This statistic functions tool runs Linear Regression function and companion studies for UTILITIES FUND. The focus on statistical functions describing dispersion and variability helps organize trend, volatility, and risk context for UTILITIES FUND.Enter Time Period to generate the indicator output.
This analysis covers thirty-eight data points across the selected time horizon. The Linear Regression model generates relationship between price series of Utilities Fund Class and its peer or benchmark and helps predict UTILITIES FUND future price from its past values.
UTILITIES FUND Technical Analysis Modules
Most technical analysis of UTILITIES FUND 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 UTILITIES from various momentum indicators to cycle indicators. When you analyze UTILITIES 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.
Exposure drift is monitored through changes in holdings and factor weights. The current allocation is approximately 99.0% equities and 1.0% cash. It is classified under Utilities within the Rydex Funds family. The five-year return stands at 10.0%.
Methodology
Unless otherwise specified, data for Utilities Fund Class 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. Utilities Fund Class market data and reported NAV may reflect delayed updates. Data may be delayed depending on reporting sources and market conventions. Assumptions: Inputs are aggregated from public fund disclosures, holdings reports, and market data feeds and public institutions such as U.S. Securities and Exchange Commission (SEC) via EDGAR. Certain values may not reflect real-time changes. 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
Utilities Fund Class may have reference inputs that incorporate holdings disclosures, category classification, and NAV-derived statistics where available. Updates may occur throughout the day.
Portfolio analytics tied to Utilities Fund Class help investors review performance in context instead of judging the holding in isolation. Used properly, the workflow gives investors clearer signals on when to hold, resize, hedge, or replace the position.
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Pair trading with UTILITIES FUND can help investors hedge some company-specific exposure by balancing a long view with an offsetting position. The advantage is that adverse movement in one leg may be partly offset by the other when correlation and thesis alignment hold.
UTILITIES FUND Pair Trading
Utilities Fund Class Pair Trading Analysis
Portfolio managers use rolling correlation data for Utilities Fund Class to assess whether candidate substitutes for UTILITIES FUND are stable or episodically correlated. Stable, long-run correlations provide more reliable wash-sale substitutes.
High-frequency correlation analysis for UTILITIES FUND uses intraday price data to capture short-term co-movements that may differ from daily or monthly correlation estimates. This is particularly relevant for short-term Utilities Fund Class trading strategies.
Use Correlation analysis and pair trading evaluation for UTILITIES FUND to review hedging context. This approach is commonly reviewed within sectors and across broader groups.