NASDAQ:SNNA
Delisted
Sienna Biopharmaceuticals Inc Stock Price (Quote)
$0.136
+0 (+0%)
At Close: Jan 21, 2020
Range | Low Price | High Price | Comment |
---|---|---|---|
30 days | $0.136 | $0.136 | Tuesday, 21st Jan 2020 SNNA stock ended at $0.136. During the day the stock fluctuated 0% from a day low at $0.136 to a day high of $0.136. |
90 days | $0.0640 | $0.439 | |
52 weeks | $0.0640 | $3.47 |
Historical Sienna Biopharmaceuticals Inc prices
Date | Open | High | Low | Close | Volume |
Jan 23, 2019 | $2.83 | $2.98 | $2.68 | $2.78 | 216 864 |
Jan 22, 2019 | $2.97 | $2.98 | $2.75 | $2.83 | 535 462 |
Jan 18, 2019 | $2.78 | $3.15 | $2.60 | $2.98 | 327 681 |
Jan 17, 2019 | $2.82 | $2.90 | $2.74 | $2.77 | 265 702 |
Jan 16, 2019 | $2.96 | $3.15 | $2.80 | $2.83 | 182 841 |
Jan 15, 2019 | $2.91 | $2.99 | $2.76 | $2.93 | 165 327 |
Jan 14, 2019 | $2.98 | $3.38 | $2.90 | $2.90 | 255 999 |
Jan 11, 2019 | $3.02 | $3.03 | $2.86 | $2.99 | 80 034 |
Jan 10, 2019 | $3.24 | $3.24 | $2.92 | $3.02 | 171 563 |
Jan 09, 2019 | $3.02 | $3.33 | $2.79 | $3.25 | 460 997 |
Jan 08, 2019 | $3.10 | $3.16 | $2.84 | $3.00 | 176 333 |
Jan 07, 2019 | $3.19 | $3.80 | $2.93 | $3.03 | 591 476 |
Jan 04, 2019 | $2.51 | $3.27 | $2.39 | $3.12 | 658 453 |
Jan 03, 2019 | $2.48 | $2.67 | $2.28 | $2.46 | 387 133 |
Jan 02, 2019 | $2.31 | $2.49 | $2.05 | $2.49 | 552 673 |
Dec 31, 2018 | $2.45 | $2.49 | $2.23 | $2.32 | 224 646 |
Dec 28, 2018 | $2.43 | $2.58 | $2.36 | $2.45 | 197 410 |
Dec 27, 2018 | $2.79 | $2.79 | $2.27 | $2.44 | 240 259 |
Dec 26, 2018 | $2.57 | $2.91 | $2.54 | $2.66 | 293 417 |
Dec 24, 2018 | $2.73 | $2.80 | $2.56 | $2.56 | 43 111 |
Dec 21, 2018 | $2.80 | $2.91 | $2.63 | $2.74 | 373 629 |
Dec 20, 2018 | $2.87 | $2.95 | $2.76 | $2.79 | 94 731 |
Dec 19, 2018 | $3.15 | $3.15 | $2.80 | $2.87 | 163 269 |
Dec 18, 2018 | $3.26 | $3.42 | $3.03 | $3.08 | 176 563 |
Dec 17, 2018 | $3.48 | $3.60 | $3.17 | $3.18 | 136 696 |
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 SNNA stock historical prices to predict future price movements?
Trend Analysis: Examine the SNNA 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 SNNA 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.