Fast Retailing Pink Sheet Forecast - 8 Period Moving Average
| FRCOY Stock | USD 26.50 0.61 2.25% |
The 8 Period Moving Average forecasted value of Fast Retailing Co on the next trading day is expected to be 26.58 with a mean absolute deviation of 0.73 and the sum of the absolute errors of 39.63. Fast Pink Sheet Forecast is based on your current time horizon. Investors can use this forecasting interface to forecast Fast Retailing stock prices and determine the direction of Fast Retailing Co's future trends based on various well-known forecasting models. 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.
Check out Historical Fundamental Analysis of Fast Retailing to cross-verify your projections. Fast |
Most investors in Fast Retailing cannot accurately predict what will happen the next trading day because, historically, stock markets tend to be unpredictable and even illogical. Modeling turbulent structures requires applying different statistical methods, techniques, and algorithms to find hidden data structures or patterns within the Fast Retailing's time series price data and predict how it will affect future prices. One of these methodologies is forecasting, which interprets Fast Retailing's price structures and extracts relationships that further increase the generated results' accuracy.
An 8-period moving average forecast model for Fast Retailing is based on an artificially constructed time series of Fast Retailing daily prices in which the value for a trading day is replaced by the mean of that value and the values for 8 of preceding and succeeding time periods. This model is best suited for price series data that changes over time. Fast Retailing 8 Period Moving Average Price Forecast For the 10th of May
Given 90 days horizon, the 8 Period Moving Average forecasted value of Fast Retailing Co on the next trading day is expected to be 26.58 with a mean absolute deviation of 0.73, mean absolute percentage error of 0.91, and the sum of the absolute errors of 39.63.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 24.77 and 28.40, 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.
Model Predictive Factors
The below table displays some essential indicators generated by the model showing the 8 Period Moving Average 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.| AIC | Akaike Information Criteria | 105.1517 |
| Bias | Arithmetic mean of the errors | 0.1104 |
| MAD | Mean absolute deviation | 0.7338 |
| MAPE | Mean absolute percentage error | 0.0259 |
| SAE | Sum of the absolute errors | 39.6262 |
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.Sophisticated investors, who have witnessed many market ups and downs, anticipate that the market will even out over time. This tendency of Fast Retailing's price to converge to an average value over time is called mean reversion. However, historically, high market prices usually discourage investors that believe in mean reversion to invest, while low prices are viewed as an opportunity to buy.
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.| Cycle Indicators | ||
| Math Operators | ||
| Math Transform | ||
| Momentum Indicators | ||
| Overlap Studies | ||
| Pattern Recognition | ||
| Price Transform | ||
| Statistic Functions | ||
| Volatility Indicators | ||
| Volume Indicators |
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.
| Accumulation Distribution | 582.9 | |||
| Daily Balance Of Power | (0.84) | |||
| Rate Of Daily Change | 0.98 | |||
| Day Median Price | 26.19 | |||
| Day Typical Price | 26.29 | |||
| Price Action Indicator | 0.01 | |||
| Period Momentum Indicator | (0.61) |
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.
| Mean Deviation | 1.39 | |||
| Semi Deviation | 1.61 | |||
| Standard Deviation | 1.79 | |||
| Variance | 3.21 | |||
| Downside Variance | 2.91 | |||
| Semi Variance | 2.6 | |||
| Expected Short fall | (1.64) |
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.
Some investors attempt to determine whether the market's mood is bullish or bearish by monitoring changes in market sentiment. Unlike more traditional methods such as technical analysis, investor sentiment usually refers to the aggregate attitude towards Fast Retailing in the overall investment community. So, suppose investors can accurately measure the market's sentiment. In that case, they can use it for their benefit. For example, some tools to gauge market sentiment could be utilized using contrarian indexes, Fast Retailing's short interest history, or implied volatility extrapolated from Fast Retailing options trading.
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Try AI Portfolio ArchitectCheck out Historical Fundamental Analysis of Fast Retailing to cross-verify your projections. You can also try the Commodity Directory module to find actively traded commodities issued by global exchanges.
Complementary Tools for Fast Pink Sheet analysis
When running Fast Retailing's price analysis, check to measure Fast Retailing'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 Fast Retailing is operating at the current time. Most of Fast Retailing's value examination focuses on studying past and present price action to predict the probability of Fast Retailing's future price movements. You can analyze the entity against its peers and the financial market as a whole to determine factors that move Fast Retailing's price. Additionally, you may evaluate how the addition of Fast Retailing to your portfolios can decrease your overall portfolio volatility.
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