NASDAQ:TRNX
Delisted
Taronis Technologies Inc. Stock Price (Quote)
$0.0001
+0 (+0%)
At Close: May 05, 2023
Range | Low Price | High Price | Comment |
---|---|---|---|
30 days | $0.0001 | $0.0001 | Friday, 5th May 2023 TRNX stock ended at $0.0001. During the day the stock fluctuated 0% from a day low at $0.0001 to a day high of $0.0001. |
90 days | $0.0001 | $0.0003 | |
52 weeks | $0.0001 | $0.0050 |
Date | Open | High | Low | Close | Volume |
Mar 07, 2018 | $1.10 | $1.19 | $1.05 | $1.05 | 2 304 000 |
Mar 06, 2018 | $1.09 | $1.11 | $1.05 | $1.06 | 960 523 |
Mar 05, 2018 | $1.14 | $1.15 | $1.05 | $1.08 | 1 127 254 |
Mar 02, 2018 | $1.31 | $1.32 | $1.06 | $1.11 | 4 224 806 |
Mar 01, 2018 | $1.47 | $1.72 | $1.22 | $1.26 | 25 284 750 |
Feb 28, 2018 | $1.07 | $1.10 | $1.02 | $1.07 | 308 965 |
Feb 27, 2018 | $1.12 | $1.22 | $1.05 | $1.06 | 660 291 |
Feb 26, 2018 | $1.09 | $1.17 | $1.01 | $1.09 | 436 588 |
Feb 23, 2018 | $1.08 | $1.12 | $0.91 | $1.07 | 715 381 |
Feb 22, 2018 | $1.28 | $1.28 | $1.05 | $1.08 | 1 926 007 |
Feb 21, 2018 | $1.20 | $1.48 | $1.19 | $1.22 | 5 108 063 |
Feb 20, 2018 | $1.28 | $1.33 | $1.16 | $1.17 | 282 390 |
Feb 16, 2018 | $1.37 | $1.37 | $1.26 | $1.31 | 294 995 |
Feb 15, 2018 | $1.31 | $1.42 | $1.24 | $1.34 | 517 192 |
Feb 14, 2018 | $1.40 | $1.44 | $1.30 | $1.30 | 419 852 |
Feb 13, 2018 | $1.52 | $1.59 | $1.40 | $1.42 | 1 129 880 |
Feb 12, 2018 | $1.52 | $1.75 | $1.43 | $1.46 | 1 486 917 |
Feb 09, 2018 | $1.63 | $1.64 | $1.44 | $1.52 | 325 607 |
Feb 08, 2018 | $1.71 | $1.76 | $1.54 | $1.58 | 351 117 |
Feb 07, 2018 | $1.76 | $1.91 | $1.71 | $1.71 | 471 850 |
Feb 06, 2018 | $1.76 | $1.85 | $1.70 | $1.76 | 230 928 |
Feb 05, 2018 | $2.03 | $2.03 | $1.76 | $1.79 | 279 730 |
Feb 02, 2018 | $2.24 | $2.34 | $1.90 | $2.00 | 904 687 |
Feb 01, 2018 | $2.14 | $2.40 | $2.08 | $2.15 | 519 003 |
Jan 31, 2018 | $2.36 | $2.41 | $2.13 | $2.15 | 279 555 |
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 TRNX stock historical prices to predict future price movements?
Trend Analysis: Examine the TRNX 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 TRNX 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.