NASDAQ:CERS
Cerus Corporation Stock Price (Quote)
$1.89
+0 (+0%)
At Close: Jun 06, 2024
Range | Low Price | High Price | Comment |
---|---|---|---|
30 days | $1.71 | $2.26 | Thursday, 6th Jun 2024 CERS stock ended at $1.89. During the day the stock fluctuated 3.28% from a day low at $1.83 to a day high of $1.89. |
90 days | $1.61 | $2.46 | |
52 weeks | $1.21 | $3.08 |
Historical Cerus Corporation prices
Date | Open | High | Low | Close | Volume |
Nov 08, 2019 | $4.12 | $4.21 | $4.10 | $4.11 | 612 610 |
Nov 07, 2019 | $4.15 | $4.25 | $4.02 | $4.24 | 1 249 666 |
Nov 06, 2019 | $4.33 | $4.36 | $4.16 | $4.18 | 1 100 824 |
Nov 05, 2019 | $4.38 | $4.42 | $4.28 | $4.33 | 1 192 979 |
Nov 04, 2019 | $4.65 | $4.66 | $4.36 | $4.38 | 934 007 |
Nov 01, 2019 | $4.36 | $4.68 | $4.34 | $4.64 | 1 011 949 |
Oct 31, 2019 | $4.17 | $4.45 | $3.95 | $4.35 | 1 441 921 |
Oct 30, 2019 | $4.55 | $4.57 | $4.40 | $4.50 | 1 099 522 |
Oct 29, 2019 | $4.55 | $4.58 | $4.47 | $4.55 | 916 579 |
Oct 28, 2019 | $4.40 | $4.55 | $4.40 | $4.54 | 1 049 217 |
Oct 25, 2019 | $4.34 | $4.40 | $4.33 | $4.40 | 525 431 |
Oct 24, 2019 | $4.44 | $4.44 | $4.33 | $4.38 | 466 916 |
Oct 23, 2019 | $4.44 | $4.47 | $4.34 | $4.41 | 756 629 |
Oct 22, 2019 | $4.50 | $4.52 | $4.40 | $4.41 | 577 129 |
Oct 21, 2019 | $4.55 | $4.55 | $4.44 | $4.49 | 590 988 |
Oct 18, 2019 | $4.41 | $4.56 | $4.39 | $4.47 | 609 383 |
Oct 17, 2019 | $4.43 | $4.46 | $4.38 | $4.45 | 690 232 |
Oct 16, 2019 | $4.52 | $4.55 | $4.38 | $4.41 | 718 203 |
Oct 15, 2019 | $4.30 | $4.56 | $4.30 | $4.51 | 1 095 035 |
Oct 14, 2019 | $4.51 | $4.51 | $4.29 | $4.30 | 563 827 |
Oct 11, 2019 | $4.47 | $4.58 | $4.40 | $4.49 | 684 401 |
Oct 10, 2019 | $4.50 | $4.52 | $4.32 | $4.44 | 989 482 |
Oct 09, 2019 | $4.46 | $4.53 | $4.42 | $4.49 | 949 981 |
Oct 08, 2019 | $4.55 | $4.62 | $4.41 | $4.45 | 976 467 |
Oct 07, 2019 | $4.65 | $4.71 | $4.59 | $4.62 | 785 806 |
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 CERS stock historical prices to predict future price movements?
Trend Analysis: Examine the CERS 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 CERS 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.