NYSE:ANW
Delisted
Aegean Marine Petroleum Network Inc Fund Price (Quote)
$0.0440
+0 (+0%)
At Close: Dec 21, 2018
Range | Low Price | High Price | Comment |
---|---|---|---|
30 days | $0.0360 | $0.0693 | Friday, 21st Dec 2018 ANW stock ended at $0.0440. During the day the stock fluctuated 0% from a day low at $0.0440 to a day high of $0.0440. |
90 days | $0.0300 | $1.60 | |
52 weeks | $0.0300 | $5.10 |
Date | Open | High | Low | Close | Volume |
Sep 05, 2018 | $1.72 | $1.79 | $1.72 | $1.75 | 382 567 |
Sep 04, 2018 | $1.82 | $1.82 | $1.72 | $1.74 | 737 946 |
Aug 31, 2018 | $1.76 | $1.80 | $1.69 | $1.78 | 2 055 121 |
Aug 30, 2018 | $1.80 | $1.84 | $1.78 | $1.80 | 349 488 |
Aug 29, 2018 | $1.84 | $1.86 | $1.78 | $1.82 | 941 237 |
Aug 28, 2018 | $1.85 | $1.90 | $1.83 | $1.85 | 421 847 |
Aug 27, 2018 | $1.86 | $1.94 | $1.86 | $1.86 | 356 071 |
Aug 24, 2018 | $1.93 | $1.97 | $1.88 | $1.90 | 451 801 |
Aug 23, 2018 | $1.97 | $2.00 | $1.93 | $1.97 | 447 170 |
Aug 22, 2018 | $1.85 | $2.00 | $1.85 | $2.00 | 841 843 |
Aug 21, 2018 | $1.86 | $1.92 | $1.81 | $1.89 | 711 935 |
Aug 20, 2018 | $1.93 | $1.98 | $1.86 | $1.86 | 913 013 |
Aug 17, 2018 | $2.06 | $2.07 | $1.93 | $1.96 | 1 044 268 |
Aug 16, 2018 | $2.48 | $2.48 | $1.90 | $2.09 | 8 640 528 |
Aug 15, 2018 | $2.02 | $2.13 | $1.61 | $1.69 | 2 039 756 |
Aug 14, 2018 | $1.75 | $1.96 | $1.63 | $1.94 | 1 072 943 |
Aug 13, 2018 | $1.85 | $1.87 | $1.76 | $1.79 | 547 266 |
Aug 10, 2018 | $1.90 | $1.90 | $1.76 | $1.81 | 708 030 |
Aug 09, 2018 | $1.86 | $1.96 | $1.81 | $1.84 | 570 085 |
Aug 08, 2018 | $1.93 | $2.00 | $1.76 | $1.81 | 941 347 |
Aug 07, 2018 | $2.09 | $2.09 | $1.94 | $1.98 | 687 317 |
Aug 06, 2018 | $1.90 | $2.15 | $1.88 | $2.01 | 1 507 623 |
Aug 03, 2018 | $1.89 | $2.14 | $1.81 | $2.00 | 3 243 135 |
Aug 02, 2018 | $1.58 | $1.89 | $1.52 | $1.86 | 1 840 168 |
Aug 01, 2018 | $1.48 | $1.59 | $1.48 | $1.57 | 341 146 |
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 ANW stock historical prices to predict future price movements?
Trend Analysis: Examine the ANW 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 ANW 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.