San Fu Stock Forecast - Simple Regression

4755 Stock  TWD 132.00  2.00  1.49%   
The Simple Regression forecasted value of San Fu Chemical on the next trading day is expected to be 124.85 with a mean absolute deviation of 4.94 and the sum of the absolute errors of 301.38. San Stock Forecast is based on your current time horizon.
  
Simple Regression model is a single variable regression model that attempts to put a straight line through San Fu price points. This line is defined by its gradient or slope, and the point at which it intercepts the x-axis. Mathematically, assuming the independent variable is X and the dependent variable is Y, then this line can be represented as: Y = intercept + slope * X.

San Fu Simple Regression Price Forecast For the 29th of November

Given 90 days horizon, the Simple Regression forecasted value of San Fu Chemical on the next trading day is expected to be 124.85 with a mean absolute deviation of 4.94, mean absolute percentage error of 34.00, and the sum of the absolute errors of 301.38.
Please note that although there have been many attempts to predict San 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 San Fu's next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).

San Fu Stock Forecast Pattern

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San Fu Forecasted Value

In the context of forecasting San Fu'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. San Fu's downside and upside margins for the forecasting period are 122.49 and 127.21, respectively. We have considered San Fu'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
132.00
122.49
Downside
124.85
Expected Value
127.21
Upside

Model Predictive Factors

The below table displays some essential indicators generated by the model showing the Simple Regression forecasting method's relative quality and the estimations of the prediction error of San Fu stock data series using in forecasting. Note that when a statistical model is used to represent San Fu 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 Criteria121.6368
BiasArithmetic mean of the errors None
MADMean absolute deviation4.9407
MAPEMean absolute percentage error0.038
SAESum of the absolute errors301.3836
In general, regression methods applied to historical equity returns or prices series is an area of active research. In recent decades, new methods have been developed for robust regression of price series such as San Fu Chemical historical returns. These new methods are regression involving correlated responses such as growth curves and different regression methods accommodating various types of missing data.

Predictive Modules for San Fu

There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as San Fu Chemical. 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
129.64132.00134.36
Details
Intrinsic
Valuation
LowRealHigh
108.10110.46145.20
Details

Other Forecasting Options for San Fu

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

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

San Fu Chemical 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 San Fu'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 San Fu's current price.

San Fu Market Strength Events

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

San Fu Risk Indicators

The analysis of San Fu'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 San Fu's investment and either accepting that risk or mitigating it. Along with some essential techniques for forecasting san 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 San Stock Analysis

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