Siemens Limited Stock Price (Quote)
₹7,185.35
+141.50 (+2.01%)
At Close: May 17, 2024
Range | Low Price | High Price | Comment |
---|---|---|---|
30 days | ₹5,480.80 | ₹7,249.05 | Friday, 17th May 2024 SIEMENS.NS stock ended at ₹7,185.35. This is 2.01% more than the trading day before Thursday, 16th May 2024. During the day the stock fluctuated 2.64% from a day low at ₹7,044.10 to a day high of ₹7,230.00. |
90 days | ₹4,375.00 | ₹7,249.05 | |
52 weeks | ₹3,246.00 | ₹7,249.05 |
Date | Open | High | Low | Close | Volume |
Dec 22, 2023 | ₹4,085.00 | ₹4,120.00 | ₹3,929.55 | ₹3,955.55 | 624 929 |
Dec 21, 2023 | ₹3,856.00 | ₹3,974.00 | ₹3,809.15 | ₹3,966.95 | 344 404 |
Dec 20, 2023 | ₹4,054.80 | ₹4,105.85 | ₹3,876.40 | ₹3,909.15 | 431 337 |
Dec 19, 2023 | ₹4,150.00 | ₹4,174.40 | ₹4,000.05 | ₹4,019.60 | 516 989 |
Dec 18, 2023 | ₹3,915.30 | ₹4,245.00 | ₹3,901.10 | ₹4,139.25 | 1 643 620 |
Dec 15, 2023 | ₹3,935.00 | ₹3,955.00 | ₹3,864.20 | ₹3,907.30 | 373 097 |
Dec 14, 2023 | ₹3,950.00 | ₹3,950.00 | ₹3,880.80 | ₹3,918.05 | 212 969 |
Dec 13, 2023 | ₹3,867.00 | ₹3,947.00 | ₹3,858.15 | ₹3,934.40 | 260 128 |
Dec 12, 2023 | ₹3,886.25 | ₹3,906.30 | ₹3,833.00 | ₹3,856.45 | 133 309 |
Dec 11, 2023 | ₹3,830.00 | ₹3,895.00 | ₹3,830.00 | ₹3,886.25 | 182 827 |
Dec 08, 2023 | ₹3,856.00 | ₹3,882.45 | ₹3,785.05 | ₹3,827.20 | 158 833 |
Dec 07, 2023 | ₹3,867.95 | ₹3,868.00 | ₹3,813.70 | ₹3,832.25 | 140 309 |
Dec 06, 2023 | ₹3,850.00 | ₹3,924.50 | ₹3,835.05 | ₹3,851.95 | 436 647 |
Dec 05, 2023 | ₹3,810.00 | ₹3,850.00 | ₹3,776.05 | ₹3,843.50 | 322 113 |
Dec 04, 2023 | ₹3,799.95 | ₹3,837.95 | ₹3,740.60 | ₹3,807.20 | 611 955 |
Dec 01, 2023 | ₹3,670.00 | ₹3,779.95 | ₹3,647.20 | ₹3,753.10 | 400 910 |
Nov 30, 2023 | ₹3,639.90 | ₹3,665.55 | ₹3,615.70 | ₹3,657.60 | 504 297 |
Nov 29, 2023 | ₹3,678.00 | ₹3,678.00 | ₹3,586.65 | ₹3,635.75 | 796 732 |
Nov 28, 2023 | ₹3,640.00 | ₹3,657.00 | ₹3,575.55 | ₹3,646.50 | 270 158 |
Nov 24, 2023 | ₹3,640.00 | ₹3,641.85 | ₹3,605.05 | ₹3,628.60 | 230 225 |
Nov 23, 2023 | ₹3,556.00 | ₹3,636.00 | ₹3,530.00 | ₹3,619.20 | 314 273 |
Nov 22, 2023 | ₹3,589.05 | ₹3,600.00 | ₹3,520.00 | ₹3,549.00 | 163 675 |
Nov 21, 2023 | ₹3,600.00 | ₹3,609.60 | ₹3,561.40 | ₹3,589.05 | 176 350 |
Nov 20, 2023 | ₹3,580.00 | ₹3,595.00 | ₹3,560.00 | ₹3,586.20 | 109 320 |
Nov 17, 2023 | ₹3,530.00 | ₹3,581.20 | ₹3,502.05 | ₹3,570.75 | 308 657 |
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 SIEMENS.NS stock historical prices to predict future price movements?
Trend Analysis: Examine the SIEMENS.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 SIEMENS.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.