AUTOMATIC Forecast - 4 Period Moving Average
| 053015AF0 | 79.35 5.06 5.99% |
The 4 Period Moving Average forecasted value of AUTOMATIC DATA PROCESSING on the next trading day is expected to be 80.12 with a mean absolute deviation of 0.54 and the sum of the absolute errors of 31.34. AUTOMATIC Bond Forecast is based on your current time horizon. Investors can use this forecasting interface to forecast AUTOMATIC stock prices and determine the direction of AUTOMATIC DATA PROCESSING's future trends based on various well-known forecasting models. We recommend always using this module together with an analysis of AUTOMATIC's historical fundamentals, such as revenue growth or operating cash flow patterns.
AUTOMATIC |
AUTOMATIC 4 Period Moving Average Price Forecast For the 13th of December 2024
Given 90 days horizon, the 4 Period Moving Average forecasted value of AUTOMATIC DATA PROCESSING on the next trading day is expected to be 80.12 with a mean absolute deviation of 0.54, mean absolute percentage error of 1.10, and the sum of the absolute errors of 31.34.Please note that although there have been many attempts to predict AUTOMATIC Bond 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 AUTOMATIC's next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).
AUTOMATIC Bond Forecast Pattern
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AUTOMATIC Forecasted Value
In the context of forecasting AUTOMATIC's Bond 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. AUTOMATIC's downside and upside margins for the forecasting period are 78.99 and 81.25, respectively. We have considered AUTOMATIC'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.
Model Predictive Factors
The below table displays some essential indicators generated by the model showing the 4 Period Moving Average forecasting method's relative quality and the estimations of the prediction error of AUTOMATIC bond data series using in forecasting. Note that when a statistical model is used to represent AUTOMATIC bond, 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.| AIC | Akaike Information Criteria | 112.6935 |
| Bias | Arithmetic mean of the errors | 0.2722 |
| MAD | Mean absolute deviation | 0.5403 |
| MAPE | Mean absolute percentage error | 0.0066 |
| SAE | Sum of the absolute errors | 31.335 |
Predictive Modules for AUTOMATIC
There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as AUTOMATIC DATA PROCESSING. Regardless of method or technology, however, to accurately forecast the bond market is more a matter of luck rather than a particular technique. Nevertheless, trying to predict the bond 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.Other Forecasting Options for AUTOMATIC
For every potential investor in AUTOMATIC, whether a beginner or expert, AUTOMATIC's price movement is the inherent factor that sparks whether it is viable to invest in it or hold it better. AUTOMATIC Bond price charts are filled with many 'noises.' These noises can hugely alter the decision one can make regarding investing in AUTOMATIC. Basic forecasting techniques help filter out the noise by identifying AUTOMATIC's price trends.AUTOMATIC 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 AUTOMATIC bond to make a market-neutral strategy. Peer analysis of AUTOMATIC could also be used in its relative valuation, which is a method of valuing AUTOMATIC by comparing valuation metrics with similar companies.
| Risk & Return | Correlation |
AUTOMATIC DATA PROCESSING Technical and Predictive Analytics
The bond market is financially volatile. Despite the volatility, there exist limitless possibilities of gaining profits and building passive income portfolios. With the complexity of AUTOMATIC'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 AUTOMATIC's current price.| Cycle Indicators | ||
| Math Operators | ||
| Math Transform | ||
| Momentum Indicators | ||
| Overlap Studies | ||
| Pattern Recognition | ||
| Price Transform | ||
| Statistic Functions | ||
| Volatility Indicators | ||
| Volume Indicators |
AUTOMATIC Market Strength Events
Market strength indicators help investors to evaluate how AUTOMATIC bond reacts to ongoing and evolving market conditions. The investors can use it to make informed decisions about market timing, and determine when trading AUTOMATIC shares will generate the highest return on investment. By undertsting and applying AUTOMATIC bond market strength indicators, traders can identify AUTOMATIC DATA PROCESSING entry and exit signals to maximize returns.
| Daily Balance Of Power | (9,223,372,036,855) | |||
| Rate Of Daily Change | 0.94 | |||
| Day Median Price | 79.35 | |||
| Day Typical Price | 79.35 | |||
| Price Action Indicator | (2.53) | |||
| Period Momentum Indicator | (5.06) | |||
| Relative Strength Index | 54.13 |
AUTOMATIC Risk Indicators
The analysis of AUTOMATIC'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 AUTOMATIC's investment and either accepting that risk or mitigating it. Along with some essential techniques for forecasting automatic bond 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. One of the essential factors to consider when estimating the risk of default for a bond instrument is its duration, which is the bond's price sensitivity to changes in interest rates. The duration of AUTOMATIC DATA PROCESSING bond is primarily affected by its yield, coupon rate, and time to maturity. The duration of a bond will be higher the lower its coupon, lower its yield, and longer the time left to maturity.
| Mean Deviation | 0.5655 | |||
| Standard Deviation | 1.24 | |||
| Variance | 1.53 |
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.Other Information on Investing in AUTOMATIC Bond
AUTOMATIC financial ratios help investors to determine whether AUTOMATIC Bond is cheap or expensive when compared to a particular measure, such as profits or enterprise value. In other words, they help investors to determine the cost of investment in AUTOMATIC with respect to the benefits of owning AUTOMATIC security.