Our recent series centered on Smart Hedging appears to have struck a major chord with many readers, judging by the high volume of comments and questions we’ve received since we first broached the topic. This is an area the institutional investment community has been grappling with as managers seek to strengthen their internal risk management practices while remaining competitive for ever-fickle client assets that have more product destinations than ever before.
It is our hope, especially for the continued prosperity of our community, that this exploration will in turn spark further discussions and research initiatives within your organizations. For those of you who may had missed these posts and would like to find out what all the buzz was all about, I encourage you to check out the links below:
10/20 THE INHERENT VOLATILITY OF A SPY HEDGE
10/27 BUILDING A SUPERIOR SPY HEDGE
11/3 BUILDING A SMARTER TECH HEDGE
This week, we’ll highlight a broader development in the investment management industry, of which smart hedging is included. Today’s reality of readily accessible machine-aided smart hedging strategies like the one’s we’ve demonstrated was either unthinkable or unreachable for the vast majority of investment managers just a few short years ago. But the turnkey availability of this new breed of technology is really just an offshoot of a wholesale industry transformation, one that is rattling the foundations of how to approach construction of even the most basic portfolios.
We’re excited to be on the front lines of what we see as a convergence between the spiraling expectations of stakeholders, technology that has evolved to offer close-to limitless product personalization capabilities, and a long overdue maturation of the big data arena. We hold little doubt that successful alignment to this convergence by investment organizations will be what separates the winners from the losers, and further blur the already shaky lines between the fundamental and quantitative investment worlds.
While we plan on taking a closer look at each of these forces in subsequent issues, this week we’ll take a closer look at a key development that is reshaping the product landscape.
The Exchange-Traded-Fund (ETF) Market
Ever since State Street Global Advisors launched the the first U.S.-listed ETF S&P 500 SPDR (SPY) in 1993, both the retail and institutional investment communities enthusiastically embraced this new product category as a missing piece of the puzzle that could propel hitherto unreachable investing and hedging strategies. Sky-high demand resulted in an avalanche of ETFs encompassing all shapes, sizes and flavors which now stands at a grand total of over 5,000 global ETFs available to investors today.
What isn’t there to love? Compared to individual stocks and mutual funds, they came out-of-the-gate offering benefits of accessible diversification, lower costs, transparency, liquidity, tax advantages, among many others.
And as we’ve seen, ETFs such as SPY, QQK, XLK and others still remain the vehicle of choice by institutional investors when hedging market risk within their portfolios.
So What’s the Problem with ETFs for Institutional Investors?
While still a boon to many investors and likely a major product category for decades to come, the ETF market hasn’t kept pace with certain key underlying trends reshaping the institutional asset management industry. Stakeholders requirements, readily accessible big data, and the adoption of ‘quantamental’ strategies keep pushing their bars higher, while the core underpinnings of the ETF market have essentially remained the same for close to three decades. The band-aid solution that worked for many years had been to keep packaging new variations and combinations to satisfy the demand.
It was a great run, but in today’s reality, the ETF market never stood a longer-term chance for many investors.
One word: customizability
The one-size-fits-most nature of the ETF markets is ill-suited to scrape even the minimum needs of modern institutional portfolio managers who have been busy overlaying machine-aided processes onto their core fundamental methodology to remain competitive for those always elusive investor assets.
To see why, please briefly indulge me in drawing an analogy of the ETF universe as items displayed on a typical restaurant menu. The proprietors have likely surveyed demand and taste in their locale to determine what type of cuisine and specific menu items will be most popular, and thus most profitable. Once the doors open, if demand for an item is low, they’ll probably drop it and add another offering more upside.
If enough customers are requesting an item they are missing, they’ll likely add it. As a customer, you’ll certainly have a wide variety of choices to complete your meal - as long as they’re on the menu! The establishment may disclose the ingredients and tweak dishes to your individual taste based on what’s back in the kitchen, but if you make too many demands you’ll likely be out the door looking for an eatery better suited to you.
Or, you can learn to cook your perfect meal. Unlimited ingredients are a click away, and you can refine your recipes to suit your taste until you’re absolutely drowning in deliciousness. No worries about food allergies either.
If you think you know where I’m going with this, I’ll now flip that analogy on its head:
As institutional money managers, WE ARE THE RESTAURANT.
But a very special type of restaurant. We’re expected by investors to not just be world-class chefs, but also be able to tailor any dish and cuisine consistent with our promised specialty.
If all we served up were fixed menu item ETFs, our ability to satisfy demand in this day and age would certainly be throttled and investors will likely go elsewhere in a heartbeat.
An ETF is essentially What You See is What You Get
What if you’d like to engage in the following?
