Kearny Financial Stock Forecast - Polynomial Regression

KRNY Stock  USD 8.21  0.06  0.73%   
The Polynomial Regression forecasted value of Kearny Financial Corp on the next trading day is expected to be 8.68 with a mean absolute deviation of 0.26 and the sum of the absolute errors of 15.69. Kearny Stock Forecast is based on your current time horizon.
  
At this time, Kearny Financial's Receivables Turnover is fairly stable compared to the past year. Asset Turnover is likely to rise to 0.03 in 2024, whereas Fixed Asset Turnover is likely to drop 1.87 in 2024. . Common Stock Shares Outstanding is likely to rise to about 88.8 M in 2024. Net Income Applicable To Common Shares is likely to rise to about 49.3 M in 2024.
Kearny Financial polinomial regression implements a single variable polynomial regression model using the daily prices as the independent variable. The coefficients of the regression for Kearny Financial Corp as well as the accuracy indicators are determined from the period prices.

Kearny Financial Polynomial Regression Price Forecast For the 27th of November

Given 90 days horizon, the Polynomial Regression forecasted value of Kearny Financial Corp on the next trading day is expected to be 8.68 with a mean absolute deviation of 0.26, mean absolute percentage error of 0.1, and the sum of the absolute errors of 15.69.
Please note that although there have been many attempts to predict Kearny 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 Kearny Financial's next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).

Kearny Financial Stock Forecast Pattern

Backtest Kearny FinancialKearny Financial Price PredictionBuy or Sell Advice 

Kearny Financial Forecasted Value

In the context of forecasting Kearny Financial'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. Kearny Financial's downside and upside margins for the forecasting period are 5.59 and 11.76, respectively. We have considered Kearny Financial'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
8.21
8.68
Expected Value
11.76
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 Kearny Financial stock data series using in forecasting. Note that when a statistical model is used to represent Kearny Financial 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 Criteria115.794
BiasArithmetic mean of the errors None
MADMean absolute deviation0.2573
MAPEMean absolute percentage error0.0358
SAESum of the absolute errors15.6937
A single variable polynomial regression model attempts to put a curve through the Kearny Financial 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 Kearny Financial

There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as Kearny Financial Corp. 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
5.058.1311.21
Details
Intrinsic
Valuation
LowRealHigh
4.437.5110.59
Details
2 Analysts
Consensus
LowTargetHigh
6.607.258.05
Details

Other Forecasting Options for Kearny Financial

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

View Kearny Financial Related Equities

 Risk & Return  Correlation

Kearny Financial Corp 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 Kearny Financial'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 Kearny Financial's current price.

Kearny Financial Market Strength Events

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

Kearny Financial Risk Indicators

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

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