Fast Food Stock Forecast - Triple Exponential Smoothing

FAST Stock  IDR 324.00  4.00  1.25%   
The Triple Exponential Smoothing forecasted value of Fast Food Indonesia on the next trading day is expected to be 321.99 with a mean absolute deviation of 5.87 and the sum of the absolute errors of 346.46. Fast Stock Forecast is based on your current time horizon.
  
Triple exponential smoothing for Fast Food - also known as the Winters method - is a refinement of the popular double exponential smoothing model with the addition of periodicity (seasonality) component. Simple exponential smoothing technique works best with data where there are no trend or seasonality components to the data. When Fast Food 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 trend in Fast Food price movement. However, neither of these exponential smoothing models address any seasonality of Fast Food Indonesia.

Fast Food Triple Exponential Smoothing Price Forecast For the 24th of November

Given 90 days horizon, the Triple Exponential Smoothing forecasted value of Fast Food Indonesia on the next trading day is expected to be 321.99 with a mean absolute deviation of 5.87, mean absolute percentage error of 71.34, and the sum of the absolute errors of 346.46.
Please note that although there have been many attempts to predict Fast 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 Fast Food's next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).

Fast Food Stock Forecast Pattern

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Fast Food Forecasted Value

In the context of forecasting Fast Food'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. Fast Food's downside and upside margins for the forecasting period are 319.91 and 324.07, respectively. We have considered Fast Food'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
324.00
319.91
Downside
321.99
Expected Value
324.07
Upside

Model Predictive Factors

The below table displays some essential indicators generated by the model showing the Triple Exponential Smoothing forecasting method's relative quality and the estimations of the prediction error of Fast Food stock data series using in forecasting. Note that when a statistical model is used to represent Fast Food 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 0.3402
MADMean absolute deviation5.8723
MAPEMean absolute percentage error0.0151
SAESum of the absolute errors346.465
As with simple exponential smoothing, in triple exponential smoothing models past Fast Food observations are given exponentially smaller weights as the observations get older. In other words, recent observations are given relatively more weight in forecasting than the older Fast Food Indonesia observations.

Predictive Modules for Fast Food

There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as Fast Food Indonesia. 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
321.92324.00326.08
Details
Intrinsic
Valuation
LowRealHigh
297.38299.46356.40
Details
Bollinger
Band Projection (param)
LowMiddleHigh
324.00324.00324.00
Details

Other Forecasting Options for Fast Food

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

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

Fast Food Indonesia 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 Fast Food'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 Fast Food's current price.

Fast Food Market Strength Events

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

Fast Food Risk Indicators

The analysis of Fast Food'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 Fast Food's investment and either accepting that risk or mitigating it. Along with some essential techniques for forecasting fast 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 Fast Stock

Fast Food financial ratios help investors to determine whether Fast 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 Fast with respect to the benefits of owning Fast Food security.