Ironnet Stock Forecast - Polynomial Regression

IRNTDelisted Stock  USD 0.13  0.00  0.00%   
The Polynomial Regression forecasted value of Ironnet on the next trading day is expected to be 0.15 with a mean absolute deviation of 0.03 and the sum of the absolute errors of 1.53. Ironnet Stock Forecast is based on your current time horizon.
  
Ironnet polinomial regression implements a single variable polynomial regression model using the daily prices as the independent variable. The coefficients of the regression for Ironnet as well as the accuracy indicators are determined from the period prices.

Ironnet Polynomial Regression Price Forecast For the 31st of December

Given 90 days horizon, the Polynomial Regression forecasted value of Ironnet on the next trading day is expected to be 0.15 with a mean absolute deviation of 0.03, mean absolute percentage error of 0.0008, and the sum of the absolute errors of 1.53.
Please note that although there have been many attempts to predict Ironnet 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 Ironnet's next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).

Ironnet Stock Forecast Pattern

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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 Ironnet stock data series using in forecasting. Note that when a statistical model is used to represent Ironnet 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 Criteria111.028
BiasArithmetic mean of the errors None
MADMean absolute deviation0.0251
MAPEMean absolute percentage error0.122
SAESum of the absolute errors1.5338
A single variable polynomial regression model attempts to put a curve through the Ironnet 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 Ironnet

There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as Ironnet. 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
0.130.130.13
Details
Intrinsic
Valuation
LowRealHigh
0.120.120.14
Details

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 Risk & Return  Correlation

Ironnet Market Strength Events

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

Ironnet Risk Indicators

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

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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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Check out Risk vs Return Analysis to better understand how to build diversified portfolios. Also, note that the market value of any company could be closely tied with the direction of predictive economic indicators such as signals in board of governors.
You can also try the Commodity Channel module to use Commodity Channel Index to analyze current equity momentum.

Other Consideration for investing in Ironnet Stock

If you are still planning to invest in Ironnet check if it may still be traded through OTC markets such as Pink Sheets or OTC Bulletin Board. You may also purchase it directly from the company, but this is not always possible and may require contacting the company directly. Please note that delisted stocks are often considered to be more risky investments, as they are no longer subject to the same regulatory and reporting requirements as listed stocks. Therefore, it is essential to carefully research the Ironnet's history and understand the potential risks before investing.
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