Container Store Group Stock Price History

Container Store Stock Price History Chart

Container Store November 30, 2024 Stock Price Synopsis

Various analyses of Container Store's daily price changes, such as its Balance Of Power or Price Action, are crucial when deciding whether to buy, hold, or sell Container Stock. It can be used to describe the percentage change in the price of Container Store from one trading day to the next and could be a valuable metric for traders and investors to gauge the volatility and momentum of Container Stock. When benchmark price declines in a down market, there may be an uptick in Container Stock price where buyers come in believing the asset is cheap or selling overdone. The opposite is true when the market is bullish. You can use Container Store intraday prices and daily technical indicators to check the level of noise trading in Container Stock and then apply it to test your longer-term investment strategies against Container.

Container Stock Price History Data

The price series of Container Store for the period between Sun, Sep 1, 2024 and Sat, Nov 30, 2024 has a statistical range of 13.74 with a coefficient of variation of 40.44. The price distribution for the period has arithmetic mean of 8.88. The median price for the last 90 days is 9.8. The company completed stock split (1:15) on 4th of September 2024. Container Store Group had dividends distributed to its stock-holders on 26th of March 2020.

Container Store investors dedicate a lot of time and effort to gaining insight into how a market's past behavior relates to its future. Access to timely market data for Container is vital when making an investment decision, and regardless of whether you use fundamental or technical analysis, your return on investment in Container Store Group will depend on recognizing future opportunities and eliminating past mistakes. Historical data analysis is the study of market behavior over a given time. Recorded market-related data such as price, volatility, and volume can be quantified and studied over a defined period. Through a detailed examination of a market's past behavior, traders and investors can gain perspective on the inner workings of that market. The information obtained throughout analyzing Container Store stock prices may prove useful in developing a viable investing in Container Store

Container Store technical stock analysis exercises models and trading practices based on price and volume transformations, such as the moving averages, relative strength index, regressions, price and return correlations, business cycles, stock market cycles, or different charting patterns.

Predictive indicators are helping investors to find signals for Container Store's price direction in advance. Along with the technical and fundamental analysis of Container Stock historical price patterns, it is also worthwhile for investors to track various predictive indicators of Container to make sure they correctly time the market and exploit it's hidden potentials. Even though most predictive indicators are useful for the short-term horizon, it's virtually impossible to predict the unforeseen market. For traders with a short-term horizon, predictive indicators add value when properly applied. Long-term investors, however, may find many predictive indicators less useful.

When running Container Store's price analysis, check to measure Container Store's market volatility, profitability, liquidity, solvency, efficiency, growth potential, financial leverage, and other vital indicators. We have many different tools that can be utilized to determine how healthy Container Store is operating at the current time. Most of Container Store's value examination focuses on studying past and present price action to predict the probability of Container Store's future price movements. You can analyze the entity against its peers and the financial market as a whole to determine factors that move Container Store's price. Additionally, you may evaluate how the addition of Container Store to your portfolios can decrease your overall portfolio volatility.