Federated Total Return Fund Statistic Functions Linear Regression Slope

FTGSX Fund

USD 9.43 -0.03 -0.32%

This statistic functions tool runs Linear Regression Slope function and companion studies for Federated Total. The analysis highlights statistical functions describing dispersion and variability and frames technical signals with volatility and risk context.Please specify Time Period to run the technical study.

Symbol

This analysis covers thirty-eight data points across the selected time horizon. The Linear Regression Slope is the rate of change in Federated Total Return price series over its benchmark or peer price series.

Federated Total Technical Analysis Modules

Most technical analysis of Federated Total 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 Federated from various momentum indicators to cycle indicators. When you analyze Federated 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.

	Cycle Indicators
	Math Operators
	Math Transform
	Momentum Indicators
	Overlap Studies
	Pattern Recognition
	Price Transform
	Statistic Functions
	Volatility Indicators
	Volume Indicators

Mutual Fund Overview, Methodology & Data Sources

Liquidity and pricing cadence can influence observed volatility and execution context. Lower trading activity may introduce occasional variability in execution conditions. The five-year return stands at 0.0%.

Methodology

Unless otherwise specified, data for Federated Total Return is derived from fund disclosures (prospectus language, holdings reports, and periodic statements where available). Asset-level metrics are computed daily by Macroaxis LLC and refreshed regularly based on instrument type. Federated Total Return market data and reported NAV may reflect delayed updates. Data may be delayed depending on reporting sources and market conventions. Assumptions: We use public fund disclosures, holdings reports, and market data feeds with disclosures published by U.S. Securities and Exchange Commission (SEC) via EDGAR as reference inputs. Data may be normalized and can be delayed. All analytics are generated using standardized, rules-based models designed to promote consistency and comparability across instruments. Model assumptions, reference parameters, and selected computational inputs are available in the Model Inputs section. If you have questions about our data sources or methodology, please contact Macroaxis Support.

Research Sources

Federated Total Return may have reference inputs that incorporate holdings disclosures, category classification, and NAV-derived statistics where available. Updates may occur throughout the day.

This content is curated and reviewed by:

Rifka Kats - Member of Macroaxis Editorial Board

Last reviewed on February 28th, 2026

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A reliable portfolio-monitoring process is important because investors need to see whether Federated Total Return is improving total return without quietly increasing concentration or risk. A disciplined tracking process turns performance data into better decisions instead of more noise.

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Sectors

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