NASDAQ:CASA
Casa Systems Inc. Stock Price (Quote)
$0.0350
+0 (+0%)
At Close: Jun 14, 2024
Range | Low Price | High Price | Comment |
---|---|---|---|
30 days | $0.0350 | $0.0350 | Friday, 14th Jun 2024 CASA stock ended at $0.0350. During the day the stock fluctuated 0% from a day low at $0.0350 to a day high of $0.0350. |
90 days | $0.0350 | $0.356 | |
52 weeks | $0.0350 | $1.42 |
Historical Casa Systems Inc. prices
Date | Open | High | Low | Close | Volume |
May 11, 2023 | $1.21 | $1.23 | $1.13 | $1.13 | 258 461 |
May 10, 2023 | $1.27 | $1.37 | $1.21 | $1.23 | 973 969 |
May 09, 2023 | $1.20 | $1.22 | $1.18 | $1.20 | 266 343 |
May 08, 2023 | $1.21 | $1.24 | $1.20 | $1.20 | 99 448 |
May 05, 2023 | $1.25 | $1.25 | $1.18 | $1.18 | 182 167 |
May 04, 2023 | $1.20 | $1.25 | $1.15 | $1.24 | 265 430 |
May 03, 2023 | $1.17 | $1.23 | $1.16 | $1.21 | 130 837 |
May 02, 2023 | $1.21 | $1.25 | $1.16 | $1.17 | 150 897 |
May 01, 2023 | $1.25 | $1.26 | $1.21 | $1.22 | 231 968 |
Apr 28, 2023 | $1.20 | $1.29 | $1.18 | $1.25 | 381 112 |
Apr 27, 2023 | $1.19 | $1.23 | $1.15 | $1.20 | 311 914 |
Apr 26, 2023 | $1.21 | $1.21 | $1.18 | $1.18 | 153 565 |
Apr 25, 2023 | $1.22 | $1.29 | $1.21 | $1.22 | 405 966 |
Apr 24, 2023 | $1.18 | $1.25 | $1.17 | $1.23 | 428 887 |
Apr 21, 2023 | $1.24 | $1.25 | $1.18 | $1.18 | 271 478 |
Apr 20, 2023 | $1.20 | $1.33 | $1.18 | $1.25 | 643 810 |
Apr 19, 2023 | $1.16 | $1.22 | $1.13 | $1.20 | 583 999 |
Apr 18, 2023 | $1.14 | $1.17 | $1.13 | $1.16 | 216 415 |
Apr 17, 2023 | $1.17 | $1.17 | $1.14 | $1.14 | 190 923 |
Apr 14, 2023 | $1.16 | $1.22 | $1.14 | $1.14 | 381 349 |
Apr 13, 2023 | $1.15 | $1.18 | $1.14 | $1.15 | 560 431 |
Apr 12, 2023 | $1.17 | $1.20 | $1.14 | $1.15 | 277 794 |
Apr 11, 2023 | $1.17 | $1.28 | $1.17 | $1.17 | 920 396 |
Apr 10, 2023 | $1.13 | $1.19 | $1.12 | $1.17 | 431 869 |
Apr 06, 2023 | $1.16 | $1.17 | $1.10 | $1.16 | 279 427 |
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 CASA stock historical prices to predict future price movements?
Trend Analysis: Examine the CASA 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 CASA 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.