Factor Spotlight
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Adding A Sector Lens - Introducing the Wolfe Research Sector Models

We are thrilled to announce that we have added several highly anticipated Risk Models from Wolfe Research to the Omega Point platform that will help enhance performance/risk analysis, portfolio construction, and precision basket hedging. The Wolfe Sector models now available include:

  • Energy
  • Consumers (Discretionary + Staples)
  • Technology, Media, and Telecom (TMT)
  • Healthcare
  • Industrials & Materials
  • Financials

Why a Sector Model?
Imagine you are an arborist attempting to study a jungle - what is the correct approach to understanding it? Do you rent a helicopter and fly over it, observing and taking notes about the jungle as a whole? Or do you take your trusty machete and cut your way into the heart of the jungle labeling all the individual plant species? Or do you simply take the most abundant plant and study only that single plant and its characteristics? All three approaches are valid, all have their pros and cons, and all describe aspects of the jungle... So which one is ‘right’?

We now leave this thought experiment and leave the imaginary jungle to the real jungle of global equity markets. We now have a broad market that is the sum of many different underlying parts: regions, countries, sectors, industries, and sub-industries. Risk model vendors attempt to map the critical risks for equity markets and face a similar challenge as our imaginary arborist, but in this case the challenge is numerical in nature.

Risk model creators are faced with a trade-off between including more factors that can describe all market risk drivers and reducing the number factors to make the model more parsimonious. While it seems that a large model that includes all possible risk factors would be ideal, statistics quickly crushes our dreams because including too many factors makes it impossible to correctly estimate them all. But if we go too far in the direction of reducing the factors in our model, we could potentially miss critical risk drivers that lead to unexpected risks and painful drawdowns.

Accordingly, there is rarely one ‘perfect’ equity risk model for the entire universe of investment professionals. A Global model may make perfect sense for a CRO looking at a highly diversified portfolio of portfolios, but will fail to capture Sector level phenomena. But a Global Model may not work for an Emerging Markets manager, who only invests in Emerging Markets where different factor behavior may be occurring. And a Global model will likely miss the granular risk drivers of a Sector-only portfolio, where sector behavior can be nuanced compared to a higher-level Global risk model.

Wolfe Sector Model Differentiators and Benefits
The Wolfe Sector models are accordingly an ideal solution for Analysts, PMs, and Risk Managers focused on concentrated Sector portfolios.

  • Each Sector model’s predicted risks are estimated using only assets within that given Sector. This helps ‘tune’ the model to more accurately model the unique market behavior of each sector.
  • Each Sector model has Fundamental, Technical, Alternative, Macro, and Positioning Factors, but the exact factors vary depending on the sector. For example, the Tech-Media-Telecom model includes unique growth oriented balance sheet and income statement information such as Return on Equity and Sales Growth, whereas the Consumer model includes Inventory Turnover. Another example would be the Energy model and it’s Macro factors: Oil beta, Natural Gas beta, and Interest Rate Beta.
  • Each Sector model has tailored GICS factors. Typically broad models rely on the Industry Level classification, but Sector Models can go deeper in the GICS structure to Sub-Industries. For example, the Energy Sector model includes the following granular GICS classifications: Refiners, Coal, Extraction Services, Oil & Gas Extraction, Pipeline & Tankers, and Drilling (compared to the two Energy GICS Industries of “Energy Equipment & Services“ and “Oil, Gas & Consumable Fuels“). The extra industry granularity provides more accurate risk estimates of companies exposed to various aspects of the Energy sector.

Over the following weeks we’ll visit some of these select Sector models in more detail, and explore their factors and benefits for Sector managers.

US & Global Market Summary

US Market: 02/01/21 - 02/05/21

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US Stock Market Cumulative Return: 2/1/2021 - 2/5/2021
  • All three benchmarks notched their best week since November, with the S&P 500 rising to a new record on Friday as 10 of the 11 sectors posted gains.
  • The Senate passed a budget resolution early Friday, as Democrats move forward with the process to pass a $1.9 trillion coronavirus relief bill. The package includes $1,400 stimulus checks, a supplemental jobless benefit and Covid-19 vaccine and testing funds.
  • The Cboe Vix — a measure of expected volatility known as Wall Street’s “fear gauge” —fell more than 12 points with the recent speculative trading frenzy dissipating.
  • The Labor Department said the U.S. added 49,000 jobs in January, slightly below the 50,000 payrolls expected by economists. The unemployment rate fell to 6.3%, better than projections of 6.7%.
  • Wall Street is in the middle of a solid earnings season, with observers noting that of the 184 companies in the S&P 500 that have reported earnings to date, over 84% have topped analyst expectations.

Normalized Factor Returns: Axioma US Equity Risk Model (AXUS4-MH)

Screen Shot 2021-02-06 at 7.15.41 PM.png
Methodology for normalized factor returns
  • Growth continues to show strong movement going deeper into positive territory and takes over the top spot this week.
  • Size increased this week, though still far off from positive territory.
  • After finally breaking into positive territory last week, Earnings Yield keeps chugging along and gains for the seventh consecutive week.
  • Momentum popped back slightly following a rare retreat last week.
  • Value continues its slide further into negative territory and once again finishes as the week’s biggest loser.
  • Last week’s winner Profitability finishes the week just shy of the bottom spot.
  • US Total Risk (using the Russell 3000 as proxy) increased by 9bps.

Normalized Factor Returns: Axioma Worldwide Equity Risk Model (AXWW4-MH)

Screen Shot 2021-02-06 at 7.48.05 PM.png
Methodology for normalized factor returns

  • Earnings Yield, Size and Volatility all finish as the week’s only positive movers, flipping on their negative grouping last week.
  • Growth and Momentum finally fall back down to earth after finishing in the two top spots for a record 8 weeks, but still sit comfortably in positive territory.
  • Market Sensitivity and Exchange Rate Sensitivity line up at the bottom for the third straight week.
  • Global Risk (using the ACWI as proxy) increased for by 14bps for the second consecutive week.


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