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Name

As of 07/25/2024

Price

Aum/Mkt Cap

YIELD

Annualized forward dividend yield. Multiplies the most recent dividend payout amount by its frequency and divides by the previous close price.

Exp Ratio

Expense ratio is the fund’s total annual operating expenses, including management fees, distribution fees, and other expenses, expressed as a percentage of average net assets.

Watchlist

Burney U.S. Factor Rotation ETF

BRNY | Active ETF

$36.92

$220 M

0.79%

$0.29

0.79%

Vitals

YTD Return

14.6%

1 yr return

24.5%

3 Yr Avg Return

N/A

5 Yr Avg Return

N/A

Net Assets

$220 M

Holdings in Top 10

44.2%

52 WEEK LOW AND HIGH

$36.8
$26.94
$38.70

Expenses

OPERATING FEES

Expense Ratio 0.79%

SALES FEES

Front Load N/A

Deferred Load N/A

TRADING FEES

Turnover N/A

Redemption Fee N/A

Min Investment

Standard (Taxable)

N/A

IRA

N/A

Fund Classification

Fund Type

Exchange Traded Fund

Name

As of 07/25/2024

Price

Aum/Mkt Cap

YIELD

Annualized forward dividend yield. Multiplies the most recent dividend payout amount by its frequency and divides by the previous close price.

Exp Ratio

Expense ratio is the fund’s total annual operating expenses, including management fees, distribution fees, and other expenses, expressed as a percentage of average net assets.

Watchlist

Burney U.S. Factor Rotation ETF

BRNY | Active ETF

$36.92

$220 M

0.79%

$0.29

0.79%

BRNY - Profile

Distributions

  • YTD Total Return 14.6%
  • 3 Yr Annualized Total Return N/A
  • 5 Yr Annualized Total Return N/A
  • Capital Gain Distribution Frequency N/A
  • Net Income Ratio N/A
DIVIDENDS
  • Dividend Yield 0.8%
  • Dividend Distribution Frequency Quarterly

Fund Details

  • Legal Name
    Burney U.S. Factor Rotation ETF
  • Fund Family Name
    N/A
  • Inception Date
    Oct 14, 2022
  • Shares Outstanding
    N/A
  • Share Class
    N/A
  • Currency
    USD
  • Domiciled Country
    US

