M Yochananof Stock Forecast - Polynomial Regression

YHNF Stock  ILA 22,200  280.00  1.28%   
The Polynomial Regression forecasted value of M Yochananof and on the next trading day is expected to be 23,347 with a mean absolute deviation of 726.59 and the sum of the absolute errors of 44,322. YHNF Stock Forecast is based on your current time horizon. Investors can use this forecasting interface to forecast M Yochananof stock prices and determine the direction of M Yochananof and's future trends based on various well-known forecasting models. We recommend always using this module together with an analysis of M Yochananof's historical fundamentals, such as revenue growth or operating cash flow patterns.
  
M Yochananof polinomial regression implements a single variable polynomial regression model using the daily prices as the independent variable. The coefficients of the regression for M Yochananof and as well as the accuracy indicators are determined from the period prices.

M Yochananof Polynomial Regression Price Forecast For the 12th of December 2024

Given 90 days horizon, the Polynomial Regression forecasted value of M Yochananof and on the next trading day is expected to be 23,347 with a mean absolute deviation of 726.59, mean absolute percentage error of 732,084, and the sum of the absolute errors of 44,322.
Please note that although there have been many attempts to predict YHNF 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 M Yochananof's next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).

M Yochananof Stock Forecast Pattern

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M Yochananof Forecasted Value

In the context of forecasting M Yochananof'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. M Yochananof's downside and upside margins for the forecasting period are 23,345 and 23,348, respectively. We have considered M Yochananof'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
22,200
23,345
Downside
23,347
Expected Value
23,348
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 M Yochananof stock data series using in forecasting. Note that when a statistical model is used to represent M Yochananof 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 Criteria131.6142
BiasArithmetic mean of the errors None
MADMean absolute deviation726.5932
MAPEMean absolute percentage error0.0329
SAESum of the absolute errors44322.1838
A single variable polynomial regression model attempts to put a curve through the M Yochananof 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 M Yochananof

There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as M Yochananof. 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
22,19822,20022,202
Details
Intrinsic
Valuation
LowRealHigh
19,98025,73525,737
Details
Bollinger
Band Projection (param)
LowMiddleHigh
21,74023,25324,765
Details

Other Forecasting Options for M Yochananof

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

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

M Yochananof 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 M Yochananof'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 M Yochananof's current price.

M Yochananof Market Strength Events

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

M Yochananof Risk Indicators

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

Other Information on Investing in YHNF Stock

M Yochananof financial ratios help investors to determine whether YHNF Stock is cheap or expensive when compared to a particular measure, such as profits or enterprise value. In other words, they help investors to determine the cost of investment in YHNF with respect to the benefits of owning M Yochananof security.