NYSE:CLNY
Delisted
Colony Capital, Inc. Stock Price (Quote)
$8.50
+0 (+0%)
At Close: Dec 08, 2021
Range | Low Price | High Price | Comment |
---|---|---|---|
30 days | $8.50 | $8.50 | Wednesday, 8th Dec 2021 CLNY stock ended at $8.50. During the day the stock fluctuated 0% from a day low at $8.50 to a day high of $8.50. |
90 days | $8.50 | $8.50 | |
52 weeks | $4.34 | $8.70 |
Date | Open | High | Low | Close | Volume |
Dec 10, 2020 | $4.85 | $4.98 | $4.85 | $4.87 | 4 300 221 |
Dec 09, 2020 | $4.94 | $4.96 | $4.82 | $4.91 | 2 907 532 |
Dec 08, 2020 | $4.74 | $4.92 | $4.73 | $4.91 | 3 486 754 |
Dec 07, 2020 | $4.77 | $4.81 | $4.59 | $4.73 | 3 220 942 |
Dec 04, 2020 | $4.76 | $4.78 | $4.60 | $4.78 | 4 720 178 |
Dec 03, 2020 | $4.55 | $4.83 | $4.47 | $4.69 | 6 200 447 |
Dec 02, 2020 | $4.31 | $4.44 | $4.27 | $4.39 | 2 506 419 |
Dec 01, 2020 | $4.37 | $4.42 | $4.17 | $4.35 | 3 788 315 |
Nov 30, 2020 | $4.32 | $4.43 | $4.28 | $4.32 | 4 701 864 |
Nov 27, 2020 | $4.39 | $4.41 | $4.34 | $4.36 | 1 373 647 |
Nov 25, 2020 | $4.31 | $4.39 | $4.22 | $4.38 | 4 889 708 |
Nov 24, 2020 | $4.32 | $4.38 | $4.24 | $4.31 | 4 258 728 |
Nov 23, 2020 | $4.34 | $4.40 | $4.22 | $4.24 | 8 129 072 |
Nov 20, 2020 | $4.21 | $4.32 | $4.16 | $4.31 | 4 484 336 |
Nov 19, 2020 | $4.12 | $4.24 | $4.00 | $4.24 | 4 542 327 |
Nov 18, 2020 | $4.25 | $4.34 | $4.12 | $4.15 | 7 084 761 |
Nov 17, 2020 | $4.19 | $4.29 | $4.07 | $4.21 | 11 100 474 |
Nov 16, 2020 | $4.10 | $4.28 | $4.02 | $4.27 | 9 117 398 |
Nov 13, 2020 | $3.93 | $4.02 | $3.86 | $3.98 | 4 933 966 |
Nov 12, 2020 | $3.91 | $3.94 | $3.78 | $3.87 | 4 585 614 |
Nov 11, 2020 | $4.08 | $4.09 | $3.91 | $3.97 | 4 494 825 |
Nov 10, 2020 | $3.95 | $4.00 | $3.83 | $4.00 | 4 911 590 |
Nov 09, 2020 | $4.02 | $4.27 | $3.74 | $3.75 | 6 961 124 |
Nov 06, 2020 | $3.77 | $3.98 | $3.66 | $3.75 | 5 474 339 |
Nov 05, 2020 | $3.70 | $3.83 | $3.66 | $3.74 | 6 926 265 |
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 CLNY stock historical prices to predict future price movements?
Trend Analysis: Examine the CLNY 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 CLNY 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.