Have you ever asked yourself, "What really is that beta in your ETF?" As more and more money continues to flow into passive ETFs, how and what is exactly the best way to value your ETF. Nowadays, there are dozens of US Large-Cap, Value, and Growth ETFs, and investors must find a way to select the best ETF in each category. In, "What Really Is That Beta In Your ETF?", we dive into these topics.
2. 2
What Are ETFs?
ETFs, or Exchange-Traded Funds, are a basket of securities representing a portfolio
that investors can purchase to introduce a desired exposure or allocation
Unlike mutual funds, ETF prices are updated regularly through the trading day and
can be bought or sold just like a stock
ETFs typically offer lower fees compared to those of mutual funds
3. 3
ETF Industry Observations
ETFs offer investors cost-efficient methods of building diversified portfolios at a low
cost
ETF industry continues to gain market share of investable assets:
2017 ETF Inflows: $476 billion
2018 ETF Inflows: $315 billion
In 2017, less than 1% of all ETFs received more than 50% of all ETF inflows
Does the typical investors have the ability to ask and answer the question “What is
actually inside my ETF?”
Source: MarketWatch, ETF.com
4. ETFs and Portfolio
Attribution
Attribution analysis of holdings should be a point of consideration
for any investor selecting an ETF
Attribution analysis can be applied to ETF holdings based on:
4
Sectors
Factors
Size – Market Capitalization, Sales, etc.
Geographic Location
5. 5
State of the ETF Industry
$204.3B $283.2B
$396.5B
$565.9B
$794.2B $710.7B
$1,042.5B
$1,311.6B$1,353.7B
$1,756.2B
$2,253.2B
$2,647.1B
$2,911.3B
$3,328.8B
$4,464.1B
$0B
$500B
$1,000B
$1,500B
$2,000B
$2,500B
$3,000B
$3,500B
$4,000B
$4,500B
$5,000B
2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017
Global ETFsTotal Assets Under Management in USD$ Billions (2003-2017)
Source: Statista
7. 7
ETF Providers – AUM
Strategists have highlighted that the ETF
industry in its current state may pose a high
concentration risk
ETFs managed by BlackRock,Vanguard, and
State Street combine to make up nearly 2/3
of total assets under management in the ETF
industry
Right now, north of 10,000 mutual funds in
the US with just over 4,000 ETFs based in the
US
Source: ETF Global,Quantamize
$1,433.50B
$923.74B
$622.82B
$180.14B
$59.66B
$36.12B
$0B$500B$1,000B$1,500B$2,000B
BlackRock
Vanguard
State Street
Invesco
First Trust
Van Eck
Total ETF Assets Under Management as of
02/22/19 (in USD$ billions)
Total Assets Under Management (in USD$ billions)
8. 8
ETF Providers – Fund Flows
Source: ETF Global,Quantamize
$207.51B
$72.70B
$7.79B $4.52B $0.19B $0.05B
$0B
$50B
$100B
$150B
$200B
$250B
BlackRock Vanguard Invesco First Trust State Street Global
Advisers
Van Eck
ETF Provider 2018 Fund Flows (in USD$ billions)
9. 9
How Do Investors Select ETFs
Investors select an ETF because it
represents a desired strategy
Strategies
Investors select an ETF because it
maintains a low expense ratio
Expense Ratios
Investors select an ETF to benefit
from its tax incentives
Tax Benefits
Investors select an ETF based on strong
historical performance
Performance
Investors select an ETF based on
a familiar name
Brands
Investors select an ETF because it
has among the highest AUM
Assets Under Management
14. 14
S&P Capital IQ
FactSet
Bulge Bracket Investment Banks
Bloomberg
Axioma
Elite Quant Hedge Funds
Examples of Who Can Value ETFs
15. 15
What Did We Do?
For our study of ETF attribution, we focused on 3 groups:
US Large-Cap
USValue
US LowVolatility
We apply 3 types of analytics tools in our study:
S&P Risk Analysis
Bloomberg Risk Analysis
Proprietary AI Factor Methodology
16. 16
What Did We Do?
