NYSE:MBT
Delisted
Mobile TeleSystems OJSC Stock Price (Quote)
$5.50
+0 (+0%)
At Close: Aug 17, 2022
Range | Low Price | High Price | Comment |
---|---|---|---|
30 days | $5.50 | $5.50 | Wednesday, 17th Aug 2022 MBT stock ended at $5.50. During the day the stock fluctuated 0% from a day low at $5.50 to a day high of $5.50. |
90 days | $5.50 | $5.50 | |
52 weeks | $5.34 | $10.08 |
Date | Open | High | Low | Close | Volume |
Jan 11, 2022 | $7.88 | $8.03 | $7.88 | $8.03 | 2 899 800 |
Jan 10, 2022 | $7.96 | $7.98 | $7.71 | $7.88 | 2 533 800 |
Jan 07, 2022 | $8.00 | $8.02 | $7.92 | $7.98 | 1 361 300 |
Jan 06, 2022 | $7.85 | $7.95 | $7.80 | $7.91 | 2 520 900 |
Jan 05, 2022 | $8.06 | $8.15 | $7.90 | $7.91 | 2 286 100 |
Jan 04, 2022 | $8.12 | $8.14 | $8.04 | $8.09 | 1 649 300 |
Jan 03, 2022 | $8.08 | $8.18 | $8.07 | $8.11 | 1 368 900 |
Dec 31, 2021 | $7.98 | $8.04 | $7.94 | $7.95 | 998 600 |
Dec 30, 2021 | $7.95 | $8.03 | $7.94 | $8.01 | 1 145 400 |
Dec 29, 2021 | $8.00 | $8.01 | $7.95 | $7.96 | 889 800 |
Dec 28, 2021 | $8.00 | $8.07 | $7.95 | $7.95 | 1 527 600 |
Dec 27, 2021 | $7.97 | $8.04 | $7.91 | $8.00 | 2 065 800 |
Dec 23, 2021 | $7.89 | $7.99 | $7.89 | $7.92 | 1 578 800 |
Dec 22, 2021 | $7.92 | $7.98 | $7.87 | $7.87 | 1 922 300 |
Dec 21, 2021 | $7.84 | $7.99 | $7.84 | $7.91 | 1 952 100 |
Dec 20, 2021 | $7.76 | $7.88 | $7.70 | $7.84 | 2 763 865 |
Dec 17, 2021 | $7.84 | $7.86 | $7.73 | $7.74 | 4 253 173 |
Dec 16, 2021 | $7.79 | $7.85 | $7.76 | $7.78 | 3 219 529 |
Dec 15, 2021 | $7.74 | $7.81 | $7.47 | $7.60 | 5 958 288 |
Dec 14, 2021 | $7.60 | $7.68 | $7.53 | $7.53 | 2 560 643 |
Dec 13, 2021 | $7.78 | $7.80 | $7.61 | $7.61 | 4 976 646 |
Dec 10, 2021 | $7.98 | $7.99 | $7.85 | $7.86 | 6 558 349 |
Dec 09, 2021 | $8.04 | $8.09 | $7.90 | $7.94 | 3 438 206 |
Dec 08, 2021 | $8.07 | $8.07 | $7.91 | $8.06 | 4 078 836 |
Dec 07, 2021 | $8.03 | $8.09 | $7.88 | $8.03 | 6 772 270 |
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 MBT stock historical prices to predict future price movements?
Trend Analysis: Examine the MBT 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 MBT 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.