Fund Description

The Burney U.S. Factor Rotation ETF (the “Fund”) is an actively managed exchange-traded fund (“ETF”) that seeks long term growth of capital. The Fund seeks to achieve its investment objective by investing, under normal circumstances, at least 80% of the Fund’s net assets plus the amount of any borrowings for investment purposes in U.S. listed common stock. The Fund will invest its assets in common stocks of large, mid, and small-capitalization companies. Security selection is determined based on a proprietary model developed by The Burney Company, the sub-adviser to the Fund (the “Sub-Adviser”).
The Sub-Adviser has observed that, over the long run, small and value stocks have shown a performance edge over large and growth companies. However, it has also observed that there are periods of time when large-cap stocks outperform small-cap stocks and when growth stocks outperform value stocks. As a result, the Fund will utilize a “factor rotation” style of investing that varies across large, small, value, and growth investment cycles (“Investment Cycles”). Specifically, Investment Cycles are defined as periods where the difference in return between small and large-cap stocks favor either small-cap stocks or large cap stocks and where the difference in return between growth and value stocks favor either growth or value stocks. Historically, the cyclical pattern of
these market phases can be seen over a 36-month rolling period with regards to market cap size and a 12-month rolling period with regards to style (i.e., growth vs. value). As described further below, the Sub-Adviser analyzes market data related to these cycles to determine the allocation of the portfolio in large and small cap stocks and growth and value stocks.
The Sub-Adviser first sets Investment Cycle targets for the strategy based on the Investment Cycle it expects to outperform. Security selection is informed by the Sub-Adviser’s proprietary quantitative stock selection model that rates stocks on key valuation, growth, profitability, quality, and technical factors in addition to an alternative data set, which utilizes artificial intelligence to predict revenue beats by measuring a company’s digital footprint based on engagement on websites, social media, search results, and applications, comparing engagement to analyst expectations (“Alternative Data”). The universe of potential portfolio holdings includes U.S. listed common stock of small, mid, and large-capitalization companies. Stocks are classified as large, mid, or small-cap stocks and growth or value based on S&P’s classifications. In cases where S&P does not classify the market cap size and style of a stock, the Sub-Adviser classifies the stock as large, mid, or small-cap and growth or value in accordance with S&P’s methodology. This methodology uses market cap to determine the size of a company (small, medium or large) and growth factors, such as earnings per share growth and sales per share growth along with value factors like book value to price ratio, earnings to price ratio, and sales to price ratio to label companies as growth or value. The Sub-Adviser’s proprietary model then rates all stocks in its universe numerically. The Sub-Adviser uses a portfolio optimizer to select stocks for the strategy that are highly rated and fit the set size and style targets, in accordance with the steps set forth below.
The Sub-Adviser utilizes a five-step approach to select U.S. listed equity securities for the Fund.
Step 1: To determine the current Investment Cycle and its weight, the Sub-Adviser assesses market indices and trends to determine which factors are currently favored by the market. The Sub-Adviser observes rolling 36-month return differentials between small- and large-cap stocks to determine the current size cycle of the stock market and 12-month rolling return differentials between growth and value stocks to determine the current style cycle. The Sub-Adviser considers the length of time the current size and style market phase has lasted, whether it has peaked in magnitude, the direction of the trend in the rolling return differential data, and valuation dispersions to predict which size and style cycle is most likely to be in favor in the future. For example, a downturn in growth stocks and large cap securities could indicate a favorable environment for small cap securities and value stocks. This analysis creates a target weight of large vs. small capitalization and growth vs. value securities for the overall portfolio. The Fund will always have an allocation to each of the target Investment Cycles: Large, Small, Growth, and Value. While mid-cap securities are not its own Investment Cycle, mid-cap securities can be included within the Small Investment Cycle.
Step 2: The universe of potential securities is then evaluated by the Sub-Adviser utilizing a proprietary screen to exclude American Depositary Receipts, microcap companies (in this case, companies whose market capitalization is generally less than $1 billion), and stocks that have, in the judgment of the Sub-Adviser, poor liquidity as measured against average daily volume.
Step 3: The Sub-Adviser then deploys proprietary analysis whereby the remaining universe of securities are individually evaluated across several criteria (profitability, revenue, trend analysis, etc.). Each security is scored and ranked based on its weighted average score across various metrics, which include traditional accounting and price data metrics, as well as other Alternative Data. Alternative Data seeks to predict revenue beats using proprietary analysis of a company’s current traffic across its digital footprint relative to its historic norms and analyst expectations as an indicator of an upcoming revenue beat. The Sub-Adviser’s model gives the highest scores to those stocks with the highest weighted average rating across the various factors and Alternative Data.
Step 4: All eligible securities are then labeled in accordance with the Investment Cycle that is most relevant to each security. Stocks are classified as large, mid, or small-cap stocks and growth or value based on S&P’s classifications. In cases where S&P does not classify the size and style of a stock, the Sub-Advisor classifies the stock as large, mid, or small-cap and growth or value in accordance with the S&P methodology that uses market cap to determine the size of a company (small, medium or large) and growth factors, such as earnings per share growth and sales per share growth along with value factors like book value to price ratio, earnings to price ratio, and sales to price ratio to label companies as growth or value.
Step 5: Securities are then included in the portfolio using a portfolio optimizer to select stocks that are highly rated by the Sub-Adviser’s proprietary model and fit the set Investment Cycle targets. Thereafter, the Sub-Adviser qualitatively assesses the portfolio and may override certain securities recommended by the portfolio optimizer to the extent that a company has certain negative characteristics (e.g., litigation or other
disadvantageous market factors) where benefits to the portfolio can be realized by selecting different investments within any of the Investment Cycle categories. In addition, the Sub-Adviser may opt to purchase a low-cost market beta ETF (e.g., small cap value ETF) for a portion of the portfolio. Nevertheless, portfolio overrides and ETF purchases are relatively infrequent. If ETFs are selected, they are expected to comprise 5% or less of the overall portfolio at any given time.
Historically, the Sub-Adviser has observed that a typical market cap size cycle lasts three to six years and a typical style cycle lasts 18 to 30 months. The rolling size and style cycle data is updated monthly and the decision to set size and style targets is reevaluated with the same frequency. The usual signal for identifying a cycle shift is identification that the rolling return differential has peaked, and the trend is moving back to the origin. This cycling momentum is analyzed against valuation dispersions to determine when a cycle shift is necessary. Size and style cycles can shift dramatically in a short period of time and there is a risk that the Sub-Adviser could react late to a change in Investment Cycles. It is also possible that an expected Investment Cycle change could fail to materialize as anticipated or otherwise does not occur.
The Fund is rebalanced monthly, and the Sub-Adviser limits portfolio turnover to no more than 37.5% per rebalance. The Fund may also invest in cash and cash equivalents and shares of money market funds. Under normal circumstances, the Fund will hold between 80 and 100 securities.
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BRNY - Performance

Return Ranking - Trailing

Period BRNY Return Category Return Low Category Return High Rank in Category (%)
YTD 14.6% N/A N/A N/A
1 Yr 24.5% N/A N/A N/A
3 Yr N/A* N/A N/A N/A
5 Yr N/A* N/A N/A N/A
10 Yr N/A* N/A N/A N/A

