Dividend Investing Ideas Center
Critical Facts You Need to Know About Preferred Stocks
Have you ever wished for the safety of bonds, but the return potential...
Name
As of 04/24/2024Price
Aum/Mkt Cap
YIELD
Exp Ratio
Watchlist
YTD Return
5.4%
1 yr return
N/A
3 Yr Avg Return
N/A
5 Yr Avg Return
N/A
Net Assets
$17.7 M
Holdings in Top 10
99.8%
Expense Ratio 1.68%
Front Load N/A
Deferred Load N/A
Turnover N/A
Redemption Fee N/A
Standard (Taxable)
N/A
IRA
N/A
Fund Type
Exchange Traded Fund
Name
As of 04/24/2024Price
Aum/Mkt Cap
YIELD
Exp Ratio
Watchlist
Montrose Estate Capital Management, LLC, doing business as Days Global Advisors, is the Fund’s sub-adviser (the “Sub-Adviser”). The Fund is a “fund-of ETFs,” and the Sub-Adviser invests all of the Fund’s assets in unaffiliated ETFs that are listed on U.S. stock exchanges (“Underlying ETFs”). The Underlying ETFs may include ETFs that invest in U.S. and foreign equity securities, fixed income securities, currencies, and commodities. In addition, Underlying ETFs may include inverse ETFs (i.e., ETFs that produce investment results that are opposite of a particular benchmark index), or leveraged ETFs (i.e., ETFs that produce investment results that exceed a particular benchmark index by a factor greater than one).
The Fund’s exposure to commodities will likely come by investing in ETFs which own commodities. Commodity ETFs are publicly traded partnerships, not regulated investment companies. Because of the 25% limit on ownership of publicly traded partnerships, the Fund will have to monitor its holdings in commodity ETFs so that such holdings will not constitute 25% of its assets at the close of any quarter.
Underlying ETFs that invest in currencies may seek to benefit from changes in exchange rates, such as between the U.S. dollar and the euro. In contrast, other Underlying ETFs may seek to benefit when the value of one or more currency(ies) increase, and others Underlying ETFs may seek to benefit when the value of one or more currenc(ies) decrease. Further, Underlying ETFs may engage in currency transactions to hedge (protect) the value of their foreign currency holdings.
Underlying ETFs, particularly inverse ETFs, may invest in index swaps, which are agreements to make or receive payments based on the different returns that would be achieved if a notional amount were invested in a specified basket of securities (such as the S&P 500 Index) or in some other investment (such as U.S. Treasury Securities). Underlying ETFs may enter into swap transactions for a wide range of reasons, such as: attempting to obtain or preserve a particular return or spread at a lower cost than obtaining a return or spread through purchases and/or sales of instruments in other markets; to protect against currency fluctuations; as a duration management technique; to protect against any increase in the price of securities the Underlying ETF anticipates purchasing at a later date; to gain exposure to one or more securities, currencies, or interest rates; to take advantage of perceived mispricing in the securities markets; or to gain exposure to certain markets in an economical way.
The Fund will invest in Underlying ETFs that, in turn, hold equity securities, fixed income securities, currencies, index swaps, and commodities. Typically, the Underlying ETFs hold those securities and financial instruments “long” in the belief that they will outperform the relevant market over time. In contrast, the Fund may also invest in inverse Underlying ETFs, which typically produce investment results that are opposite of a particular benchmark index. Inverse Underlying ETFs essentially provide the Fund with “short” exposure, because their portfolios benefit when the relevant market declines. The Fund will generally have net exposure ranging from 20% short to 100% long equities. The Fund’s net exposure at any time is the total of the Fund’s percentage of long holdings (including leverage) less the percentage of its short exposure. For example, if the Fund’s long holdings totaled 60% and its short exposure totaled 40%, the Fund’s net exposure would be 20% long (60%-40%). The Fund’s short exposure will be obtained via investments in inverse ETFs.
