Farglory FTZ Stock Forecast - Polynomial Regression

5607 Stock  TWD 45.35  0.40  0.87%   
The Polynomial Regression forecasted value of Farglory FTZ Investment on the next trading day is expected to be 47.41 with a mean absolute deviation of 0.51 and the sum of the absolute errors of 31.76. Farglory Stock Forecast is based on your current time horizon.
  
Farglory FTZ polinomial regression implements a single variable polynomial regression model using the daily prices as the independent variable. The coefficients of the regression for Farglory FTZ Investment as well as the accuracy indicators are determined from the period prices.

Farglory FTZ Polynomial Regression Price Forecast For the 14th of December 2024

Given 90 days horizon, the Polynomial Regression forecasted value of Farglory FTZ Investment on the next trading day is expected to be 47.41 with a mean absolute deviation of 0.51, mean absolute percentage error of 0.42, and the sum of the absolute errors of 31.76.
Please note that although there have been many attempts to predict Farglory 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 Farglory FTZ's next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).

Farglory FTZ Stock Forecast Pattern

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Farglory FTZ Forecasted Value

In the context of forecasting Farglory FTZ'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. Farglory FTZ's downside and upside margins for the forecasting period are 46.26 and 48.55, respectively. We have considered Farglory FTZ'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.
Market Value
45.35
47.41
Expected Value
48.55
Upside

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 Farglory FTZ stock data series using in forecasting. Note that when a statistical model is used to represent Farglory FTZ 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.
AICAkaike Information Criteria119.0715
BiasArithmetic mean of the errors None
MADMean absolute deviation0.5122
MAPEMean absolute percentage error0.0113
SAESum of the absolute errors31.7574
A single variable polynomial regression model attempts to put a curve through the Farglory FTZ historical price points. Mathematically, assuming the independent variable is X and the dependent variable is Y, this line can be indicated as: Y = a0 + a1*X + a2*X2 + a3*X3 + ... + am*Xm

Predictive Modules for Farglory FTZ

There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as Farglory FTZ Investment. 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.
Hype
Prediction
LowEstimatedHigh
44.1945.3546.51
Details
Intrinsic
Valuation
LowRealHigh
44.0545.2146.37
Details

Other Forecasting Options for Farglory FTZ

For every potential investor in Farglory, whether a beginner or expert, Farglory FTZ's price movement is the inherent factor that sparks whether it is viable to invest in it or hold it better. Farglory Stock price charts are filled with many 'noises.' These noises can hugely alter the decision one can make regarding investing in Farglory. Basic forecasting techniques help filter out the noise by identifying Farglory FTZ's price trends.

Farglory FTZ 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 Farglory FTZ stock to make a market-neutral strategy. Peer analysis of Farglory FTZ could also be used in its relative valuation, which is a method of valuing Farglory FTZ by comparing valuation metrics with similar companies.
 Risk & Return  Correlation

Farglory FTZ Investment 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 Farglory FTZ'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 Farglory FTZ's current price.

Farglory FTZ Market Strength Events

Market strength indicators help investors to evaluate how Farglory FTZ stock reacts to ongoing and evolving market conditions. The investors can use it to make informed decisions about market timing, and determine when trading Farglory FTZ shares will generate the highest return on investment. By undertsting and applying Farglory FTZ stock market strength indicators, traders can identify Farglory FTZ Investment entry and exit signals to maximize returns.

Farglory FTZ Risk Indicators

The analysis of Farglory FTZ'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 Farglory FTZ's investment and either accepting that risk or mitigating it. Along with some essential techniques for forecasting farglory 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.
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.

Also Currently Popular

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.

Additional Tools for Farglory Stock Analysis

When running Farglory FTZ's price analysis, check to measure Farglory FTZ'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 Farglory FTZ is operating at the current time. Most of Farglory FTZ's value examination focuses on studying past and present price action to predict the probability of Farglory FTZ's future price movements. You can analyze the entity against its peers and the financial market as a whole to determine factors that move Farglory FTZ's price. Additionally, you may evaluate how the addition of Farglory FTZ to your portfolios can decrease your overall portfolio volatility.