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Range Low Price High Price Comment
30 days $12.83 $12.83 Thursday, 28th Mar 2024 RPT stock ended at $12.83. During the day the stock fluctuated 0% from a day low at $12.83 to a day high of $12.83.
90 days $12.83 $13.16
52 weeks $8.67 $13.79

Historical Ramco-Gershenson Properties Trust prices

Date Open High Low Close Volume
Feb 04, 2016 $17.15 $17.33 $17.08 $16.99 340 900
Feb 03, 2016 $17.23 $17.38 $17.09 $17.03 781 400
Feb 02, 2016 $17.28 $17.29 $16.97 $16.94 645 300
Feb 01, 2016 $17.02 $17.38 $16.93 $17.05 684 800
Jan 29, 2016 $16.75 $17.09 $16.64 $16.88 434 900
Jan 28, 2016 $16.70 $16.84 $16.53 $16.38 277 300
Jan 27, 2016 $16.67 $16.80 $16.48 $16.37 518 500
Jan 26, 2016 $16.52 $16.91 $16.52 $16.55 803 100
Jan 25, 2016 $16.59 $16.81 $16.41 $16.26 738 600
Jan 22, 2016 $16.17 $16.74 $16.17 $16.38 934 200
Jan 21, 2016 $16.10 $16.39 $15.90 $15.90 670 400
Jan 20, 2016 $16.07 $16.22 $15.50 $15.79 620 800
Jan 19, 2016 $16.19 $16.35 $16.12 $16.10 485 100
Jan 15, 2016 $15.72 $16.12 $15.69 $15.87 517 700
Jan 14, 2016 $16.15 $16.29 $16.02 $15.87 347 100
Jan 13, 2016 $16.48 $16.64 $16.06 $15.91 428 300
Jan 12, 2016 $16.84 $16.84 $16.35 $16.28 427 900
Jan 11, 2016 $16.52 $16.74 $16.48 $16.46 413 700
Jan 08, 2016 $16.80 $16.88 $16.45 $16.28 640 700
Jan 07, 2016 $16.75 $16.86 $16.63 $16.56 542 600
Jan 06, 2016 $16.75 $17.04 $16.75 $16.82 452 200
Jan 05, 2016 $16.54 $16.91 $16.34 $16.69 879 900

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.

How can I use RPT stock historical prices to predict future price movements?
Trend Analysis: Examine the RPT 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.

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.

Why do the RPT 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.
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