As an ETF, The RBB Fund is influenced by holdings mix. One-year return is 24.5%, reflecting strong recent performance. It falls under the Broad Equity and Size and Style category. Volume of about 250.11K shares indicates limited liquidity. Downside deviation of 1.55% indicates contained downside behavior.
Performance
Soft
Weak
Strong
Odds Of Distress
Low
High
Low
Trading activity places RBB Fund at $49.80, translating to 2.01% up in today's trading. Credit and volatility analytics assign RBB Fund a 9% risk of financial distress over the forecast horizon. On a risk-adjusted basis, RBB Fund has produced modest risk-adjusted performance over the last 90 trading days, consistent with soft return metrics. The performance scores apply to the period beginning December 24, 2025 and ending March 24, 2026. Learn more.
Matthew McLennan, Kimball Brooker, Jr., Julien Albertini, Adrian Jones
Transfer Agent
U.S. Bancorp Fund Services, LLC
Fiscal Year End
31-Aug
Exchange
NYSE Arca, Inc.
Number of Constituents
79.0
Market Maker
GTS
Total Expense
0.79
Management Fee
0.79
200 Day M A
46.9231
Country Name
USA
50 Day M A
52.2892
Code
FEOE
Updated At
23rd of March 2026
Returns Y T D
0.95
Name
The RBB Fund Trust
Currency Name
US Dollar
Currency Code
USD
Open Figi
BBG01R35FFF8
Type
ETF
1y Volatility
8.3
Currency Exposure
The RBB Fund can carry currency exposure whenever underlying holdings or revenue streams are tied to markets outside the investor's home currency. Used correctly, currency exposure data provides context for deciding whether portfolio risk is coming from holdings selection, foreign-exchange translation, or a combination of both.
Common Risk Profiles
The Capital Asset Pricing Model provides the standard benchmark for evaluating RBB Fund return potential. The risk-reward tradeoff central to CAPM is quantified through alpha and beta measures. CAPM helps analysts calculate the return investors require for the risk associated with RBB Fund. These CAPM metrics provide a structured basis for evaluating RBB Fund as an ETF portfolio component.
This analysis covers sixty-one data points across the selected time horizon. RBB Fund Inverse Tangent Over Price Movement function is an inverse trigonometric method to describe RBB Fund price patterns.
RBB Fund is is formed as Regulated Investment Company in the United States. ETF is managed and operated by U.S. Bancorp Fund Services, LLC. The fund has 79 constituents across multiple sectors and instustries. The fund charges 0.79 percent management fee with a total expences of 0.79 percent of total asset. The RBB Fund posted an ETF Asset Type of Equity for the reported period.
Thematic Classifications
Looking at The RBB Fund through a thematic lens provides context for understanding which broader trends, sectors, or policy shifts may be supporting the position. This creates a better bridge between security selection, portfolio construction, and risk-adjusted return targeting.
Short-horizon indicators in The RBB Fund turn fast-changing price action into clearer risk and execution cues. Used carefully, they can improve execution without tempting investors to overtrade every small swing.
Quantitative tools for The RBB Fund focus on observed patterns, which helps when markets move faster than research can update. Financial data rarely stays stable for long, so the model is best used as a probability tool, not a price promise.
ETF evaluation emphasizes index methodology, tracking difference, and fee drag. The one-year return is 24.5%.
Methodology
Unless otherwise specified, data for The RBB Fund 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. The RBB Fund market data and reported NAV may reflect delayed updates. Data may be delayed depending on reporting sources and market conventions. For The RBB Fund, market price can deviate from reported NAV; premium/discount behavior may widen during volatility or when underlying holdings become less liquid. Assumptions: Datasets used in this report incorporate public fund disclosures, holdings reports, and market data feeds and official institutional disclosures, including U.S. Securities and Exchange Commission (SEC) via EDGAR. Information may be standardized across formats and may reflect delayed updates. 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
The RBB Fund may have reference inputs that incorporate holdings disclosures, category classification, and NAV-derived statistics where available. Updates may occur throughout the day.
Reviewing RBB Fund typically starts with core financial statements and performance trends. Outlined below are key reports that provide context for The RBB Fund:
Investing Opportunities provides context for diversified portfolio design. Portfolio balance depends on how holdings are weighted relative to each other. Portfolio analysis tools can evaluate how The RBB Fund fits within a broader allocation. The allocation framework in use shapes how individual positions are weighted. Broader economic conditions can influence The RBB Fund's etf valuation — related indicators include signals in metropolitan statistical area.
Investors get more value from RBB Fund analysis when it is combined with other construction and diversification tools. RBB Fund analysis across multiple dimensions - risk, valuation, diversification - produces a more informed position-sizing decision. You can also try the Risk-Return Analysis module to view associations between returns expected from investment and the risk you assume.
Market capitalization and book value offer complementary views of RBB Fund - the first driven by investor sentiment, the second by accounting standards.
For RBB Fund, intrinsic value is a model-driven estimate while price is a market-driven observation. All metrics are derived from available inputs and shown for reference.