Fast Retailing Pink Sheet Forecast - Double Exponential Smoothing

FRCOF Stock  USD 335.90  15.25  4.76%   
The Double Exponential Smoothing forecasted value of Fast Retailing Co on the next trading day is expected to be 335.90 with a mean absolute deviation of 3.61 and the sum of the absolute errors of 212.98. Fast Pink Sheet Forecast is based on your current time horizon. We recommend always using this module together with an analysis of Fast Retailing's 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 Fast Retailing works best with periods where there are trends or seasonality.

Fast Retailing Double Exponential Smoothing Price Forecast For the 4th of December

Given 90 days horizon, the Double Exponential Smoothing forecasted value of Fast Retailing Co on the next trading day is expected to be 335.90 with a mean absolute deviation of 3.61, mean absolute percentage error of 96.85, and the sum of the absolute errors of 212.98.
Please note that although there have been many attempts to predict Fast Pink Sheet 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 Retailing's next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).

Fast Retailing Pink Sheet Forecast Pattern

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Fast Retailing Forecasted Value

In the context of forecasting Fast Retailing's Pink Sheet 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 Retailing's downside and upside margins for the forecasting period are 332.94 and 338.86, respectively. We have considered Fast Retailing'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
335.90
332.94
Downside
335.90
Expected Value
338.86
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 Fast Retailing pink sheet data series using in forecasting. Note that when a statistical model is used to represent Fast Retailing pink sheet, 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 -0.5522
MADMean absolute deviation3.6098
MAPEMean absolute percentage error0.0107
SAESum of the absolute errors212.98
When Fast Retailing Co 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 Fast Retailing Co 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 Fast Retailing observations are given relatively more weight in forecasting than the older observations.

Predictive Modules for Fast Retailing

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 Retailing. Regardless of method or technology, however, to accurately forecast the pink sheet market is more a matter of luck rather than a particular technique. Nevertheless, trying to predict the pink sheet 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
332.94335.90338.86
Details
Intrinsic
Valuation
LowRealHigh
280.88283.84369.49
Details
Bollinger
Band Projection (param)
LowMiddleHigh
321.62327.75333.88
Details

Other Forecasting Options for Fast Retailing

For every potential investor in Fast, whether a beginner or expert, Fast Retailing's price movement is the inherent factor that sparks whether it is viable to invest in it or hold it better. Fast Pink Sheet 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 Retailing's price trends.

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

Fast Retailing Technical and Predictive Analytics

The pink sheet market is financially volatile. Despite the volatility, there exist limitless possibilities of gaining profits and building passive income portfolios. With the complexity of Fast Retailing'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 Retailing's current price.

Fast Retailing Market Strength Events

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

Fast Retailing Risk Indicators

The analysis of Fast Retailing'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 Retailing's investment and either accepting that risk or mitigating it. Along with some essential techniques for forecasting fast pink sheet 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 Pink Sheet

Fast Retailing financial ratios help investors to determine whether Fast Pink Sheet 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 Retailing security.