Kearny Financial Corp Stock Cycle Indicators Hilbert Transform Dominant Cycle Period

KRNY Stock  USD 8.48  0.37  4.56%   
Kearny Financial cycle indicators tool provides the execution environment for running the Hilbert Transform Dominant Cycle Period indicator and other technical functions against Kearny Financial. Kearny Financial value trend is the prevailing direction of the price over some defined period of time. The concept of trend is an important idea in technical analysis, including the analysis of cycle indicators indicators. As with most other technical indicators, the Hilbert Transform Dominant Cycle Period indicator function is designed to identify and follow existing trends. Cycle Indicators are used by chartists in order to analyze variations of the instantaneous phase or amplitude of Kearny Financial price series.

Indicator
The output start index for this execution was thirty-two with a total number of output elements of twenty-nine. The Hilbert Transform - Dominant Cycle Period indicator is used to generate in-phase and quadrature components of Kearny Financial Corp price series in order to analyze variations of the instantaneous cycles.

Kearny Financial Technical Analysis Modules

Most technical analysis of Kearny Financial help investors determine whether a current trend will continue and, if not, when it will shift. We provide a combination of tools to recognize potential entry and exit points for Kearny from various momentum indicators to cycle indicators. When you analyze Kearny charts, please remember that the event formation may indicate an entry point for a short seller, and look at other indicators across different periods to confirm that a breakdown or reversion is likely to occur.

About Kearny Financial Predictive Technical Analysis

Predictive technical analysis modules help investors to analyze different prices and returns patterns as well as diagnose historical swings to determine the real value of Kearny Financial Corp. We use our internally-developed statistical techniques to arrive at the intrinsic value of Kearny Financial Corp based on widely used predictive technical indicators. In general, we focus on analyzing Kearny Stock price patterns and their correlations with different microeconomic environment and drivers. We also apply predictive analytics to build Kearny Financial's daily price indicators and compare them against related drivers, such as cycle indicators and various other types of predictive indicators. Using this methodology combined with a more conventional technical analysis and fundamental analysis, we attempt to find the most accurate representation of Kearny Financial's intrinsic value. In addition to deriving basic predictive indicators for Kearny Financial, we also check how macroeconomic factors affect Kearny Financial price patterns. Please read more on our technical analysis page or use our predictive modules below to complement your research.
 2021 2022 2023 2024 (projected)
Dividend Yield0.0390.06240.07360.0772
Price To Sales Ratio3.742.561.151.09
Hype
Prediction
LowEstimatedHigh
5.178.3711.57
Details
Intrinsic
Valuation
LowRealHigh
4.377.5710.77
Details
Naive
Forecast
LowNextHigh
5.628.8312.03
Details
2 Analysts
Consensus
LowTargetHigh
6.607.258.05
Details

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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.