XLON:AGY
Allergy Therapeutics Plc Stock Price (Quote)
£3.78
+0 (+0%)
At Close: May 30, 2024
Range | Low Price | High Price | Comment |
---|---|---|---|
30 days | £2.74 | £3.80 | Thursday, 30th May 2024 AGY.L stock ended at £3.78. During the day the stock fluctuated 0% from a day low at £3.78 to a day high of £3.78. |
90 days | £2.20 | £3.80 | |
52 weeks | £0.0250 | £6.25 |
Historical Allergy Therapeutics Plc prices
Date | Open | High | Low | Close | Volume |
May 30, 2024 | £3.78 | £3.78 | £3.78 | £3.78 | 0 |
May 29, 2024 | £3.78 | £3.78 | £3.78 | £3.78 | 0 |
May 24, 2024 | £3.43 | £3.80 | £3.43 | £3.78 | 711 616 |
May 23, 2024 | £3.40 | £3.80 | £3.33 | £3.40 | 1 658 438 |
May 22, 2024 | £3.50 | £3.50 | £3.30 | £3.30 | 18 902 |
May 21, 2024 | £3.44 | £3.50 | £3.30 | £3.40 | 421 327 |
May 20, 2024 | £3.29 | £3.40 | £3.10 | £3.40 | 1 355 264 |
May 17, 2024 | £3.30 | £3.40 | £3.10 | £3.25 | 591 351 |
May 16, 2024 | £3.30 | £3.40 | £3.30 | £3.35 | 2 273 888 |
May 15, 2024 | £3.21 | £3.30 | £3.00 | £3.20 | 1 291 179 |
May 14, 2024 | £3.21 | £3.21 | £3.06 | £3.15 | 661 794 |
May 13, 2024 | £3.06 | £3.25 | £3.00 | £3.15 | 1 359 810 |
May 10, 2024 | £3.08 | £3.28 | £3.00 | £3.15 | 881 633 |
May 09, 2024 | £3.14 | £3.38 | £3.02 | £3.13 | 576 496 |
May 08, 2024 | £2.99 | £3.30 | £2.95 | £3.30 | 324 167 |
May 07, 2024 | £2.75 | £3.15 | £2.75 | £3.12 | 2 801 938 |
May 03, 2024 | £3.00 | £3.00 | £2.75 | £2.88 | 320 409 |
May 02, 2024 | £2.90 | £3.00 | £2.88 | £2.88 | 973 172 |
May 01, 2024 | £3.00 | £3.00 | £2.74 | £2.88 | 759 943 |
Apr 30, 2024 | £3.00 | £3.00 | £2.80 | £2.90 | 782 547 |
Apr 29, 2024 | £2.80 | £2.90 | £2.74 | £2.90 | 1 571 923 |
Apr 26, 2024 | £2.89 | £2.90 | £2.80 | £2.85 | 515 871 |
Apr 25, 2024 | £2.90 | £2.90 | £2.80 | £2.85 | 750 862 |
Apr 24, 2024 | £2.90 | £2.90 | £2.80 | £2.85 | 919 062 |
Apr 23, 2024 | £3.00 | £3.00 | £2.70 | £2.80 | 948 754 |
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 AGY.L stock historical prices to predict future price movements?
Trend Analysis: Examine the AGY.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 AGY.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.