InTest Stock Forecast - Polynomial Regression

INTT Stock  USD 7.58  0.36  4.53%   
The Polynomial Regression forecasted value of inTest on the next trading day is expected to be 7.62 with a mean absolute deviation of 0.19 and the sum of the absolute errors of 11.79. InTest Stock Forecast is based on your current time horizon.
  
At this time, InTest's Inventory Turnover is comparatively stable compared to the past year. Receivables Turnover is likely to gain to 7.72 in 2024, whereas Payables Turnover is likely to drop 11.18 in 2024. . Net Income Applicable To Common Shares is likely to gain to about 8 M in 2024, whereas Common Stock Shares Outstanding is likely to drop slightly above 10.2 M in 2024.
InTest polinomial regression implements a single variable polynomial regression model using the daily prices as the independent variable. The coefficients of the regression for inTest as well as the accuracy indicators are determined from the period prices.

InTest Polynomial Regression Price Forecast For the 3rd of December

Given 90 days horizon, the Polynomial Regression forecasted value of inTest on the next trading day is expected to be 7.62 with a mean absolute deviation of 0.19, mean absolute percentage error of 0.07, and the sum of the absolute errors of 11.79.
Please note that although there have been many attempts to predict InTest 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 InTest's next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).

InTest Stock Forecast Pattern

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InTest Forecasted Value

In the context of forecasting InTest'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. InTest's downside and upside margins for the forecasting period are 4.21 and 11.03, respectively. We have considered InTest'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
7.58
7.62
Expected Value
11.03
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 InTest stock data series using in forecasting. Note that when a statistical model is used to represent InTest 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 Criteria115.3881
BiasArithmetic mean of the errors None
MADMean absolute deviation0.1934
MAPEMean absolute percentage error0.0265
SAESum of the absolute errors11.7946
A single variable polynomial regression model attempts to put a curve through the InTest 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 InTest

There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as inTest. 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 InTest'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.
Hype
Prediction
LowEstimatedHigh
4.137.5410.95
Details
Intrinsic
Valuation
LowRealHigh
6.8212.1115.52
Details
2 Analysts
Consensus
LowTargetHigh
24.5727.0029.97
Details

Other Forecasting Options for InTest

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

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 Risk & Return  Correlation

inTest 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 InTest'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 InTest's current price.

InTest Market Strength Events

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

InTest Risk Indicators

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

Thematic Opportunities

Explore Investment Opportunities

Build portfolios using Macroaxis predefined set of investing ideas. Many of Macroaxis investing ideas can easily outperform a given market. Ideas can also be optimized per your risk profile before portfolio origination is invoked. Macroaxis thematic optimization helps investors identify companies most likely to benefit from changes or shifts in various micro-economic or local macro-level trends. Originating optimal thematic portfolios involves aligning investors' personal views, ideas, and beliefs with their actual investments.
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Additional Tools for InTest Stock Analysis

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