Alliance Data (Germany) Analysis

LID Stock  EUR 59.02  0.72  1.23%   
Alliance Data Systems is undervalued with Real Value of 66.14 and Hype Value of 59.02. The main objective of Alliance Data stock analysis is to determine its intrinsic value, which is an estimate of what Alliance Data Systems is worth, separate from its market price. There are two main types of Alliance Data's stock analysis: fundamental analysis and technical analysis. Fundamental analysis focuses on the financial and economic factors that affect Alliance Data's performance, such as revenue growth, earnings, and financial stability. Technical analysis, on the other hand, focuses on the price and volume data of Alliance Data's stock to identify patterns and trends that may indicate its future price movements.
The Alliance Data stock is traded in Germany on Dusseldorf Exchange, with the market opening at 08:00:00 and closing at 20:00:00 every Mon,Tue,Wed,Thu,Fri except for officially observed holidays in Germany. Alliance Data is usually not traded on GermanUnityDay, Christmas Day, Boxing Day, New Year 's Day, Good Friday, Easter Monday, International Workers ' Day. Alliance Stock trading window is adjusted to Europe/Berlin timezone.
  
Check out Correlation Analysis to better understand how to build diversified portfolios, which includes a position in Alliance Data Systems. Also, note that the market value of any company could be closely tied with the direction of predictive economic indicators such as signals in board of governors.

Alliance Data Systems Investment Alerts

Alliance Data appears to be risky and price may revert if volatility continues

Alliance Data Thematic Classifications

In addition to having Alliance Data stock in your portfolios, you can add positions using our predefined set of ideas and optimize them against your very unique investing style. A single investing idea is a collection of funds, stocks, ETFs, or cryptocurrencies that are programmatically selected from a pull of investment themes. After you determine your favorite investment opportunity, you can then obtain an optimal portfolio that will maximize potential returns on the chosen idea or minimize its exposure to market volatility. If you are a result-oriented investor, you can benefit from optimizing one of our existing themes to build an efficient portfolio against your specific investing outlook.

Technical Drivers

As of the 4th of January, Alliance Data shows the Mean Deviation of 1.81, risk adjusted performance of 0.1634, and Downside Deviation of 2.0. Our technical analysis interface gives you tools to check existing technical drivers of Alliance Data Systems, as well as the relationship between them.

Alliance Data Systems Price Movement Analysis

Execute Study
java.lang.NullPointerException: Cannot invoke "java.lang.Number.intValue()" because the return value of "sun.invoke.util.ValueConversions.primitiveConversion(sun.invoke.util.Wrapper, Object, boolean)" is null. The output start index for this execution was zero with a total number of output elements of zero. The Bollinger Bands is very popular indicator that was developed by John Bollinger. It consist of three lines. Alliance Data middle band is a simple moving average of its typical price. The upper and lower bands are (N) standard deviations above and below the middle band. The bands widen and narrow when the volatility of the price is higher or lower, respectively. The upper and lower bands can also be interpreted as price targets for Alliance Data Systems. When the price bounces off of the lower band and crosses the middle band, then the upper band becomes the price target.

Alliance Data Predictive Daily Indicators

Alliance Data intraday indicators are useful technical analysis tools used by many experienced traders. Just like the conventional technical analysis, daily indicators help intraday investors to analyze the price movement with the timing of Alliance Data stock daily movement. By combining multiple daily indicators into a single trading strategy, you can limit your risk while still earning strong returns on your managed positions.

Alliance Data Forecast Models

Alliance Data's time-series forecasting models are one of many Alliance Data's stock analysis techniques aimed at predicting future share value based on previously observed values. Time-series forecasting models ae widely used for non-stationary data. Non-stationary data are called the data whose statistical properties e.g. the mean and standard deviation are not constant over time but instead, these metrics vary over time. These non-stationary Alliance Data's historical data is usually called time-series. Some empirical experimentation suggests that the statistical forecasting models outperform the models based exclusively on fundamental analysis to predict the direction of the market movement and maximize returns from investment trading.

Be your own money manager

As an investor, your ultimate goal is to build wealth. Optimizing your investment portfolio is an essential element in this goal. Using our stock analysis tools, you can find out how much better you can do when adding Alliance Data to your portfolios without increasing risk or reducing expected return.

Did you try this?

Run Bonds Directory Now

   

Bonds Directory

Find actively traded corporate debentures issued by US companies
All  Next Launch Module

Additional Tools for Alliance Stock Analysis

When running Alliance Data's price analysis, check to measure Alliance Data'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 Alliance Data is operating at the current time. Most of Alliance Data's value examination focuses on studying past and present price action to predict the probability of Alliance Data's future price movements. You can analyze the entity against its peers and the financial market as a whole to determine factors that move Alliance Data's price. Additionally, you may evaluate how the addition of Alliance Data to your portfolios can decrease your overall portfolio volatility.