Next, we ranked the ETFs in each category from best to worst based on sub-factor
exposures scoring each sub-factor group by terciles
Scores are based on ordinal ranking – z-score methodology
Absolute measures are less important than their relative rank within a category
When selecting an ETF within a category, what matters most is how it ranks relative
to its peers in the category
22. 22
Bloomberg Model Results: US Value
Name Ticker Expense Ratio AUM Leverage
Earnings
Variability Momentum Size Volatility
Aggregate
Factor Score Final Rating
Alpha Architect US Quant Value QVAL 0.79% $0.13B Overweight Overweight Overweight Overweight Overweight 4.6 Best
iShares S&P Midcap 400 Value IJJ 0.25% $5.92B Underweight Overweight Neutral Neutral Overweight 3.8 Good
iShares Edge MSCI US Value Factor VLUE 0.15% $3.31B Neutral Overweight Overweight Neutral Underweight 3.6 Good
iShares Russell 300 Value IWV 0.20% $8.61B Overweight Neutral Neutral Neutral Neutral 3.5 Good
Vanguard MidCap Value VOE 0.07% $8.43B Underweight Neutral Overweight Neutral Neutral 3.4 Good
Invesco S&P 600 Pure Value RZV 0.35% $0.16B Overweight Overweight Underweight Overweight Underweight 3.4 Good
iShares Russell 2000 Value IWN 0.24% $9.33B Overweight Neutral Neutral Overweight Underweight 3.4 Good
First Trust Large-Cap Value AlphaDEX FTA 0.62% $1.05B Underweight Neutral Overweight Neutral Overweight 3.4 Good
SPDR S&P600 Value SLYV 0.15% $0.64B Overweight Overweight Underweight Overweight Underweight 3.4 Good
iShares S&P500 Value IVE 0.18% $15.97B Neutral Neutral Neutral Underweight Overweight 3.2 Caution
iShares Core S&P Value IUSV 0.04% $3.67B Neutral Overweight Neutral Underweight Overweight 3.0 Caution
Invesco S&P MidCap 400 Pure Value RFV 0.35% $0.11B Overweight Neutral Underweight Overweight Underweight 2.8 Caution
Vanguard SmallCap Value VBR 0.07% $13.05B Underweight Underweight Neutral Overweight Neutral 2.8 Caution
Schwab Large-Cap Value SCHV 0.04% $4.30B Underweight Underweight Overweight Neutral Neutral 2.6 Caution
Invesco S&P 500 Pure Value RPV 0.35% $0.86B Underweight Neutral Overweight Underweight Neutral 2.5 Caution
Vanguard Value VTV 0.05% $37.73B Neutral Underweight Neutral Underweight Underweight 2.4 Caution
Vanguard MegaCap 300 Value MGV 0.07% $2.00B Neutral Underweight Underweight Underweight Underweight 2.2 Poor
iShares Russell Midcap Value IWS 0.25% $10.49B Underweight Underweight Underweight Neutral Overweight 2.2 Poor
iShares Russell 1000 Value IWD 0.20% $36.93B Neutral Underweight Underweight Underweight Neutral 2.0 Poor
Vanguard Russell 1K Value VONV 0.12% $1.35B Neutral Underweight Underweight Underweight Neutral 1.8 Worst
Source: Bloomberg
23. 23
Factor Determination Using AI
IC Score and relevantT-Statistics maximized using an AI methodology
Repetition of iterative process until right combinations are found
Market not treated as homogenous, rather, we approach it as a heterogenous
environment with different factors driving different sizes, sectors, regions, etc.
