Genuine Parts Stock Forecast - Double Exponential Smoothing

GPT Stock  EUR 120.05  0.25  0.21%   
The Double Exponential Smoothing forecasted value of Genuine Parts on the next trading day is expected to be 120.29 with a mean absolute deviation of 2.23 and the sum of the absolute errors of 131.73. Genuine Stock Forecast is based on your current time horizon. We recommend always using this module together with an analysis of Genuine Parts' historical fundamentals, such as revenue growth or operating cash flow patterns.
  
Double exponential smoothing - also known as Holt exponential smoothing is a refinement of the popular simple exponential smoothing model with an additional trending component. Double exponential smoothing model for Genuine Parts works best with periods where there are trends or seasonality.

Genuine Parts Double Exponential Smoothing Price Forecast For the 3rd of December

Given 90 days horizon, the Double Exponential Smoothing forecasted value of Genuine Parts on the next trading day is expected to be 120.29 with a mean absolute deviation of 2.23, mean absolute percentage error of 18.21, and the sum of the absolute errors of 131.73.
Please note that although there have been many attempts to predict Genuine 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 Genuine Parts' next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).

Genuine Parts Stock Forecast Pattern

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Genuine Parts Forecasted Value

In the context of forecasting Genuine Parts' 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. Genuine Parts' downside and upside margins for the forecasting period are 117.18 and 123.40, respectively. We have considered Genuine Parts' 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
120.05
117.18
Downside
120.29
Expected Value
123.40
Upside

Model Predictive Factors

The below table displays some essential indicators generated by the model showing the Double Exponential Smoothing forecasting method's relative quality and the estimations of the prediction error of Genuine Parts stock data series using in forecasting. Note that when a statistical model is used to represent Genuine Parts 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 CriteriaHuge
BiasArithmetic mean of the errors 0.565
MADMean absolute deviation2.2327
MAPEMean absolute percentage error0.0194
SAESum of the absolute errors131.7307
When Genuine Parts prices exhibit either an increasing or decreasing trend over time, simple exponential smoothing forecasts tend to lag behind observations. Double exponential smoothing is designed to address this type of data series by taking into account any Genuine Parts trend in the prices. So in double exponential smoothing past observations are given exponentially smaller weights as the observations get older. In other words, recent Genuine Parts observations are given relatively more weight in forecasting than the older observations.

Predictive Modules for Genuine Parts

There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as Genuine Parts. 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
116.94120.05123.16
Details
Intrinsic
Valuation
LowRealHigh
115.98119.09122.20
Details
Bollinger
Band Projection (param)
LowMiddleHigh
103.73114.74125.74
Details

Other Forecasting Options for Genuine Parts

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

Genuine Parts 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 Genuine Parts stock to make a market-neutral strategy. Peer analysis of Genuine Parts could also be used in its relative valuation, which is a method of valuing Genuine Parts by comparing valuation metrics with similar companies.
 Risk & Return  Correlation

Genuine Parts 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 Genuine Parts' 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 Genuine Parts' current price.

Genuine Parts Market Strength Events

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

Genuine Parts Risk Indicators

The analysis of Genuine Parts' 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 Genuine Parts' investment and either accepting that risk or mitigating it. Along with some essential techniques for forecasting genuine 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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Other Information on Investing in Genuine Stock

Genuine Parts financial ratios help investors to determine whether Genuine Stock 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 Genuine with respect to the benefits of owning Genuine Parts security.