NYSE:FIG
Delisted
Fortress Investment Group LLC ETF Price (Quote)
$7.85
+0 (+0%)
At Close: Jul 22, 2019
Range | Low Price | High Price | Comment |
---|---|---|---|
30 days | $7.85 | $7.85 | Monday, 22nd Jul 2019 FIG stock ended at $7.85. During the day the stock fluctuated 0% from a day low at $7.85 to a day high of $7.85. |
90 days | $7.85 | $7.85 | |
52 weeks | $7.85 | $7.85 |
Date | Open | High | Low | Close | Volume |
Mar 03, 2017 | $7.97 | $8.00 | $7.97 | $8.00 | 8 371 644 |
Mar 02, 2017 | $7.97 | $8.00 | $7.96 | $7.97 | 12 981 654 |
Mar 01, 2017 | $7.98 | $7.98 | $7.96 | $7.97 | 10 773 273 |
Feb 28, 2017 | $7.98 | $7.99 | $7.97 | $7.98 | 4 023 775 |
Feb 27, 2017 | $7.97 | $7.98 | $7.97 | $7.98 | 3 927 622 |
Feb 24, 2017 | $7.99 | $7.99 | $7.96 | $7.97 | 4 834 266 |
Feb 23, 2017 | $7.98 | $7.99 | $7.98 | $7.98 | 3 042 910 |
Feb 22, 2017 | $7.98 | $7.99 | $7.98 | $7.99 | 5 248 811 |
Feb 21, 2017 | $7.99 | $7.99 | $7.98 | $7.98 | 5 344 501 |
Feb 17, 2017 | $7.97 | $7.99 | $7.97 | $7.99 | 6 414 020 |
Feb 16, 2017 | $7.98 | $8.00 | $7.96 | $7.97 | 36 701 916 |
Feb 15, 2017 | $7.96 | $8.05 | $7.95 | $7.99 | 151 443 169 |
Feb 14, 2017 | $5.85 | $6.36 | $5.79 | $6.21 | 7 981 459 |
Feb 13, 2017 | $5.96 | $5.97 | $5.82 | $5.83 | 802 988 |
Feb 10, 2017 | $5.88 | $5.96 | $5.82 | $5.92 | 1 211 080 |
Feb 09, 2017 | $5.87 | $5.92 | $5.81 | $5.85 | 1 273 399 |
Feb 08, 2017 | $5.90 | $5.97 | $5.73 | $5.85 | 1 279 928 |
Feb 07, 2017 | $5.92 | $6.00 | $5.87 | $5.91 | 1 535 820 |
Feb 06, 2017 | $5.92 | $5.97 | $5.87 | $5.90 | 686 286 |
Feb 03, 2017 | $5.90 | $6.03 | $5.85 | $5.91 | 2 017 530 |
Feb 02, 2017 | $5.83 | $5.97 | $5.75 | $5.79 | 2 464 110 |
Feb 01, 2017 | $5.68 | $5.73 | $5.56 | $5.66 | 1 029 054 |
Jan 31, 2017 | $5.31 | $5.65 | $5.25 | $5.61 | 1 803 009 |
Jan 30, 2017 | $5.21 | $5.40 | $5.18 | $5.37 | 1 094 905 |
Jan 27, 2017 | $5.08 | $5.25 | $5.08 | $5.21 | 774 705 |
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 FIG stock historical prices to predict future price movements?
Trend Analysis: Examine the FIG 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 FIG 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.