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ETFs

Day Hagan/Ned Davis Research Smart Sector Fixed Income ETF

SSFI
$--
Today’s Change
-- (--)

Snapshot
*

Inception Date
Sep 29 2021
Expense Ratio
0.79%
Type
Global Bonds
Fund Owner
Day Hagan
Volume (1m avg. daily)
$299,996
AUM
$41,751,500
Associated Index
None
Inverse/Leveraged
No
Passive/Active
Active
Fractionable on Composer
No
Prospectus
View

Top 10 Holdings

SPTL
SSgA Active Trust - SPDR Portfolio Long Term Treasury ETF
20.67%
BNDX
Vanguard Group, Inc. - Vanguard Total International Bond ETF
12.76%
SPMB
SPDR Series Trust - SPDR Portfolio Mortgage Backed Bond ETF
12.75%
SPBO
SPDR Series Trust - SPDR Portfolio Corporate Bond ETF
11.97%
VWOB
Vanguard Group, Inc. - Vanguard Emerging Markets Government Bond ETF
11.02%
SPHY
SPDR Series Trust - SPDR Portfolio High Yield Bond ETF
10.76%
BIL
SPDR Series Trust - SPDR Bloomberg 1-3 Month T-Bill ETF
9.69%
FLRN
SPDR Series Trust - SPDR Bloomberg Investment Grade Floating Rate ETF
5.50%
VTIP
Vanguard Malvern Funds - Vanguard Short-Term Inflation-Protected Securities Index Fund
3.41%
n/a
CASH AND CASH EQUIVALENTS
1.49%
Invest with SSFI

What is SSFI?

Under normal market conditions, the Fund will invest, indirectly through the Underlying Funds, at least 80% of its net assets, plus the amount of any borrowings for investment purposes, in fixed income securities. The Fund may invest in Underlying Funds without any constraints as to the duration (i.e., the sensitivity of a fixed income security s price to interest rate changes), maturity, and country of domicile (including emerging market countries) of the securities held by the Underlying Funds. Certain of the Underlying Funds may hold, without limit, debt securities of any credit quality including below investment grade debt securities (also known as junk bonds). The Fund utilizes the Ned Davis Fixed Income Model developed by NDR, to determine its allocation to each Category. The model combines unique macroeconomic and technical indicators which (i) evaluate the relative attractiveness of Underlying Funds across Categories; (ii) reallocate assets from Categories with unfavorable characteristics to areas providing the greatest opportunities; and (iii) protect capital by lowering duration and reducing credit risk during weak economic environments. The indicators for each Category focus on risk/reward characteristics of each Category with the goal of investing in the areas that have the highest probability of maximizing total return. By combining multiple and diverse indicators, which historically have been shown to add value in Category allocation decisions, the model seeks to objectively assess the weight of the evidence and generate Category allocation recommendations. The Fund s allocation to a particular Category may be greater than 25%. Conversely, the Fund s allocation to a particular Category may be reduced to 0% if the Category s model composite is at low levels.

ETFs related toSSFI

ETFs correlated to SSFI include ILTB, BLV, LQD

SSFI
Strategy Shares - Day Hagan/Ned Davis Research Smart Sector Fixed Income ETF
ILTB
BlackRock Institutional Trust Company N.A. - iShares Core 10+ Year USD Bond ETF
BLV
Vanguard Group, Inc. - Vanguard Long-Term Bond ETF
LQD
BlackRock Institutional Trust Company N.A. - iShares iBoxx USD Investment Grade Corporate Bond ETF
IUSB
BlackRock Institutional Trust Company N.A. - iShares Core Total USD Bond Market ETF
AGG
BlackRock Institutional Trust Company N.A. - iShares Core U.S. Aggregate Bond ETF
SCHZ
Schwab Strategic Trust - Schwab US Aggregate Bond ETF
FBND
Fidelity Covington Trust - Fidelity Total Bond ETF
BND
Vanguard Group, Inc. - Vanguard Total Bond Market ETF
SPBO
SPDR Series Trust - SPDR Portfolio Corporate Bond ETF
AVIG
American Century ETF Trust - Avantis Core Fixed Income ETF

What is ETF correlation?