Market Environments/Fund Positioning:
The Sub-Adviser utilizes a proprietary, analytical investment model that examines current and historical ETF market data to seek to structure a portfolio that will benefit over a full market cycle (described below) by identifying and responding to changes in price momentum in the global equity markets. Essentially, the Fund seeks to capitalize on the tendency of stock prices to continue trending in the same direction over short- to medium-term periods. The Sub-Adviser’s model analyzes a number of criteria, such as ETF trade volumes, prices, pricing and volume trends, and activities in the futures markets over various periods to identify broad market signals indicating an upward or downward trend. The Sub-Adviser’s model then analyzes the size (or “amplitude”) and prevalence (or “frequency”) of these signals to determine which of four market environments is then prevailing. The four market environments and how they impact the Fund’s positioning are:
● | Bullish – The Fund is positioned long, with an aggressive investment tilt. In this state, the Fund’s portfolio will largely be comprised of long-only equity Underlying ETFs. In this state, the Fund will generally participate in changes to the overall equity markets (both U.S. and foreign). The Underlying ETFs will likely include: |
○ | Growth-focused ETFs (e.g., ETFs that invest in equity securities of companies that are expected to have above average growth rates), |
○ | Momentum-focused ETFs (e.g., ETFs that invest in equity securities with higher recent price performance compared to other securities), |
○ | Thematic ETFs (e.g., ETFs that invest based on a particular theme, such as climate change or artificial intelligence), and |
○ | Sector ETFs (e.g., ETFs that invest in one or more market sectors, such as consumer discretionary or health care). |
● | Moderate – The Fund is positioned long, with a moderate investment tilt. In this state, the Fund’s portfolio will largely be comprised of (a) long-only, broad-based, equity Underlying ETFs with (b) a moderate allocation (about 40% to 60% of the Fund’s portfolio), to more focused Underlying ETFs (e.g., sector or commodity ETFs). The Underlying ETFs may include: |
○ | Growth-focused ETFs, |
○ | Value-focused ETFs (e.g., ETFs that invest in equity securities of companies whose securities have low prices relative to estimates of their fundamental (or intrinsic) value), and |
○ | Sector ETFs. |
○ | Commodity ETFs (e.g., gold). |
○ | Currency ETFs. |
● | Hedged – The Fund is positioned as hedged. In this state, the Fund’s portfolio will be comprised of approximately half (or slightly more than half) of long-only equity Underlying ETFs and the other half (or slightly less than half) will consist of allocations to more Underlying ETFs that provide short exposure and to more focused Underlying ETFs. In this state, the Fund will generally participate in changes to the overall equity markets only to a limited extent. The Underlying ETFs may include: |
○ | Growth-focused and Value-focused ETFs (which correlate to and offset to a limited extent the Fund’s inverse ETFs), |
○ | Inverse ETFs (e.g., ETFs that seek to produce investment results that are opposite of a particular benchmark index), |
○ | Leveraged ETFs, |
○ | Fixed income ETFs, and |
○ | Commodity ETFs (e.g., gold). |
○ | Currency ETFs. |
● | Bearish – The Fund is positioned short. In this state, the Fund’s portfolio will generally be comprised of a smaller allocation to long-only equity Underlying ETFs and a greater allocation to Underlying ETFs that provide short exposure and to more focused Underlying ETFs. In this state, the Fund will generally not participate in changes to the overall equity markets. The Underlying ETFs may include: |
○ | Growth-focused and Value-focused ETFs (which correlate to and offset to a limited extent the Fund’s inverse ETFs), |
○ | Inverse ETFs, |
○ | Leveraged ETFs, |
○ | Fixed income ETFs, and |
○ | Commodity ETFs (e.g., gold). |
○ | Currency ETFs. |
As described below, the Sub-Adviser selects more focused Underlying ETFs (e.g., sector, fixed income, etc.) depending on the then-current perceived market environment (i.e., Bullish, Moderate, etc.) and the model’s assessment of how best to position the Fund’s portfolio for anticipated changes to various markets (e.g., stock market, fixed income market, etc.). For example, the model may suggest that the Fund allocate a portion of its portfolio to gold ETFs because gold historically has not moved in line with the overall stock market.
The Sub-Adviser views a full market cycle as being secular and lasting an average of 10 years or more depending on underlying macroeconomic conditions, and containing periods of both cyclical bull and cyclical bear market events. Over a full market cycle, it is expected that the Fund will be in each of the four market environments approximately equally (i.e., about 25% in each market environment).
Model Analyses:
1. | Market Environment Analysis: The model’s recommendations are derived from an ongoing analysis of extensive market data regarding the Fund’s initial ETF universe, which is comprised of all ETFs that trade on U.S. stock exchange. See “Additional Information About the Fund” below for information about the data analyzed. |
The model’s analysis produces market signals (the “Signals”), which the model processes to classify the current market environment’s state. In particular, if the signal processing shows: |
● | Large but infrequent changes in the Signals - the model will reflect a Bullish market environment, indicating the market appears strong and growing. |
● | Small and consistent changes in the Signals - the model will reflect a Moderate market environment, indicating the market appears stable and not particularly strong or weak. |
● | Large and frequent changes in the Signals - the model will reflect a Hedged market environment, indicating the market appears volatile and there are significant changes happening on a regular basis. |
● | Small, but infrequent changes in the Signals - the model will reflect a Bearish market environment, indicating the market appears weak and declining. |
2. | Hedging Exposure/Sub-Market Exposure Analysis. |
The model recommends hedging exposure levels to adapt the Fund’s portfolio to the then-current market environment. For example, in a Bullish market environment, the Fund will not engage in hedging activity. In a Moderate market environment, the Fund will hedge a small portion of the Fund’s portfolio. The Fund’s level of hedging is increased for a Hedged market environment and increased further for a Bearish market environment.
The model may recommend that the Fund achieve the desired level hedging via different types of ETFs depending on the model’s assessment of the anticipated changes to various markets (e.g., stock market, fixed income market, commodities, etc.).
