Fukuyama Transporting Stock Forecast - Polynomial Regression
| FUY Stock | EUR 23.00 0.40 1.77% |
The Polynomial Regression forecasted value of Fukuyama Transporting Co on the next trading day is expected to be 21.96 with a mean absolute deviation of 0.43 and the sum of the absolute errors of 26.64. Fukuyama Stock Forecast is based on your current time horizon. We recommend always using this module together with an analysis of Fukuyama Transporting's historical fundamentals, such as revenue growth or operating cash flow patterns.
Fukuyama |
Fukuyama Transporting Polynomial Regression Price Forecast For the 30th of November
Given 90 days horizon, the Polynomial Regression forecasted value of Fukuyama Transporting Co on the next trading day is expected to be 21.96 with a mean absolute deviation of 0.43, mean absolute percentage error of 0.31, and the sum of the absolute errors of 26.64.Please note that although there have been many attempts to predict Fukuyama 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 Fukuyama Transporting's next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).
Fukuyama Transporting Stock Forecast Pattern
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Fukuyama Transporting Forecasted Value
In the context of forecasting Fukuyama Transporting'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. Fukuyama Transporting's downside and upside margins for the forecasting period are 20.12 and 23.80, respectively. We have considered Fukuyama Transporting'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 Polynomial Regression forecasting method's relative quality and the estimations of the prediction error of Fukuyama Transporting stock data series using in forecasting. Note that when a statistical model is used to represent Fukuyama Transporting 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.| AIC | Akaike Information Criteria | 118.7701 |
| Bias | Arithmetic mean of the errors | None |
| MAD | Mean absolute deviation | 0.4296 |
| MAPE | Mean absolute percentage error | 0.0192 |
| SAE | Sum of the absolute errors | 26.6378 |
Predictive Modules for Fukuyama Transporting
There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as Fukuyama Transporting. 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.Other Forecasting Options for Fukuyama Transporting
For every potential investor in Fukuyama, whether a beginner or expert, Fukuyama Transporting's price movement is the inherent factor that sparks whether it is viable to invest in it or hold it better. Fukuyama Stock price charts are filled with many 'noises.' These noises can hugely alter the decision one can make regarding investing in Fukuyama. Basic forecasting techniques help filter out the noise by identifying Fukuyama Transporting's price trends.Fukuyama Transporting 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 Fukuyama Transporting stock to make a market-neutral strategy. Peer analysis of Fukuyama Transporting could also be used in its relative valuation, which is a method of valuing Fukuyama Transporting by comparing valuation metrics with similar companies.
| Risk & Return | Correlation |
Fukuyama Transporting 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 Fukuyama Transporting'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 Fukuyama Transporting's current price.| Cycle Indicators | ||
| Math Operators | ||
| Math Transform | ||
| Momentum Indicators | ||
| Overlap Studies | ||
| Pattern Recognition | ||
| Price Transform | ||
| Statistic Functions | ||
| Volatility Indicators | ||
| Volume Indicators |
Fukuyama Transporting Market Strength Events
Market strength indicators help investors to evaluate how Fukuyama Transporting stock reacts to ongoing and evolving market conditions. The investors can use it to make informed decisions about market timing, and determine when trading Fukuyama Transporting shares will generate the highest return on investment. By undertsting and applying Fukuyama Transporting stock market strength indicators, traders can identify Fukuyama Transporting Co entry and exit signals to maximize returns.
| Daily Balance Of Power | 9.2 T | |||
| Rate Of Daily Change | 1.02 | |||
| Day Median Price | 23.0 | |||
| Day Typical Price | 23.0 | |||
| Price Action Indicator | 0.2 | |||
| Period Momentum Indicator | 0.4 | |||
| Relative Strength Index | 37.09 |
Fukuyama Transporting Risk Indicators
The analysis of Fukuyama Transporting'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 Fukuyama Transporting's investment and either accepting that risk or mitigating it. Along with some essential techniques for forecasting fukuyama 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.
| Mean Deviation | 1.14 | |||
| Semi Deviation | 1.69 | |||
| Standard Deviation | 1.83 | |||
| Variance | 3.35 | |||
| Downside Variance | 5.22 | |||
| Semi Variance | 2.85 | |||
| Expected Short fall | (1.52) |
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 Fukuyama Stock
Fukuyama Transporting financial ratios help investors to determine whether Fukuyama 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 Fukuyama with respect to the benefits of owning Fukuyama Transporting security.