ALPS Sector Dividend Dogs ETFALPS Sector Dividend Dogs ETFALPS Sector Dividend Dogs ETF

ALPS Sector Dividend Dogs ETF

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Key stats


Assets under management (AUM)
‪1.25 B‬USD
Fund flows (1Y)
‪−81.33 M‬USD
Dividend yield (indicated)
3.72%
Discount/Premium to NAV
−0.03%

About ALPS Sector Dividend Dogs ETF


Issuer
SS&C Technologies Holdings, Inc.
Brand
ALPS
Expense ratio
0.36%
Home page
Inception date
Jun 29, 2012
Index tracked
S-Network Sector Dividend Dogs Index
Management style
Passive
SDOG is built around the theory that high-yielding equities tend to appreciate faster than lower-yielding equities. SDOG starts with the S&P 500 and then equally weights the five companies in each GICS sector with the highest dividend yields. It also equal weights those sectors, which introduces permanent sector biases. It reconstitutes its portfolio annually, but it subsequently rebalances that portfolio every quarter. SDOG's methodology may cause it to diverge considerably from our segment benchmark with a heavy mid-cap tilt and huge sector biases.

Classification


Asset Class
Equity
Category
Size and style
Focus
Large cap
Niche
Broad-based
Strategy
Dividends
Weighting scheme
Equal
Selection criteria
Dividends
What's in the fund
Exposure type
StocksBonds, Cash & Other
Finance
Health Technology
Electronic Technology
Stock breakdown by region
100%
Summarizing what the indicators are suggesting.
Oscillators
Neutral
SellBuy
Strong sellStrong buy
Strong sellSellNeutralBuyStrong buy
Oscillators
Neutral
SellBuy
Strong sellStrong buy
Strong sellSellNeutralBuyStrong buy
Summary
Neutral
SellBuy
Strong sellStrong buy
Strong sellSellNeutralBuyStrong buy
Summary
Neutral
SellBuy
Strong sellStrong buy
Strong sellSellNeutralBuyStrong buy
Summary
Neutral
SellBuy
Strong sellStrong buy
Strong sellSellNeutralBuyStrong buy
Moving Averages
Neutral
SellBuy
Strong sellStrong buy
Strong sellSellNeutralBuyStrong buy
Moving Averages
Neutral
SellBuy
Strong sellStrong buy
Strong sellSellNeutralBuyStrong buy
Displays a symbol's price movements over previous years to identify recurring trends.