NASDAQ:CFMS
Delisted
ConforMIS Stock Price (Quote)
$2.26
+0 (+0%)
At Close: Nov 30, 2023
Range | Low Price | High Price | Comment |
---|---|---|---|
30 days | $2.26 | $2.26 | Thursday, 30th Nov 2023 CFMS stock ended at $2.26. During the day the stock fluctuated 0% from a day low at $2.26 to a day high of $2.26. |
90 days | $2.25 | $2.27 | |
52 weeks | $1.05 | $4.22 |
Date | Open | High | Low | Close | Volume |
Dec 09, 2019 | $1.53 | $1.55 | $1.45 | $1.49 | 1 660 759 |
Dec 06, 2019 | $1.63 | $1.68 | $1.53 | $1.56 | 289 991 |
Dec 05, 2019 | $1.70 | $1.72 | $1.47 | $1.63 | 1 025 178 |
Dec 04, 2019 | $1.79 | $1.82 | $1.69 | $1.71 | 407 888 |
Dec 03, 2019 | $1.80 | $1.84 | $1.77 | $1.81 | 259 413 |
Dec 02, 2019 | $1.86 | $1.87 | $1.78 | $1.81 | 409 252 |
Nov 29, 2019 | $1.81 | $1.90 | $1.76 | $1.86 | 145 236 |
Nov 27, 2019 | $1.88 | $1.92 | $1.80 | $1.80 | 325 005 |
Nov 26, 2019 | $1.84 | $1.91 | $1.82 | $1.88 | 194 407 |
Nov 25, 2019 | $1.82 | $1.89 | $1.79 | $1.84 | 267 138 |
Nov 22, 2019 | $1.79 | $1.87 | $1.78 | $1.82 | 209 790 |
Nov 21, 2019 | $1.78 | $1.86 | $1.77 | $1.81 | 489 277 |
Nov 20, 2019 | $1.78 | $1.86 | $1.76 | $1.77 | 355 066 |
Nov 19, 2019 | $1.75 | $1.82 | $1.73 | $1.80 | 323 421 |
Nov 18, 2019 | $1.90 | $1.90 | $1.76 | $1.76 | 543 005 |
Nov 15, 2019 | $1.83 | $1.90 | $1.81 | $1.88 | 470 634 |
Nov 14, 2019 | $1.90 | $1.94 | $1.79 | $1.79 | 553 251 |
Nov 13, 2019 | $1.95 | $1.98 | $1.91 | $1.94 | 279 046 |
Nov 12, 2019 | $1.96 | $2.05 | $1.95 | $1.97 | 282 172 |
Nov 11, 2019 | $1.97 | $2.03 | $1.94 | $1.97 | 370 860 |
Nov 08, 2019 | $2.24 | $2.25 | $1.90 | $2.01 | 1 827 641 |
Nov 07, 2019 | $1.91 | $2.06 | $1.90 | $1.97 | 454 350 |
Nov 06, 2019 | $2.01 | $2.07 | $1.90 | $1.91 | 831 445 |
Nov 05, 2019 | $2.04 | $2.07 | $1.99 | $2.00 | 533 539 |
Nov 04, 2019 | $2.07 | $2.17 | $2.02 | $2.04 | 667 367 |
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 CFMS stock historical prices to predict future price movements?
Trend Analysis: Examine the CFMS 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 CFMS 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.