Ganfeng Lithium Co Stock Price History

Ganfeng Lithium Pink Sheet Price History Chart

Ganfeng Lithium December 2, 2024 Pink Sheet Price Synopsis

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

Ganfeng Pink Sheet Price History Data

The price series of Ganfeng Lithium for the period between Tue, Sep 3, 2024 and Mon, Dec 2, 2024 has a statistical range of 1.57 with a coefficient of variation of 15.39. Under current investment horizon, the daily prices are spread out with arithmetic mean of 2.6. The median price for the last 90 days is 2.7. The company completed 14:10 stock split on 19th of August 2022. Ganfeng Lithium completed dividends distribution on 2022-06-16.

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

Ganfeng Lithium technical pink sheet 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, pink sheet market cycles, or different charting patterns.

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