NASDAQ:ARQL
Delisted
ArQule Stock Price (Quote)
$20.00
+0 (+0%)
At Close: Apr 15, 2020
Range | Low Price | High Price | Comment |
---|---|---|---|
30 days | $20.00 | $20.00 | Wednesday, 15th Apr 2020 ARQL stock ended at $20.00. During the day the stock fluctuated 0% from a day low at $20.00 to a day high of $20.00. |
90 days | $20.00 | $20.00 | |
52 weeks | $5.76 | $20.45 |
Date | Open | High | Low | Close | Volume |
Jul 07, 2016 | $1.71 | $1.71 | $1.63 | $1.66 | 120 900 |
Jul 06, 2016 | $1.74 | $1.76 | $1.69 | $1.70 | 90 300 |
Jul 05, 2016 | $1.84 | $1.93 | $1.67 | $1.75 | 510 600 |
Jul 01, 2016 | $1.88 | $1.94 | $1.82 | $1.85 | 220 800 |
Jun 30, 2016 | $2.10 | $2.17 | $1.83 | $1.90 | 438 300 |
Jun 29, 2016 | $1.85 | $1.92 | $1.83 | $1.91 | 211 900 |
Jun 28, 2016 | $1.82 | $1.86 | $1.77 | $1.82 | 93 800 |
Jun 27, 2016 | $1.92 | $1.92 | $1.73 | $1.78 | 228 500 |
Jun 24, 2016 | $1.85 | $1.93 | $1.78 | $1.91 | 310 300 |
Jun 23, 2016 | $1.93 | $2.04 | $1.86 | $1.92 | 472 500 |
Jun 22, 2016 | $1.78 | $1.90 | $1.78 | $1.89 | 310 800 |
Jun 21, 2016 | $1.75 | $1.80 | $1.71 | $1.75 | 71 400 |
Jun 20, 2016 | $1.79 | $1.80 | $1.75 | $1.75 | 50 800 |
Jun 17, 2016 | $1.80 | $1.82 | $1.73 | $1.79 | 325 600 |
Jun 16, 2016 | $1.79 | $1.79 | $1.79 | $1.79 | 153 338 |
Jun 15, 2016 | $1.74 | $1.74 | $1.74 | $1.74 | 63 205 |
Jun 14, 2016 | $1.70 | $1.70 | $1.70 | $1.70 | 78 779 |
Jun 13, 2016 | $1.73 | $1.73 | $1.73 | $1.73 | 91 793 |
Jun 10, 2016 | $1.78 | $1.78 | $1.78 | $1.78 | 70 539 |
Jun 09, 2016 | $1.78 | $1.78 | $1.78 | $1.78 | 197 140 |
Jun 08, 2016 | $1.78 | $1.78 | $1.78 | $1.78 | 144 176 |
Jun 07, 2016 | $1.80 | $1.80 | $1.80 | $1.80 | 151 799 |
Jun 06, 2016 | $1.83 | $1.83 | $1.83 | $1.83 | 70 693 |
Jun 03, 2016 | $1.82 | $1.82 | $1.82 | $1.82 | 49 214 |
Jun 02, 2016 | $1.85 | $1.85 | $1.85 | $1.85 | 122 266 |
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 ARQL stock historical prices to predict future price movements?
Trend Analysis: Examine the ARQL 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 ARQL 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.