Siit Ultra Short Fund Math Operators Price Series Summation

SUSAX Fund  USD 9.97  -0.01  -0.10%   
The math operators module provides an execution environment for Price Series Summation operator and related indicators on SIIT ULTRA and Sterling Capital Short. It emphasizes relative price relationships between SIIT ULTRA and Sterling Capital Short while keeping volatility, risk, and performance context in view.

Operator
The output start index for this execution was zero with a total number of output elements of sixty-one. Siit Ultra Short Price Series Summation is a cross summation of SIIT ULTRA price series and its benchmark/peer.

SIIT ULTRA Technical Analysis Modules

Most technical analysis of SIIT ULTRA 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 SIIT from various momentum indicators to cycle indicators. When you analyze SIIT 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.

Mutual Fund Overview, Methodology & Data Sources

The fund overview for SIIT ULTRA summarizes mandate, holdings profile, and risk characteristics. The fund has exposure to SEI Funds, Large Funds, Ultrashort Bond Funds. The current allocation is approximately 93.0% bonds and 3.0% cash. It is classified under Ultrashort Bond within the SEI family.

Methodology

Unless otherwise specified, data for Siit Ultra Short 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. Siit Ultra Short market data and reported NAV may reflect delayed updates. Data may be delayed depending on reporting sources and market conventions. Assumptions: We primarily rely on public fund disclosures, holdings reports, and market data feeds, including disclosures published by U.S. Securities and Exchange Commission (SEC) via EDGAR. Data is normalized for analytical consistency across reporting formats. 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

Siit Ultra Short 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:

Ellen Johnson - Member of Macroaxis Editorial Board

Learn to be your own money manager

Tracking SIIT ULTRA inside a portfolio is useful because individual winners can still weaken diversification or distort overall risk targets. A disciplined tracking process turns performance data into better decisions instead of more noise.

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Siit Ultra Short pair trading

Pair trading with SIIT ULTRA can help investors hedge some company-specific exposure by balancing a long view with an offsetting position. The key question is whether the second leg adds real hedge value instead of just creating a more complex version of the same risk.

SIIT ULTRA Pair Trading

Siit Ultra Short Pair Trading Analysis

The ability to find closely correlated positions to SIIT ULTRA could be a great tool in your tax-loss harvesting strategies, allowing investors a quick way to find a similar-enough asset to replace SIIT ULTRA when you sell it.
The correlation of SIIT ULTRA is a statistical measure of how it moves in relation to other instruments. This measure is expressed in what is known as the correlation coefficient, which ranges between -1 and +1.
Correlation analysis and pair trading evaluation for SIIT ULTRA can be used to frame hedging context. The approach can be applied within sectors or across broader universes.
Pair CorrelationCorrelation Matching