Giant Manufacturing Stock Forecast - Double Exponential Smoothing
| 9921 Stock | TWD 219.00 1.00 0.45% |
The Double Exponential Smoothing forecasted value of Giant Manufacturing Co on the next trading day is expected to be 219.01 with a mean absolute deviation of 4.61 and the sum of the absolute errors of 272.19. Giant Stock Forecast is based on your current time horizon. Investors can use this forecasting interface to forecast Giant Manufacturing stock prices and determine the direction of Giant Manufacturing Co's future trends based on various well-known forecasting models. We recommend always using this module together with an analysis of Giant Manufacturing's historical fundamentals, such as revenue growth or operating cash flow patterns.
Check out Historical Fundamental Analysis of Giant Manufacturing to cross-verify your projections. Giant |
Most investors in Giant Manufacturing 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 Giant Manufacturing's time series price data and predict how it will affect future prices. One of these methodologies is forecasting, which interprets Giant Manufacturing's price structures and extracts relationships that further increase the generated results' accuracy.
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 Giant Manufacturing works best with periods where there are trends or seasonality. Giant Manufacturing Double Exponential Smoothing Price Forecast For the 27th of May
Given 90 days horizon, the Double Exponential Smoothing forecasted value of Giant Manufacturing Co on the next trading day is expected to be 219.01 with a mean absolute deviation of 4.61, mean absolute percentage error of 32.24, and the sum of the absolute errors of 272.19.Please note that although there have been many attempts to predict Giant 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 Giant Manufacturing's next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).
Giant Manufacturing Stock Forecast Pattern
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Giant Manufacturing Forecasted Value
In the context of forecasting Giant Manufacturing'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. Giant Manufacturing's downside and upside margins for the forecasting period are 216.56 and 221.46, respectively. We have considered Giant Manufacturing'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 Giant Manufacturing stock data series using in forecasting. Note that when a statistical model is used to represent Giant Manufacturing 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 | 0.9802 |
| MAD | Mean absolute deviation | 4.6134 |
| MAPE | Mean absolute percentage error | 0.0212 |
| SAE | Sum of the absolute errors | 272.1877 |
Predictive Modules for Giant Manufacturing
There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as Giant Manufacturing. 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.Sophisticated investors, who have witnessed many market ups and downs, anticipate that the market will even out over time. This tendency of Giant Manufacturing'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 Giant Manufacturing
For every potential investor in Giant, whether a beginner or expert, Giant Manufacturing's price movement is the inherent factor that sparks whether it is viable to invest in it or hold it better. Giant Stock price charts are filled with many 'noises.' These noises can hugely alter the decision one can make regarding investing in Giant. Basic forecasting techniques help filter out the noise by identifying Giant Manufacturing's price trends.Giant Manufacturing 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 Giant Manufacturing stock to make a market-neutral strategy. Peer analysis of Giant Manufacturing could also be used in its relative valuation, which is a method of valuing Giant Manufacturing by comparing valuation metrics with similar companies.
| Risk & Return | Correlation |
Giant Manufacturing 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 Giant Manufacturing'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 Giant Manufacturing's current price.| Cycle Indicators | ||
| Math Operators | ||
| Math Transform | ||
| Momentum Indicators | ||
| Overlap Studies | ||
| Pattern Recognition | ||
| Price Transform | ||
| Statistic Functions | ||
| Volatility Indicators | ||
| Volume Indicators |
Giant Manufacturing Market Strength Events
Market strength indicators help investors to evaluate how Giant Manufacturing stock reacts to ongoing and evolving market conditions. The investors can use it to make informed decisions about market timing, and determine when trading Giant Manufacturing shares will generate the highest return on investment. By undertsting and applying Giant Manufacturing stock market strength indicators, traders can identify Giant Manufacturing Co entry and exit signals to maximize returns.
Giant Manufacturing Risk Indicators
The analysis of Giant Manufacturing'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 Giant Manufacturing's investment and either accepting that risk or mitigating it. Along with some essential techniques for forecasting giant 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 | 1.87 | |||
| Semi Deviation | 1.85 | |||
| Standard Deviation | 2.4 | |||
| Variance | 5.76 | |||
| Downside Variance | 3.79 | |||
| Semi Variance | 3.43 | |||
| Expected Short fall | (2.37) |
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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Analyzing currently trending equities could be an opportunity to develop a better portfolio based on different market momentums that they can trigger. Utilizing the top trending stocks is also useful when creating a market-neutral strategy or pair trading technique involving a short or a long position in a currently trending equity.| MSFT | Microsoft | |
| GM | General Motors | |
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Check out Historical Fundamental Analysis of Giant Manufacturing to cross-verify your projections. You can also try the Equity Forecasting module to use basic forecasting models to generate price predictions and determine price momentum.
Complementary Tools for Giant Stock analysis
When running Giant Manufacturing's price analysis, check to measure Giant Manufacturing'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 Giant Manufacturing is operating at the current time. Most of Giant Manufacturing's value examination focuses on studying past and present price action to predict the probability of Giant Manufacturing's future price movements. You can analyze the entity against its peers and the financial market as a whole to determine factors that move Giant Manufacturing's price. Additionally, you may evaluate how the addition of Giant Manufacturing to your portfolios can decrease your overall portfolio volatility.
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