* Annualized

Return Ranking - Calendar

Period BRNY Return Category Return Low Category Return High Rank in Category (%)
2023 21.4% N/A N/A N/A
2022 N/A N/A N/A N/A
2021 N/A N/A N/A N/A
2020 N/A N/A N/A N/A
2019 N/A N/A N/A N/A

Total Return Ranking - Trailing

Period BRNY Return Category Return Low Category Return High Rank in Category (%)
YTD 14.6% N/A N/A N/A
1 Yr 24.5% N/A N/A N/A
3 Yr N/A* N/A N/A N/A
5 Yr N/A* N/A N/A N/A
10 Yr N/A* N/A N/A N/A

* Annualized

Total Return Ranking - Calendar

Period BRNY Return Category Return Low Category Return High Rank in Category (%)
2023 22.4% N/A N/A N/A
2022 N/A N/A N/A N/A
2021 N/A N/A N/A N/A
2020 N/A N/A N/A N/A
2019 N/A N/A N/A N/A

BRNY - Holdings

Concentration Analysis

BRNY Category Low Category High BRNY % Rank
Net Assets 220 M N/A N/A N/A
Number of Holdings 79 N/A N/A N/A
Net Assets in Top 10 97.9 M N/A N/A N/A
Weighting of Top 10 44.22% N/A N/A N/A

Top 10 Holdings

  1. Microsoft Corp 6.73%
  2. Cencora Inc 5.15%
  3. ServiceNow Inc 4.72%
  4. UGI Corp 4.72%
  5. Alphabet Inc 4.34%
  6. Meta Platforms Inc 4.17%
  7. Iron Mountain Inc 3.97%
  8. NVIDIA Corp 3.90%
  9. Toll Brothers Inc 3.73%
  10. Donnelley Financial Solutions Inc 2.79%

Asset Allocation

Weighting Return Low Return High BRNY % Rank
Stocks 		94.25% N/A N/A N/A
Other 		5.43% N/A N/A N/A
Cash 		0.33% N/A N/A N/A
Preferred Stocks 		0.00% N/A N/A N/A
Convertible Bonds 		0.00% N/A N/A N/A
Bonds 		0.00% N/A N/A N/A

Stock Sector Breakdown

Weighting Return Low Return High BRNY % Rank
Utilities 		0.00% N/A N/A N/A
Technology 		0.00% N/A N/A N/A
Real Estate 		0.00% N/A N/A N/A
Industrials 		0.00% N/A N/A N/A
Healthcare 		0.00% N/A N/A N/A
Financial Services 		0.00% N/A N/A N/A
Energy 		0.00% N/A N/A N/A
Communication Services 		0.00% N/A N/A N/A
Consumer Defense 		0.00% N/A N/A N/A
Consumer Cyclical 		0.00% N/A N/A N/A
Basic Materials 		0.00% N/A N/A N/A

Stock Geographic Breakdown

Weighting Return Low Return High BRNY % Rank
US 		94.25% N/A N/A N/A
Non US 		0.00% N/A N/A N/A

BRNY - Expenses

Operational Fees

BRNY Fees (% of AUM) Category Return Low Category Return High Rank in Category (%)
Expense Ratio 0.79% N/A N/A N/A
Management Fee 0.79% N/A N/A N/A
12b-1 Fee N/A N/A N/A N/A
Administrative Fee N/A N/A N/A N/A

Sales Fees

BRNY Fees (% of AUM) Category Return Low Category Return High Rank in Category (%)
Front Load N/A N/A N/A N/A
Deferred Load N/A N/A N/A N/A

Trading Fees

BRNY Fees (% of AUM) Category Return Low Category Return High Rank in Category (%)
Max Redemption Fee N/A N/A N/A N/A

Related Fees

Turnover provides investors a proxy for the trading fees incurred by mutual fund managers who frequently adjust position allocations. Higher turnover means higher trading fees.

BRNY Fees (% of AUM) Category Return Low Category Return High Rank in Category (%)
Turnover N/A N/A N/A N/A

BRNY - Distributions

Dividend Yield Analysis

BRNY Category Low Category High BRNY % Rank
Dividend Yield 0.79% N/A N/A N/A

Dividend Distribution Analysis

BRNY Category Low Category High Category Mod
Dividend Distribution Frequency Quarterly

Net Income Ratio Analysis

BRNY Category Low Category High BRNY % Rank
Net Income Ratio N/A N/A N/A N/A

Capital Gain Distribution Analysis

BRNY Category Low Category High Capital Mode
Capital Gain Distribution Frequency

Distributions History

View More +

BRNY - Fund Manager Analysis

Tenure Analysis

Category Low Category High Category Average Category Mode
N/A N/A N/A N/A

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