Reward Wool Stock Forecast - Polynomial Regression

1423 Stock  TWD 37.65  0.75  2.03%   
The Polynomial Regression forecasted value of Reward Wool Industry on the next trading day is expected to be 38.06 with a mean absolute deviation of 0.60 and the sum of the absolute errors of 36.53. Reward Stock Forecast is based on your current time horizon.
  
Reward Wool polinomial regression implements a single variable polynomial regression model using the daily prices as the independent variable. The coefficients of the regression for Reward Wool Industry as well as the accuracy indicators are determined from the period prices.

Reward Wool Polynomial Regression Price Forecast For the 25th of November

Given 90 days horizon, the Polynomial Regression forecasted value of Reward Wool Industry on the next trading day is expected to be 38.06 with a mean absolute deviation of 0.60, mean absolute percentage error of 0.59, and the sum of the absolute errors of 36.53.
Please note that although there have been many attempts to predict Reward 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 Reward Wool's next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).

Reward Wool Stock Forecast Pattern

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Reward Wool Forecasted Value

In the context of forecasting Reward Wool'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. Reward Wool's downside and upside margins for the forecasting period are 37.06 and 39.05, respectively. We have considered Reward Wool'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
37.65
38.06
Expected Value
39.05
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 Reward Wool stock data series using in forecasting. Note that when a statistical model is used to represent Reward Wool 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 Criteria117.5756
BiasArithmetic mean of the errors None
MADMean absolute deviation0.5989
MAPEMean absolute percentage error0.0142
SAESum of the absolute errors36.5324
A single variable polynomial regression model attempts to put a curve through the Reward Wool 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 Reward Wool

There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as Reward Wool Industry. 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
36.6637.6538.64
Details
Intrinsic
Valuation
LowRealHigh
33.8945.6746.67
Details
Bollinger
Band Projection (param)
LowMiddleHigh
36.6937.4038.11
Details

Other Forecasting Options for Reward Wool

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

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

Reward Wool Industry 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 Reward Wool'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 Reward Wool's current price.

Reward Wool Market Strength Events

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

Reward Wool Risk Indicators

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

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