Dominos Pizza Stock Forecast - 20 Period Moving Average

DPZ Stock  USD 445.85  6.88  1.57%   
The 20 Period Moving Average forecasted value of Dominos Pizza on the next trading day is expected to be 434.84 with a mean absolute deviation of 10.20 and the sum of the absolute errors of 418.17. Dominos Stock Forecast is based on your current time horizon.
  
At this time, Dominos Pizza's Inventory Turnover is fairly stable compared to the past year. Receivables Turnover is likely to rise to 19.99 in 2024, whereas Payables Turnover is likely to drop 15.86 in 2024. . Common Stock Shares Outstanding is likely to rise to about 61 M in 2024. Net Income Applicable To Common Shares is likely to rise to about 546.1 M in 2024.
A commonly used 20-period moving average forecast model for Dominos Pizza is based on a synthetically constructed Dominos Pizzadaily 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.

Dominos Pizza 20 Period Moving Average Price Forecast For the 23rd of November

Given 90 days horizon, the 20 Period Moving Average forecasted value of Dominos Pizza on the next trading day is expected to be 434.84 with a mean absolute deviation of 10.20, mean absolute percentage error of 143.60, and the sum of the absolute errors of 418.17.
Please note that although there have been many attempts to predict Dominos 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 Dominos Pizza's next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).

Dominos Pizza Stock Forecast Pattern

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Dominos Pizza Forecasted Value

In the context of forecasting Dominos Pizza'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. Dominos Pizza's downside and upside margins for the forecasting period are 433.32 and 436.37, respectively. We have considered Dominos Pizza'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
445.85
433.32
Downside
434.84
Expected Value
436.37
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 Dominos Pizza stock data series using in forecasting. Note that when a statistical model is used to represent Dominos Pizza 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 Criteria86.32
BiasArithmetic mean of the errors -6.1797
MADMean absolute deviation10.1994
MAPEMean absolute percentage error0.0235
SAESum of the absolute errors418.1735
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. Dominos Pizza 20-period moving average forecast can only be used reliably to predict one or two periods into the future.

Predictive Modules for Dominos Pizza

There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as Dominos Pizza. 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
444.32445.85447.38
Details
Intrinsic
Valuation
LowRealHigh
399.74401.27490.44
Details
Bollinger
Band Projection (param)
LowMiddleHigh
405.39432.30459.21
Details
34 Analysts
Consensus
LowTargetHigh
374.62411.67456.95
Details

Other Forecasting Options for Dominos Pizza

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

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 Risk & Return  Correlation

Dominos Pizza 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 Dominos Pizza'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 Dominos Pizza's current price.

Dominos Pizza Market Strength Events

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

Dominos Pizza Risk Indicators

The analysis of Dominos Pizza'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 Dominos Pizza's investment and either accepting that risk or mitigating it. Along with some essential techniques for forecasting dominos 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.

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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 Dominos Stock Analysis

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