Feature Integration Stock Forecast - Double Exponential Smoothing
| 4951 Stock | TWD 70.00 0.30 0.43% |
The Double Exponential Smoothing forecasted value of Feature Integration Technology on the next trading day is expected to be 69.90 with a mean absolute deviation of 0.66 and the sum of the absolute errors of 39.90. Feature Stock Forecast is based on your current time horizon.
Feature |
Feature Integration Double Exponential Smoothing Price Forecast For the 1st of December
Given 90 days horizon, the Double Exponential Smoothing forecasted value of Feature Integration Technology on the next trading day is expected to be 69.90 with a mean absolute deviation of 0.66, mean absolute percentage error of 0.82, and the sum of the absolute errors of 39.90.Please note that although there have been many attempts to predict Feature 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 Feature Integration's next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).
Feature Integration Stock Forecast Pattern
| Backtest Feature Integration | Feature Integration Price Prediction | Buy or Sell Advice |
Feature Integration Forecasted Value
In the context of forecasting Feature Integration'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. Feature Integration's downside and upside margins for the forecasting period are 68.55 and 71.25, respectively. We have considered Feature Integration'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 Double Exponential Smoothing forecasting method's relative quality and the estimations of the prediction error of Feature Integration stock data series using in forecasting. Note that when a statistical model is used to represent Feature Integration 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 | Huge |
| Bias | Arithmetic mean of the errors | -0.0683 |
| MAD | Mean absolute deviation | 0.665 |
| MAPE | Mean absolute percentage error | 0.0093 |
| SAE | Sum of the absolute errors | 39.9 |
Predictive Modules for Feature Integration
There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as Feature Integration. 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 Feature Integration
For every potential investor in Feature, whether a beginner or expert, Feature Integration's price movement is the inherent factor that sparks whether it is viable to invest in it or hold it better. Feature Stock price charts are filled with many 'noises.' These noises can hugely alter the decision one can make regarding investing in Feature. Basic forecasting techniques help filter out the noise by identifying Feature Integration's price trends.Feature Integration 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 Feature Integration stock to make a market-neutral strategy. Peer analysis of Feature Integration could also be used in its relative valuation, which is a method of valuing Feature Integration by comparing valuation metrics with similar companies.
| Risk & Return | Correlation |
Feature Integration 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 Feature Integration'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 Feature Integration's current price.| Cycle Indicators | ||
| Math Operators | ||
| Math Transform | ||
| Momentum Indicators | ||
| Overlap Studies | ||
| Pattern Recognition | ||
| Price Transform | ||
| Statistic Functions | ||
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| Volume Indicators |
Feature Integration Market Strength Events
Market strength indicators help investors to evaluate how Feature Integration stock reacts to ongoing and evolving market conditions. The investors can use it to make informed decisions about market timing, and determine when trading Feature Integration shares will generate the highest return on investment. By undertsting and applying Feature Integration stock market strength indicators, traders can identify Feature Integration Technology entry and exit signals to maximize returns.
Feature Integration Risk Indicators
The analysis of Feature Integration'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 Feature Integration's investment and either accepting that risk or mitigating it. Along with some essential techniques for forecasting feature 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 | 0.9564 | |||
| Standard Deviation | 1.34 | |||
| Variance | 1.81 |
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.
Pair Trading with Feature Integration
One of the main advantages of trading using pair correlations is that every trade hedges away some risk. Because there are two separate transactions required, even if Feature Integration position performs unexpectedly, the other equity can make up some of the losses. Pair trading also minimizes risk from directional movements in the market. For example, if an entire industry or sector drops because of unexpected headlines, the short position in Feature Integration will appreciate offsetting losses from the drop in the long position's value.Moving together with Feature Stock
Moving against Feature Stock
| 0.46 | 3443 | Global Unichip Corp | PairCorr |
| 0.46 | 2317 | Hon Hai Precision | PairCorr |
| 0.39 | 0050 | YuantaP shares Taiwan | PairCorr |
| 0.36 | 2330 | Taiwan Semiconductor | PairCorr |
| 0.31 | 0057 | Fubon MSCI Taiwan | PairCorr |
The ability to find closely correlated positions to Feature Integration could be a great tool in your tax-loss harvesting strategies, allowing investors a quick way to find a similar-enough asset to replace Feature Integration when you sell it. If you don't do this, your portfolio allocation will be skewed against your target asset allocation. So, investors can't just sell and buy back Feature Integration - that would be a violation of the tax code under the "wash sale" rule, and this is why you need to find a similar enough asset and use the proceeds from selling Feature Integration Technology to buy it.
The correlation of Feature Integration is a statistical measure of how it moves in relation to other instruments. This measure is expressed in what is known as the correlation coefficient, which ranges between -1 and +1. A perfect positive correlation (i.e., a correlation coefficient of +1) implies that as Feature Integration moves, either up or down, the other security will move in the same direction. Alternatively, perfect negative correlation means that if Feature Integration moves in either direction, the perfectly negatively correlated security will move in the opposite direction. If the correlation is 0, the equities are not correlated; they are entirely random. A correlation greater than 0.8 is generally described as strong, whereas a correlation less than 0.5 is generally considered weak.
Correlation analysis and pair trading evaluation for Feature Integration can also be used as hedging techniques within a particular sector or industry or even over random equities to generate a better risk-adjusted return on your portfolios.Additional Tools for Feature Stock Analysis
When running Feature Integration's price analysis, check to measure Feature Integration'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 Feature Integration is operating at the current time. Most of Feature Integration's value examination focuses on studying past and present price action to predict the probability of Feature Integration's future price movements. You can analyze the entity against its peers and the financial market as a whole to determine factors that move Feature Integration's price. Additionally, you may evaluate how the addition of Feature Integration to your portfolios can decrease your overall portfolio volatility.