For example, in a Moderate market environment, the model may recommend ETFs (e.g., gold) with performance that has not historically correlated with a particular equity-based securities index. A higher level of hedging may be achieved by investing in one or more inverse ETFs.
The model also recommends, on an ongoing basis, sizing of the Fund’s exposure to various sub-markets (e.g., the percentage of the Fund’s portfolio to be invested in long-equities, bonds, commodities, etc.).
3. | Underlying ETF Analysis: |
The model evaluates the universe of ETFs to select Underlying ETFs most appropriate for the Fund’s portfolio. To do so, the model analyzes a range of ETF attributes including:
● | diversification (e.g., the number of securities held). |
● | correlation (e.g., whether an ETF’s returns are consistent with (or deviate from) other ETFs or indices. |
● | moving average (e.g., examines whether the value of the ETF is generally increasing or decreasing over different periods). |
Further, the model evaluates subsets of similarly-focused ETFs. For example, the model conducts comparative analyses for broad-based, passively managed ETFs, market sector-focused ETFs (e.g., healthcare, energy, technology, and finance), and factor-style focused ETFs (e.g., value, growth, dividends, and momentum), and thematic-focused ETFs (e.g., ETFs that focus on predicting long-term trends), commodity ETFs (e.g., gold ETFs), and leveraged ETFs, among others. For each cohort of ETFs, the model scores the relevant ETFs to determine the ETFs that may provide the best fit for the model’s recommended overall portfolio. The model tends to favor lower-cost ETFs that provide exposure consistent with the model’s signals. For example, if the model signals that the Fund should invest in one or more particular market sectors, the model will recommend ETFs that have relevant investment objectives.
Portfolio Construction:
The Sub-Adviser’s portfolio managers review the ETFs recommended by the model for the then-current market environment and review each potential ETF’s attributes. Based on the portfolio managers’ assessment, Underlying ETFs are selected for the Fund’s portfolio.
The Fund’s portfolio will generally hold between five and twenty Underlying ETFs. As noted above, the Fund will generally have net equity exposure ranging from 20% short to 100% long.
Period | HF Return | Category Return Low | Category Return High | Rank in Category (%) |
---|---|---|---|---|
YTD | 5.4% | N/A | N/A | N/A |
1 Yr | N/A | 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
Period | HF Return | Category Return Low | Category Return High | Rank in Category (%) |
---|---|---|---|---|
2023 | N/A | 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 |
Period | HF Return | Category Return Low | Category Return High | Rank in Category (%) |
---|---|---|---|---|
YTD | 5.4% | N/A | N/A | N/A |
1 Yr | N/A | 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
Period | HF Return | Category Return Low | Category Return High | Rank in Category (%) |
---|---|---|---|---|
2023 | N/A | 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 |
HF | Category Low | Category High | HF % Rank | |
---|---|---|---|---|
Net Assets | 17.7 M | N/A | N/A | N/A |
Number of Holdings | 11 | N/A | N/A | N/A |
Net Assets in Top 10 | 16.9 M | N/A | N/A | N/A |
Weighting of Top 10 | 99.80% | N/A | N/A | N/A |
Weighting | Return Low | Return High | HF % Rank | |
---|---|---|---|---|
Stocks | 99.80% | N/A | N/A | N/A |
Cash | 0.31% | N/A | N/A | N/A |
Preferred Stocks | 0.00% | N/A | N/A | N/A |
Other | 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 |
Weighting | Return Low | Return High | HF % 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 |
Weighting | Return Low | Return High | HF % Rank | |
---|---|---|---|---|
US | 99.80% | N/A | N/A | N/A |
Non US | 0.00% | N/A | N/A | N/A |
HF Fees (% of AUM) | Category Return Low | Category Return High | Rank in Category (%) | |
---|---|---|---|---|
Expense Ratio | 1.68% | N/A | N/A | N/A |
Management Fee | 1.50% | 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 |
HF 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 |
HF Fees (% of AUM) | Category Return Low | Category Return High | Rank in Category (%) | |
---|---|---|---|---|
Max Redemption Fee | N/A | N/A | N/A | N/A |
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.
HF Fees (% of AUM) | Category Return Low | Category Return High | Rank in Category (%) | |
---|---|---|---|---|
Turnover | N/A | N/A | N/A | N/A |
HF | Category Low | Category High | HF % Rank | |
---|---|---|---|---|
Dividend Yield | 0.00% | N/A | N/A | N/A |
HF | Category Low | Category High | Category Mod | |
---|---|---|---|---|
Dividend Distribution Frequency | None |
HF | Category Low | Category High | HF % Rank | |
---|---|---|---|---|
Net Income Ratio | N/A | N/A | N/A | N/A |
HF | Category Low | Category High | Capital Mode | |
---|---|---|---|---|
Capital Gain Distribution Frequency |
Dividend Investing Ideas Center
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