- Adjust the weighting of individual names - OUT OF LUCK
- Align with your ESG mandates - OUT OF LUCK
- Add an asset class - OUT OF LUCK
- Tilt the basket based on your desired factor exposures - OUT OF LUCK
- Remove names you may be overweight outside the basket - OUT OF LUCK
- Minimize Tracking Errors to Indices and Benchmarks - OUT OF LUCK
- Hedge Market Risk - DON’T EVEN GET ME STARTED
And the list goes on and on...
Direct Indexing is a solution that removes most of the hurdles associated with the ETF Market to the institutional investment community.
Let’s briefly compare some of the key differences between ETFs and Direct Indexing models that are most relevant to institutional investors:
The financial dictionary definition of Direct Indexing typically reads that it “attempts to replicate the performance of any index or benchmark through direct purchase of the underlying individual securities instead of using an ETF or mutual fund.”
OK, that sounds fairly straightforward. Big deal, you can package up a bunch of stocks that you like and trade them together.
But in actual practice, the concept has evolved light years beyond the simple definition you’ll find all over the Internet. With AI and machine learning technology such as Omega Point’s now helping uncover even the most minute and esoteric forces impacting portfolios, Direct Indexing is really the ONLY way to effectively practice such a new breed of portfolio optimization.
But lest we think this is just the latest and greatest, Direct Indexing has actually been around for quite some time. Firms like Parametric have been serving the institutional and retail markets for direct indexing and tax-loss harvesting since the early 1990s.
On the retail front, an ecosystem of brokers and other providers has emerged to offer individual clients the ability to buy fractional shares using underlying Direct Investing methodologies.
A further catalyst is the remarkable growth in sustainable investing which is being helped by firms such as OpenInvest who use Direct Indexing to build customized portfolios for its clients based on ESG data.
On a broader level, Direct Indexing has been driving in the direction of leveraging alternative data to build a wide variety of customized investment products to:
- Hedge out risks in the portfolio
- Capture new thematic opportunities through the lens of new data
We expect that Direct Indexing will continue its impressive trajectory over the next several years, especially since it touches each of the 4 converging themes identified earlier that are shaking up the investment management industry:
- More Individualized Stakeholder Needs
- Product Personalization
- Big Data
- The blurring between Active and Passive investing
Many of ETF market’s drawbacks are finally coming to light as the institutional investment community continues its shift up the technological continuum. For many participants, ETFs remain the vehicle of choice, even if begrudgingly acknowledging that the outcomes are less than ideal. At least it’s better than nothing?
Direct Indexing is certainly a better option, and it’s within reach of just about every institutional investment manager. All of us at Omega Point are highly bullish that Direct Indexing will continue to blaze new trails for modern portfolio managers and are excited to be able to participate in a movement that we believe will propel our industry for years to come.
If you’re interested in learning more about this topic (and a slew of others in our wheelhouse), please don’t hesitate to reach out.
Now on to this past week’s market summary.
- The market continued to see strength throughout the week, driven by investor optimism that the US - China trade spat was moving towards a resolution due to comments from China’s Ministry of Commerce.
- The S&P 500, DOW, and NASDAQ all hit new highs on Friday despite comments from Trump that he hadn’t yet agreed to any Chinese tariff reductions.
- The University of Michigan consumer index rose from 95.5 to 95.7 in October, vs. consensus forecast of 95.
Factor Update - US Model
- Market Sensitivity had the week’s biggest gains, continuing its rise further into Overbought space
- Value drifted down to +0.99 SD above the mean and then bounced back into Overbought territory.
- Momentum continued to revert back to the mean, albeit at a slower pace relative to the past few weeks as it surged away from being ~3 SD below the mean at the end of September.
- Growth also saw positive normalized gains but at a less rapid clip
- Earnings Yield hit a peak of +1.35 SD on 10/30 and appears to be flattening back towards the mean
- Size started to drift down from a recent height of +1.03 SD above the mean on 10/28, as it has now exited Overbought territory
- US Total Risk (using the Russell 3000 as proxy) saw a slight decrease of 15 bps.
Factor Update - Worldwide Model
- Volatility and Market Sensitivity both saw the biggest gains worldwide, as they both climbed higher into Overbought space
- Momentum ended exactly flat over the course of the week after seeing the most gains last week
- Size saw modest normalized gains as it inched up towards an Overbought designation
- Earnings Yield continued to revert down from Extremely Overbought territory, now sitting at +1.76 SD above the mean.
- Exchange Rate Sensitivity was again the biggest loser, as it continues to head towards being Extremely Oversold
- Global Risk (using the ACWI as proxy) declined 9 bps.
Please let us know if you’d like to learn more about using Omega Point to create a better hedge for your portfolio, or if you’d like to better understand your portfolio’s relationship with factors.