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 |
Apr 11, 2024 | ₹5,605.25 | ₹5,605.25 | ₹5,605.25 | ₹5,605.25 | 0 |
Apr 10, 2024 | ₹5,632.95 | ₹5,632.95 | ₹5,550.05 | ₹5,582.80 | 182 102 |
Apr 09, 2024 | ₹5,705.00 | ₹5,715.80 | ₹5,583.80 | ₹5,605.25 | 146 472 |
Apr 08, 2024 | ₹5,678.00 | ₹5,737.45 | ₹5,636.00 | ₹5,668.00 | 233 954 |
Apr 05, 2024 | ₹5,642.80 | ₹5,692.45 | ₹5,538.25 | ₹5,634.25 | 242 495 |
Apr 04, 2024 | ₹5,646.05 | ₹5,770.00 | ₹5,605.00 | ₹5,627.05 | 366 075 |
Apr 03, 2024 | ₹5,511.00 | ₹5,672.40 | ₹5,511.00 | ₹5,645.30 | 341 383 |
Apr 02, 2024 | ₹5,474.95 | ₹5,599.00 | ₹5,454.40 | ₹5,576.85 | 263 803 |
Apr 01, 2024 | ₹5,378.85 | ₹5,528.75 | ₹5,378.85 | ₹5,462.90 | 370 805 |
Mar 28, 2024 | ₹5,288.65 | ₹5,405.00 | ₹5,236.50 | ₹5,374.05 | 398 175 |
Mar 27, 2024 | ₹5,130.00 | ₹5,360.00 | ₹5,117.45 | ₹5,288.65 | 791 200 |
Mar 26, 2024 | ₹4,991.55 | ₹5,111.20 | ₹4,970.00 | ₹5,098.65 | 427 338 |
Mar 22, 2024 | ₹4,935.05 | ₹4,997.20 | ₹4,864.65 | ₹4,991.55 | 281 403 |
Mar 21, 2024 | ₹4,750.00 | ₹4,954.00 | ₹4,741.55 | ₹4,942.35 | 461 386 |
Mar 20, 2024 | ₹4,668.70 | ₹4,758.45 | ₹4,562.35 | ₹4,709.55 | 179 032 |
Mar 19, 2024 | ₹4,840.00 | ₹4,849.55 | ₹4,602.65 | ₹4,639.85 | 371 815 |
Mar 18, 2024 | ₹4,774.95 | ₹4,855.00 | ₹4,745.90 | ₹4,834.40 | 171 795 |
Mar 15, 2024 | ₹4,768.00 | ₹4,820.60 | ₹4,682.10 | ₹4,771.30 | 229 256 |
Mar 14, 2024 | ₹4,650.95 | ₹4,788.20 | ₹4,579.75 | ₹4,751.40 | 242 062 |
Mar 13, 2024 | ₹4,784.85 | ₹4,844.00 | ₹4,613.80 | ₹4,650.10 | 378 991 |
Mar 12, 2024 | ₹4,745.00 | ₹4,834.95 | ₹4,700.00 | ₹4,782.45 | 409 379 |
Mar 11, 2024 | ₹4,670.00 | ₹4,972.40 | ₹4,670.00 | ₹4,730.85 | 1 126 126 |
Mar 07, 2024 | ₹4,730.00 | ₹4,743.00 | ₹4,655.75 | ₹4,668.65 | 143 364 |
Mar 06, 2024 | ₹4,745.00 | ₹4,745.00 | ₹4,630.10 | ₹4,708.55 | 172 873 |
Mar 05, 2024 | ₹4,718.40 | ₹4,759.65 | ₹4,687.15 | ₹4,730.15 | 96 228 |
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.