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 |
Dec 07, 2022 | ₹2.75 | ₹3.15 | ₹2.75 | ₹3.05 | 1 971 694 |
Dec 06, 2022 | ₹2.75 | ₹2.85 | ₹2.65 | ₹2.80 | 1 580 565 |
Dec 05, 2022 | ₹2.70 | ₹2.80 | ₹2.65 | ₹2.80 | 895 091 |
Dec 02, 2022 | ₹2.60 | ₹2.70 | ₹2.55 | ₹2.65 | 578 952 |
Dec 01, 2022 | ₹2.65 | ₹2.70 | ₹2.55 | ₹2.60 | 702 179 |
Nov 30, 2022 | ₹2.65 | ₹2.70 | ₹2.60 | ₹2.60 | 298 032 |
Nov 29, 2022 | ₹2.65 | ₹2.75 | ₹2.60 | ₹2.65 | 479 335 |
Nov 28, 2022 | ₹2.65 | ₹2.80 | ₹2.60 | ₹2.65 | 519 294 |
Nov 25, 2022 | ₹2.75 | ₹2.75 | ₹2.65 | ₹2.70 | 296 910 |
Nov 24, 2022 | ₹2.75 | ₹2.75 | ₹2.65 | ₹2.70 | 406 315 |
Nov 23, 2022 | ₹2.80 | ₹2.85 | ₹2.65 | ₹2.70 | 344 848 |
Nov 22, 2022 | ₹2.75 | ₹2.90 | ₹2.65 | ₹2.80 | 489 137 |
Nov 21, 2022 | ₹2.75 | ₹2.75 | ₹2.60 | ₹2.75 | 276 716 |
Nov 18, 2022 | ₹2.80 | ₹2.80 | ₹2.75 | ₹2.75 | 176 656 |
Nov 17, 2022 | ₹2.75 | ₹2.80 | ₹2.70 | ₹2.80 | 109 193 |
Nov 16, 2022 | ₹2.70 | ₹2.85 | ₹2.70 | ₹2.80 | 330 412 |
Nov 15, 2022 | ₹2.75 | ₹2.75 | ₹2.70 | ₹2.70 | 114 323 |
Nov 14, 2022 | ₹2.80 | ₹2.80 | ₹2.70 | ₹2.75 | 178 301 |
Nov 11, 2022 | ₹2.75 | ₹2.90 | ₹2.70 | ₹2.70 | 285 156 |
Nov 10, 2022 | ₹2.75 | ₹2.95 | ₹2.70 | ₹2.70 | 308 282 |
Nov 09, 2022 | ₹2.65 | ₹2.75 | ₹2.60 | ₹2.75 | 657 684 |
Nov 07, 2022 | ₹2.55 | ₹2.65 | ₹2.50 | ₹2.65 | 810 083 |
Nov 04, 2022 | ₹2.60 | ₹2.60 | ₹2.45 | ₹2.50 | 615 902 |
Nov 03, 2022 | ₹2.55 | ₹2.60 | ₹2.50 | ₹2.55 | 1 126 632 |
Nov 02, 2022 | ₹2.60 | ₹2.60 | ₹2.55 | ₹2.60 | 191 334 |
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.