NSE:GAL
Delisted
Gyscoal Alloys Limited Stock Price (Quote)
₹2.95
+0 (+0%)
At Close: Sep 29, 2023
Range | Low Price | High Price | Comment |
---|---|---|---|
30 days | ₹2.95 | ₹2.95 | Friday, 29th Sep 2023 GAL.NS stock ended at ₹2.95. During the day the stock fluctuated 0% from a day low at ₹2.95 to a day high of ₹2.95. |
90 days | ₹2.95 | ₹2.95 | |
52 weeks | ₹2.40 | ₹4.20 |
Historical Gyscoal Alloys Limited prices
Date | Open | High | Low | Close | Volume |
Mar 29, 2023 | ₹2.55 | ₹2.55 | ₹2.45 | ₹2.45 | 241 496 |
Mar 28, 2023 | ₹2.55 | ₹2.65 | ₹2.50 | ₹2.50 | 298 745 |
Mar 27, 2023 | ₹2.65 | ₹2.65 | ₹2.55 | ₹2.60 | 601 883 |
Mar 24, 2023 | ₹2.60 | ₹2.65 | ₹2.55 | ₹2.55 | 332 441 |
Mar 23, 2023 | ₹2.80 | ₹2.85 | ₹2.65 | ₹2.65 | 237 282 |
Mar 22, 2023 | ₹2.65 | ₹2.75 | ₹2.55 | ₹2.75 | 762 887 |
Mar 21, 2023 | ₹2.55 | ₹2.65 | ₹2.45 | ₹2.65 | 867 867 |
Mar 20, 2023 | ₹2.60 | ₹2.65 | ₹2.50 | ₹2.55 | 238 241 |
Mar 17, 2023 | ₹2.60 | ₹2.65 | ₹2.50 | ₹2.60 | 534 833 |
Mar 16, 2023 | ₹2.65 | ₹2.65 | ₹2.55 | ₹2.55 | 200 928 |
Mar 15, 2023 | ₹2.65 | ₹2.65 | ₹2.55 | ₹2.60 | 192 703 |
Mar 14, 2023 | ₹2.60 | ₹2.65 | ₹2.50 | ₹2.60 | 227 678 |
Mar 13, 2023 | ₹2.60 | ₹2.75 | ₹2.60 | ₹2.60 | 706 853 |
Mar 10, 2023 | ₹2.80 | ₹2.80 | ₹2.70 | ₹2.70 | 448 288 |
Mar 09, 2023 | ₹2.80 | ₹2.85 | ₹2.75 | ₹2.80 | 722 442 |
Mar 08, 2023 | ₹2.70 | ₹2.75 | ₹2.65 | ₹2.75 | 795 509 |
Mar 06, 2023 | ₹2.70 | ₹2.75 | ₹2.65 | ₹2.65 | 365 655 |
Mar 03, 2023 | ₹2.70 | ₹2.75 | ₹2.65 | ₹2.70 | 385 031 |
Mar 02, 2023 | ₹2.65 | ₹2.75 | ₹2.60 | ₹2.70 | 326 815 |
Mar 01, 2023 | ₹2.75 | ₹2.75 | ₹2.65 | ₹2.70 | 157 692 |
Feb 28, 2023 | ₹2.70 | ₹2.75 | ₹2.70 | ₹2.70 | 318 839 |
Feb 27, 2023 | ₹2.75 | ₹2.80 | ₹2.60 | ₹2.65 | 247 796 |
Feb 24, 2023 | ₹2.70 | ₹2.80 | ₹2.70 | ₹2.70 | 616 816 |
Feb 23, 2023 | ₹2.75 | ₹2.75 | ₹2.65 | ₹2.75 | 440 343 |
Feb 20, 2023 | ₹2.55 | ₹2.60 | ₹2.45 | ₹2.60 | 211 415 |
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 GAL.NS stock historical prices to predict future price movements?
Trend Analysis: Examine the GAL.NS 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 GAL.NS 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.