Swiss Life Holding Stock Price on August 16, 2024

Swiss Life Valuation on August 16, 2024

Swiss Life Trading Date Momentum on August 16, 2024

On August 19 2024 Swiss Life Holding was traded for  752.54  at the closing time. The highest daily price throughout the period was 752.54  and the lowest price was  752.54 . There was no trading activity during the period 1.0. Lack of trading volume on 08/19/2024 did not result in any price rise and fall. The trading price change to current closing price is 2.32% .

Swiss Life Holding Fundamentals Correlations and Trends

By evaluating Swiss Life'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 Swiss Life's main balance sheet or income statement drivers and many other relevant indicators that can statistically be found significantly correlated or uncorrelated. Swiss financial account trend analysis is a perfect complement when working with valuation or volatility modules.

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

Swiss Life 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.

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

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