Alliance Data Stock Forecast - 20 Period Moving Average

0HCR Stock   58.29  2.23  3.98%   
The 20 Period Moving Average forecasted value of Alliance Data Systems on the next trading day is expected to be 56.34 with a mean absolute deviation of 2.94 and the sum of the absolute errors of 120.73. Alliance Stock Forecast is based on your current time horizon.
  
At this time, Alliance Data's Net Tangible Assets are comparatively stable compared to the past year. Accounts Payable is likely to gain to about 17.2 B in 2024, whereas Net Debt is likely to drop slightly above 1.4 B in 2024.
A commonly used 20-period moving average forecast model for Alliance Data Systems is based on a synthetically constructed Alliance Datadaily price series in which the value for a trading day is replaced by the mean of that value and the values for 20 of preceding and succeeding time periods. This model is best suited for price series data that changes over time.

Alliance Data 20 Period Moving Average Price Forecast For the 24th of November

Given 90 days horizon, the 20 Period Moving Average forecasted value of Alliance Data Systems on the next trading day is expected to be 56.34 with a mean absolute deviation of 2.94, mean absolute percentage error of 15.31, and the sum of the absolute errors of 120.73.
Please note that although there have been many attempts to predict Alliance Stock prices using its time series forecasting, we generally do not recommend using it to place bets in the real market. The most commonly used models for forecasting predictions are the autoregressive models, which specify that Alliance Data's next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).

Alliance Data Stock Forecast Pattern

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Alliance Data Forecasted Value

In the context of forecasting Alliance Data's Stock value on the next trading day, we examine the predictive performance of the model to find good statistically significant boundaries of downside and upside scenarios. Alliance Data's downside and upside margins for the forecasting period are 52.76 and 59.92, respectively. We have considered Alliance Data's daily market price to evaluate the above model's predictive performance. Remember, however, there is no scientific proof or empirical evidence that traditional linear or nonlinear forecasting models outperform artificial intelligence and frequency domain models to provide accurate forecasts consistently.
Market Value
58.29
56.34
Expected Value
59.92
Upside

Model Predictive Factors

The below table displays some essential indicators generated by the model showing the 20 Period Moving Average forecasting method's relative quality and the estimations of the prediction error of Alliance Data stock data series using in forecasting. Note that when a statistical model is used to represent Alliance Data stock, the representation will rarely be exact; so some information will be lost using the model to explain the process. AIC estimates the relative amount of information lost by a given model: the less information a model loses, the higher its quality.
AICAkaike Information Criteria84.0815
BiasArithmetic mean of the errors -2.0371
MADMean absolute deviation2.9447
MAPEMean absolute percentage error0.0535
SAESum of the absolute errors120.734
The eieght-period moving average method has an advantage over other forecasting models in that it does smooth out peaks and valleys in a set of daily observations. Alliance Data Systems 20-period moving average forecast can only be used reliably to predict one or two periods into the future.

Predictive Modules for Alliance Data

There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as Alliance Data Systems. Regardless of method or technology, however, to accurately forecast the stock market is more a matter of luck rather than a particular technique. Nevertheless, trying to predict the stock market accurately is still an essential part of the overall investment decision process. Using different forecasting techniques and comparing the results might improve your chances of accuracy even though unexpected events may often change the market sentiment and impact your forecasting results.
Hype
Prediction
LowEstimatedHigh
54.7258.3361.94
Details
Intrinsic
Valuation
LowRealHigh
52.4856.0959.70
Details

Other Forecasting Options for Alliance Data

For every potential investor in Alliance, whether a beginner or expert, Alliance Data's price movement is the inherent factor that sparks whether it is viable to invest in it or hold it better. Alliance Stock price charts are filled with many 'noises.' These noises can hugely alter the decision one can make regarding investing in Alliance. Basic forecasting techniques help filter out the noise by identifying Alliance Data's price trends.

Alliance Data Related Equities

One of the popular trading techniques among algorithmic traders is to use market-neutral strategies where every trade hedges away some risk. Because there are two separate transactions required, even if one position performs unexpectedly, the other equity can make up some of the losses. Below are some of the equities that can be combined with Alliance Data stock to make a market-neutral strategy. Peer analysis of Alliance Data could also be used in its relative valuation, which is a method of valuing Alliance Data by comparing valuation metrics with similar companies.
 Risk & Return  Correlation

Alliance Data Systems Technical and Predictive Analytics

The stock market is financially volatile. Despite the volatility, there exist limitless possibilities of gaining profits and building passive income portfolios. With the complexity of Alliance Data's price movements, a comprehensive understanding of forecasting methods that an investor can rely on to make the right move is invaluable. These methods predict trends that assist an investor in predicting the movement of Alliance Data's current price.

Alliance Data Market Strength Events

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

Alliance Data Risk Indicators

The analysis of Alliance Data's basic risk indicators is one of the essential steps in accurately forecasting its future price. The process involves identifying the amount of risk involved in Alliance Data's investment and either accepting that risk or mitigating it. Along with some essential techniques for forecasting alliance stock prices, we also provide a set of basic risk indicators that can assist in the individual investment decision or help in hedging the risk of your existing portfolios.
Please note, the risk measures we provide can be used independently or collectively to perform a risk assessment. When comparing two potential investments, we recommend comparing similar equities with homogenous growth potential and valuation from related markets to determine which investment holds the most risk.

Also Currently Popular

Analyzing currently trending equities could be an opportunity to develop a better portfolio based on different market momentums that they can trigger. Utilizing the top trending stocks is also useful when creating a market-neutral strategy or pair trading technique involving a short or a long position in a currently trending equity.

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.