Hyster-Yale Materials Stock Forecast - Naive Prediction
HYEA Stock | EUR 52.00 1.50 2.80% |
The Naive Prediction forecasted value of Hyster Yale Materials Handling on the next trading day is expected to be 57.35 with a mean absolute deviation of 1.10 and the sum of the absolute errors of 67.01. Hyster-Yale Stock Forecast is based on your current time horizon. We recommend always using this module together with an analysis of Hyster-Yale Materials' historical fundamentals, such as revenue growth or operating cash flow patterns.
Hyster-Yale |
Hyster-Yale Materials Naive Prediction Price Forecast For the 28th of November
Given 90 days horizon, the Naive Prediction forecasted value of Hyster Yale Materials Handling on the next trading day is expected to be 57.35 with a mean absolute deviation of 1.10, mean absolute percentage error of 2.33, and the sum of the absolute errors of 67.01.Please note that although there have been many attempts to predict Hyster-Yale 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 Hyster-Yale Materials' next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).
Hyster-Yale Materials Stock Forecast Pattern
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Hyster-Yale Materials Forecasted Value
In the context of forecasting Hyster-Yale Materials' 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. Hyster-Yale Materials' downside and upside margins for the forecasting period are 54.19 and 60.51, respectively. We have considered Hyster-Yale Materials' 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 Naive Prediction forecasting method's relative quality and the estimations of the prediction error of Hyster-Yale Materials stock data series using in forecasting. Note that when a statistical model is used to represent Hyster-Yale Materials 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 | 118.9558 |
Bias | Arithmetic mean of the errors | None |
MAD | Mean absolute deviation | 1.0986 |
MAPE | Mean absolute percentage error | 0.0204 |
SAE | Sum of the absolute errors | 67.0125 |
Predictive Modules for Hyster-Yale Materials
There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as Hyster Yale Materials. 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 Hyster-Yale Materials
For every potential investor in Hyster-Yale, whether a beginner or expert, Hyster-Yale Materials' price movement is the inherent factor that sparks whether it is viable to invest in it or hold it better. Hyster-Yale Stock price charts are filled with many 'noises.' These noises can hugely alter the decision one can make regarding investing in Hyster-Yale. Basic forecasting techniques help filter out the noise by identifying Hyster-Yale Materials' price trends.Hyster-Yale Materials 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 Hyster-Yale Materials stock to make a market-neutral strategy. Peer analysis of Hyster-Yale Materials could also be used in its relative valuation, which is a method of valuing Hyster-Yale Materials by comparing valuation metrics with similar companies.
Risk & Return | Correlation |
Hyster Yale Materials 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 Hyster-Yale Materials' 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 Hyster-Yale Materials' current price.Cycle Indicators | ||
Math Operators | ||
Math Transform | ||
Momentum Indicators | ||
Overlap Studies | ||
Pattern Recognition | ||
Price Transform | ||
Statistic Functions | ||
Volatility Indicators | ||
Volume Indicators |
Hyster-Yale Materials Market Strength Events
Market strength indicators help investors to evaluate how Hyster-Yale Materials stock reacts to ongoing and evolving market conditions. The investors can use it to make informed decisions about market timing, and determine when trading Hyster-Yale Materials shares will generate the highest return on investment. By undertsting and applying Hyster-Yale Materials stock market strength indicators, traders can identify Hyster Yale Materials Handling entry and exit signals to maximize returns.
Daily Balance Of Power | (9,223,372,036,855) | |||
Rate Of Daily Change | 0.97 | |||
Day Median Price | 52.0 | |||
Day Typical Price | 52.0 | |||
Price Action Indicator | (0.75) | |||
Period Momentum Indicator | (1.50) |
Hyster-Yale Materials Risk Indicators
The analysis of Hyster-Yale Materials' 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 Hyster-Yale Materials' investment and either accepting that risk or mitigating it. Along with some essential techniques for forecasting hyster-yale 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 | 2.15 | |||
Standard Deviation | 3.12 | |||
Variance | 9.71 |
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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Additional Information and Resources on Investing in Hyster-Yale Stock
When determining whether Hyster Yale Materials offers a strong return on investment in its stock, a comprehensive analysis is essential. The process typically begins with a thorough review of Hyster-Yale Materials' financial statements, including income statements, balance sheets, and cash flow statements, to assess its financial health. Key financial ratios are used to gauge profitability, efficiency, and growth potential of Hyster Yale Materials Handling Stock. Outlined below are crucial reports that will aid in making a well-informed decision on Hyster Yale Materials Handling Stock:Check out Historical Fundamental Analysis of Hyster-Yale Materials to cross-verify your projections. You can also try the Portfolio Analyzer module to portfolio analysis module that provides access to portfolio diagnostics and optimization engine.