Triumph Financial Stock Overlap Studies All Moving Average

TFINP Stock   23.66  0.02  0.08%   
Triumph Financial overlap studies tool provides the execution environment for running the All Moving Average study and other technical functions against Triumph Financial. Triumph 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 overlap studies indicators. As with most other technical indicators, the All Moving Average study function is designed to identify and follow existing trends. Triumph Financial overlay technical analysis usually involve calculating upper and lower limits of price movements based on various statistical techniques. Please specify Time Period and MA Type to execute this module.

The output start index for this execution was nine with a total number of output elements of fifty-two. The Moving Average is predictive technique used to analyze Triumph Financial price data points by creating a series of averages of different subsets of Triumph Financial entire price series.

Triumph Financial Technical Analysis Modules

Most technical analysis of Triumph 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 Triumph from various momentum indicators to cycle indicators. When you analyze Triumph 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 Triumph 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 Triumph Financial. We use our internally-developed statistical techniques to arrive at the intrinsic value of Triumph Financial based on widely used predictive technical indicators. In general, we focus on analyzing Triumph Stock price patterns and their correlations with different microeconomic environment and drivers. We also apply predictive analytics to build Triumph Financial's daily price indicators and compare them against related drivers, such as overlap studies 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 Triumph Financial's intrinsic value. In addition to deriving basic predictive indicators for Triumph Financial, we also check how macroeconomic factors affect Triumph 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 Yield0.0010880.0026890.0017230.002279
Price To Sales Ratio6.952.463.934.38
Hype
Prediction
LowEstimatedHigh
22.5423.6224.70
Details
Intrinsic
Valuation
LowRealHigh
18.2819.3626.03
Details
Naive
Forecast
LowNextHigh
22.4623.5424.62
Details
Bollinger
Band Projection (param)
LowerMiddle BandUpper
22.4623.3224.18
Details

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Additional Tools for Triumph Stock Analysis

When running Triumph Financial's price analysis, check to measure Triumph 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 Triumph Financial is operating at the current time. Most of Triumph Financial's value examination focuses on studying past and present price action to predict the probability of Triumph 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 Triumph Financial's price. Additionally, you may evaluate how the addition of Triumph Financial to your portfolios can decrease your overall portfolio volatility.