Derived risk models have r2 north of 90% -- risk models are unique to market
capitalization
26. 26
AI Factor Model Results: US Value
Name Ticker Expense Ratio AUM Growth
Low Volatility &
Momentum Quality Value Technicals Size
Aggregate
Factor Score Final Rating
SPDR S&P600 Value SLYV 0.15% $0.64B Overweight Overweight Neutral Overweight Neutral 4.2 Best
iShares Russell 2000 Value IWN 0.24% $9.33B Neutral Overweight Overweight Neutral Overweight 4.2 Best
Vanguard SmallCap Value VBR 0.07% $13.05B Neutral Overweight Neutral Overweight Overweight 4.2 Best
Vanguard MidCap Value VOE 0.07% $8.43B Underweight Neutral Overweight Neutral Overweight 4.0 Good
iShares S&P Midcap 400 Value IJJ 0.25% $5.92B Underweight Overweight Neutral Overweight Overweight 4.0 Good
Invesco S&P MidCap 400 Pure Value RFV 0.35% $0.11B Overweight Overweight Overweight Underweight Neutral 3.8 Good
iShares Russell Midcap Value IWS 0.25% $10.49B Underweight Overweight Overweight Overweight Overweight 3.8 Good
Invesco S&P 600 Pure Value RZV 0.35% $0.16B Neutral Neutral Overweight Neutral Neutral 3.6 Caution
Invesco S&P 500 Pure Value RPV 0.35% $0.86B Overweight Neutral Neutral Underweight Neutral 3.0 Caution
Alpha Architect US Quant Value QVAL 0.79% $0.13B Underweight Neutral Neutral Underweight Overweight 2.8 Caution
iShares Russell 300 Value IWV 0.20% $8.61B Underweight Underweight Overweight Overweight Underweight 2.8 Caution
iShares Russell 1000 Value IWD 0.20% $36.93B Neutral Underweight Neutral Neutral Neutral 2.6 Caution
First Trust Large-Cap Value AlphaDEX FTA 0.62% $1.05B Underweight Neutral Underweight Overweight Neutral 2.6 Caution
Vanguard Russell 1K Value VONV 0.12% $1.35B Neutral Underweight Neutral Neutral Neutral 2.4 Caution
iShares Core S&P Value IUSV 0.04% $3.67B Neutral Neutral Underweight Underweight Underweight 2.4 Caution
Schwab Large-Cap Value SCHV 0.04% $4.30B Overweight Underweight Underweight Neutral Underweight 2.2 Caution
iShares S&P500 Value IVE 0.18% $15.97B Overweight Underweight Underweight Underweight Underweight 2.2 Caution
Vanguard MegaCap 300 Value MGV 0.07% $2.00B Overweight Underweight Underweight Underweight Underweight 1.8 Poor
iShares Edge MSCI US Value Factor VLUE 0.15% $3.31B Underweight Neutral Underweight Neutral Underweight 1.8 Poor
Vanguard Value VTV 0.05% $37.73B Neutral Underweight Underweight Underweight Underweight 1.6 Worst
Source: ETF Global,Quantamize
27. 27
Our Conclusions
Attribution analysis will be a primary
driver of ETF valuations in the future
Specifically, measuring beta exposures
of ETFs will be the primary valuation
methodology
With so many ETFs that claim to follow
the same strategy, attribution will be
how investors differentiate “best” from
“worst” and answer the question “How
do I really know what I am buying?”
Quantamize has established itself as a unique Artificial Intelligence quantitative investment factor research portal. Quantamize is now recognized within the industry as a leading quantitative factor research site. It now seeks to raise $3.25 million to expand its staff, ramp up marketing, expand current product offering, and take advantage of its business model opportunities.
Quantamize has established itself as a unique Artificial Intelligence quantitative investment factor research portal. Quantamize is now recognized within the industry as a leading quantitative factor research site. It now seeks to raise $3.25 million to expand its staff, ramp up marketing, expand current product offering, and take advantage of its business model opportunities.
Using big data, advanced technology, and Artificial Intelligence, Quantamize has developed proprietary advanced, multi-factor algorithms using “deep learning” neural networks, hierarchical risk parity and other AI techniques which are applied to global stocks, ETFs, options and cryptocurrencies.
The Quantamize algorithms use both traditional and alternative data. Quantamize advanced algorithms identify stock, ETFs, options and Cryptocurrency investment opportunities which are transparent and easily actionable. Our unique website offers independent investors proprietary investments and strategies, including:
AI-generated multi-factor algorithms/models that outperform US & global stock markets
AI-generated multi-factor regional and sector concentrated stock models for global markets
AI Smart Beta Rating Risk Model telling investors what really is the “beta exposure” of the ETF they are buying
AI Trading Signals for ETFs using a basket of multiple Deep Learning neural networks
AI-Powered Ranking Systems for 10,000 Stocks Across 30 Countries
Deep Learning Process used to highlight stocks in our factor-powered stock research report
Detailed unique landing pages including which includes (but not limited to) alternative sentiment data, relative ranks, etc for over 20,000 global stocks and 3,000 US-listed ETFs
Industry Leading Returns for Option Trades (e.g. average returns on premium north of 100% with average calendar duration of 32 days)
Machine Learning Accuracy Rates for Cryptocurrencies