Shanghai (China) Price on December 6, 2024

Shanghai Valuation on December 6, 2024

Shanghai Trading Date Momentum on December 6, 2024

On December 09 2024 Shanghai SK Automation was traded for  43.05  at the closing time. The highest price during the trading period was 43.77  and the lowest recorded bid was listed for  42.02 . The volume for the day was 2.3 M. This history from December 9, 2024 contributed to the next trading day price jump. The daily price change to the next closing price was 1.65% . The trading price change to the current price is 2.64% .

Shanghai SK Automation Fundamentals Correlations and Trends

By evaluating Shanghai's financials over time, investors can gain insight into future company performance. However, you can also analyze the published financial statements to find patterns among Shanghai's main balance sheet or income statement drivers and many other relevant indicators that can statistically be found significantly correlated or uncorrelated. Shanghai financial account trend analysis is a perfect complement when working with valuation or volatility modules.

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

Shanghai 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.

Market strength indicators help investors to evaluate how Shanghai stock reacts to ongoing and evolving market conditions. The investors can use it to make informed decisions about market timing, and determine when trading Shanghai shares will generate the highest return on investment. By undertsting and applying Shanghai stock market strength indicators, traders can identify Shanghai SK Automation entry and exit signals to maximize returns

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