Borusan Mannesmann (Turkey) Price History

Borusan Mannesmann Stock Price History Chart

Borusan Mannesmann December 23, 2024 Stock Price Synopsis

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

Borusan Stock Price History Data

The price series of Borusan Mannesmann for the period between Tue, Sep 24, 2024 and Mon, Dec 23, 2024 has a statistical range of 110.0 with a coefficient of variation of 4.76. The prices are distributed with arithmetic mean of 458.42. The median price for the last 90 days is 459.5. The company had 500:100 stock split on 7th of November 2013. Borusan Mannesmann Boru issued dividends on 2019-05-31.

Borusan Mannesmann 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 Borusan is vital when making an investment decision, and regardless of whether you use fundamental or technical analysis, your return on investment in Borusan Mannesmann Boru 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 Borusan Mannesmann stock prices may prove useful in developing a viable investing in Borusan Mannesmann

Borusan Mannesmann 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 Borusan Mannesmann's price direction in advance. Along with the technical and fundamental analysis of Borusan Stock historical price patterns, it is also worthwhile for investors to track various predictive indicators of Borusan 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 Borusan Mannesmann's price analysis, check to measure Borusan Mannesmann'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 Borusan Mannesmann is operating at the current time. Most of Borusan Mannesmann's value examination focuses on studying past and present price action to predict the probability of Borusan Mannesmann's future price movements. You can analyze the entity against its peers and the financial market as a whole to determine factors that move Borusan Mannesmann's price. Additionally, you may evaluate how the addition of Borusan Mannesmann to your portfolios can decrease your overall portfolio volatility.