 | £1.37 | £1.30 | £1.35 | 627 302 |
Aug 18, 2023 | £1.40 | £1.42 | £1.31 | £1.35 | 2 530 650 |
Aug 17, 2023 | £1.40 | £1.42 | £1.35 | £1.40 | 1 543 491 |
Aug 16, 2023 | £1.45 | £1.46 | £1.37 | £1.42 | 3 683 936 |
Aug 15, 2023 | £1.50 | £1.50 | £1.43 | £1.45 | 2 692 541 |
Aug 14, 2023 | £1.53 | £1.63 | £1.45 | £1.45 | 7 134 342 |
Aug 11, 2023 | £1.35 | £1.60 | £1.25 | £1.53 | 9 689 038 |
FAQ
What are historical stock prices?
Historical stock prices refer to a stock’s recorded prices at various past points. These prices include several key figures that help investors and analysts evaluate a stock’s performance over time:
Open: Open price for the trading day.
High: Highest price for the trading day.
Low: Lowest price for the trading day.
Close: Close price for the trading day.
Additionally, historical prices often include:
Volume is the number of shares traded during the day. It indicates how actively a stock was traded and can provide insights into market sentiment and liquidity.
Open: Open price for the trading day.
High: Highest price for the trading day.
Low: Lowest price for the trading day.
Close: Close price for the trading day.
Additionally, historical prices often include:
Volume is the number of shares traded during the day. It indicates how actively a stock was traded and can provide insights into market sentiment and liquidity.
How can I use ARS.L stock historical prices to predict future price movements?
Trend Analysis: Examine the ARS.L stock’s historical trends to identify patterns that might continue.
Moving Averages: Use moving averages to detect potential reversal points.
Momentum Indicators: Apply indicators like RSI or MACD to assess the momentum and strength of price movements.
Volume Analysis: Analyze trading volume alongside price changes to gauge trend strength.
Statistical Methods: Use statistical tools such as regression analysis to model and forecast future prices based on past data.
These techniques can provide insights but should be used with risk management practices to mitigate potential losses.
Moving Averages: Use moving averages to detect potential reversal points.
Momentum Indicators: Apply indicators like RSI or MACD to assess the momentum and strength of price movements.
Volume Analysis: Analyze trading volume alongside price changes to gauge trend strength.
Statistical Methods: Use statistical tools such as regression analysis to model and forecast future prices based on past data.
These techniques can provide insights but should be used with risk management practices to mitigate potential losses.
What impact do stock splits have on historical price data?
When a company performs a stock split, it adjusts the historical price data to reflect the new, lower trading price as if it had always been that way.
This ensures consistency for anyone analyzing the stock’s past prices. The adjustment helps prevent misleading signals on charts, such as false sell signals or bearish trends that aren’t there. For instance, in a 2-for-1 stock split, the price per share is cut in half, which would otherwise appear as a dramatic drop on the chart. If someone didn’t know about the split, they might wrongly think something negative happened to the company. Most technical indicators would also react to this apparent drop by signaling to sell.
A stock split, while making the shares seem more affordable and potentially more attractive to investors, doesn’t alter the company’s fundamental value.
This ensures consistency for anyone analyzing the stock’s past prices. The adjustment helps prevent misleading signals on charts, such as false sell signals or bearish trends that aren’t there. For instance, in a 2-for-1 stock split, the price per share is cut in half, which would otherwise appear as a dramatic drop on the chart. If someone didn’t know about the split, they might wrongly think something negative happened to the company. Most technical indicators would also react to this apparent drop by signaling to sell.
A stock split, while making the shares seem more affordable and potentially more attractive to investors, doesn’t alter the company’s fundamental value.
Why do the ARS.L stock historical prices show a range for periods like 30 days, 90 days, and 52 weeks?
The range provides the lowest and highest prices at which the stock has traded during the specified period. This helps investors understand the stock’s volatility and price variability within that timeframe.
How can I use historical price volatility to assess risk?
High price volatility historically indicates higher risk and potentially higher returns. Investors can gauge the stock’s risk level by examining the range between high and low prices over various periods.