Correlation is a measure of the strength of the relationship between two ETFs. It quantifies the degree to which prices of the two ETFs typically move together.

Here, correlation is measured over the past year with the Pearson correlation coefficient (Pearon’s r), which ranges from -1 to 1.

Using ETF correlations in portfolio and strategy construction

ETF correlations can help you create investing strategies and portfolios. Use them to:

  • •Build a diversified portfolio from uncorrelated or inversely correlated ETFs with the aim of minimizing portfolio risk.
  • •Compare correlated or related ETFs to find one with a lower expense ratio or higher trading volume.
  • •Create an investing strategy that hedges an ETF with an uncorrelated or inversely correlated ETF.

Automated Strategies
Related toSSFI

#PTAC

Pick the Trending Asset Class

Category

Momentum, Tactical Asset Allocation, Be Risk Aware, Ride the Momentum

Risk Rating

Moderate

#DPE

Diversify with Private Equity

Category

Getting Started, Go Global, Diversification

Risk Rating

Moderate

Create your own algorithmic trading strategy with SSFI using Composer

FAQ

SSFI is a Global Bonds ETF. Under normal market conditions, the Fund will invest, indirectly through the Underlying Funds, at least 80% of its net assets, plus the amount of any borrowings for investment purposes, in fixed income securities. The Fund may invest in Underlying Funds without any constraints as to the duration (i.e., the sensitivity of a fixed income security s price to interest rate changes), maturity, and country of domicile (including emerging market countries) of the securities held by the Underlying Funds. Certain of the Underlying Funds may hold, without limit, debt securities of any credit quality including below investment grade debt securities (also known as junk bonds). The Fund utilizes the Ned Davis Fixed Income Model developed by NDR, to determine its allocation to each Category. The model combines unique macroeconomic and technical indicators which (i) evaluate the relative attractiveness of Underlying Funds across Categories; (ii) reallocate assets from Categories with unfavorable characteristics to areas providing the greatest opportunities; and (iii) protect capital by lowering duration and reducing credit risk during weak economic environments. The indicators for each Category focus on risk/reward characteristics of each Category with the goal of investing in the areas that have the highest probability of maximizing total return. By combining multiple and diverse indicators, which historically have been shown to add value in Category allocation decisions, the model seeks to objectively assess the weight of the evidence and generate Category allocation recommendations. The Fund s allocation to a particular Category may be greater than 25%. Conversely, the Fund s allocation to a particular Category may be reduced to 0% if the Category s model composite is at low levels.

Yes, SSFI is actively managed. In an actively managed fund, the fund manager makes decisions about how funds are invested. A passively managed fund typically tries to track or follow a market index.

No, SSFI is not passively managed. It is actively managed. A passively managed fund typically tries to track or follow a market index. In an actively managed fund, the fund manager makes decisions about how funds are invested.

The 1-month return on SSFI is -0.0167%. This is the percent change in the value of SSFI over the most recent 1-month period. The 3-month return on SSFI is -0.0347%. This is the percent change in the value of SSFI over the most recent 3-month period.

The standard deviation of SSFI for the past year is 0.0704%. Standard deviation is the typical amount that the daily returns vary from the mean of the returns over the time period, standardized to a period of a year.

ETFs similar to SSFI include GSY, GVI, and BSV.

ETFs correlated to SSFI include ILTB, BLV, and LQD.

ETFs that are inversely correlated to SSFI include TTT, TBF, and TMV.

Disclaimers

*

We show information directly obtained from our data provider, Xignite. Data shown here is provided by Xignite, an unaffiliated third party. Composer believes the information shown here is reliable, but has not been verified and there is no guarantee that the information is accurate.

**

We show information based on calculations performed by Composer using data from our provider. Information provided here is based on calculations performed by Composer using data sourced from Xignite, an unaffiliated third party. Composer believes this information is reliable, but has not verified the data and there is no guarantee that the calculations are accurate.