XLON:AGQ
Delisted
ProShares Ultra Silver ETF Fund Price (Quote)
£0.135
+0 (+0%)
At Close: Sep 16, 2019
Range | Low Price | High Price | Comment |
---|---|---|---|
30 days | £0.135 | £0.135 | Monday, 16th Sep 2019 AGQ.L stock ended at £0.135. During the day the stock fluctuated 0% from a day low at £0.135 to a day high of £0.135. |
90 days | £0.125 | £0.150 | |
52 weeks | £0.0450 | £0.470 |
Date | Open | High | Low | Close | Volume |
May 10, 2016 | £0.95 | £0.95 | £0.93 | £0.93 | 1 766 898 |
May 09, 2016 | £0.95 | £0.95 | £0.95 | £0.95 | 1 641 373 |
May 06, 2016 | £0.95 | £0.95 | £0.95 | £0.95 | 3 698 088 |
May 05, 2016 | £0.98 | £0.98 | £0.93 | £0.95 | 3 134 339 |
May 04, 2016 | £1.18 | £1.18 | £0.93 | £0.98 | 23 722 393 |
May 03, 2016 | £1.13 | £1.13 | £1.05 | £1.13 | 9 440 037 |
Apr 29, 2016 | £1.10 | £1.18 | £1.10 | £1.13 | 19 691 474 |
Apr 28, 2016 | £1.05 | £1.10 | £1.00 | £1.10 | 39 672 710 |
Apr 27, 2016 | £1.23 | £1.23 | £1.18 | £1.18 | 3 359 380 |
Apr 26, 2016 | £1.25 | £1.25 | £1.23 | £1.23 | 2 194 600 |
Apr 25, 2016 | £1.30 | £1.30 | £1.25 | £1.25 | 1 115 854 |
Apr 22, 2016 | £1.40 | £1.40 | £1.30 | £1.30 | 1 977 144 |
Apr 21, 2016 | £1.38 | £1.40 | £1.38 | £1.40 | 3 072 713 |
Apr 20, 2016 | £1.43 | £1.43 | £1.38 | £1.38 | 5 012 869 |
Apr 19, 2016 | £1.25 | £1.43 | £1.25 | £1.43 | 15 656 338 |
Apr 18, 2016 | £1.28 | £1.28 | £1.25 | £1.25 | 1 137 256 |
Apr 15, 2016 | £1.30 | £1.30 | £1.25 | £1.28 | 1 248 013 |
Apr 14, 2016 | £1.30 | £1.30 | £1.30 | £1.30 | 818 548 |
Apr 13, 2016 | £1.40 | £1.40 | £1.28 | £1.30 | 9 037 267 |
Apr 12, 2016 | £1.30 | £1.43 | £1.30 | £1.40 | 8 979 424 |
Apr 11, 2016 | £1.30 | £1.30 | £1.30 | £1.30 | 2 768 555 |
Apr 08, 2016 | £1.25 | £1.30 | £1.25 | £1.30 | 5 816 784 |
Apr 07, 2016 | £1.30 | £1.38 | £1.25 | £1.25 | 9 226 480 |
Apr 06, 2016 | £1.20 | £1.30 | £1.20 | £1.30 | 4 835 738 |
Apr 05, 2016 | £1.13 | £1.25 | £1.13 | £1.20 | 6 209 771 |
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 AGQ.L stock historical prices to predict future price movements?
Trend Analysis: Examine the AGQ.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 AGQ.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.