Force ranking across sectors

I force rank my coverage by sub-sector and we have general allocations for sub-sectors that help size trades. I was talking to a buddy whose pod is effectively generalist and he said that they force rank across sector groupings. It’s not like utes and CPG in the same buckets but utes would be with A&D, multis, O&G, etc. Assuming revisions is the key driver, a 10% revision for a utility is way different than a similar revision for like an LTL or E&P. How do you compare across sectors? Do you capitalize the revision at like current multiple to get % value change vs cons and compare? It’s easy enough to account for subsector sentiment but how would you control across sectors? 

3 Comments
 

When force ranking across sectors, especially in a generalist pod, the key is to normalize and standardize metrics to allow for meaningful comparisons. Based on the most helpful WSO content, here’s how you might approach it:

  1. Capitalizing Revisions:

    • Yes, capitalizing the revision at the current multiple is a common approach. For example, if a utility has a 10% revision and trades at a 15x multiple, you’d calculate the implied value change (10% x 15x = 150% value change). This allows you to compare the impact of revisions across sectors with different valuation multiples.
  2. Adjusting for Sector-Specific Sentiment:

    • Subsector sentiment is crucial. For instance, utilities (utes) and oil & gas (O&G) might have vastly different market dynamics. To control for this, you could use relative performance metrics or compare against sector benchmarks to gauge how much of the revision impact is already priced in.
  3. Normalizing Across Sectors:

    • To control for differences in sector dynamics (e.g., growth rates, cyclicality), you could use metrics like:
      • Percentage Value Change vs. Consensus: This helps standardize the impact of revisions relative to expectations.
      • Risk-Adjusted Returns: Incorporate volatility or beta to account for sector-specific risk profiles.
      • Growth-Adjusted Multiples: For example, compare PEG ratios (P/E to growth) across sectors to normalize for growth differences.
  4. Framework for Comparison:

    • Create a scoring system that weights key factors like revisions, sentiment, and risk-adjusted returns. For example:
      • Revisions Impact (40%): Capitalized revision value change.
      • Sector Sentiment (30%): Relative performance to sector benchmarks.
      • Risk-Adjusted Metrics (30%): Volatility or beta-adjusted returns.
  5. Consider Sector-Specific Nuances:

    • As you mentioned, a 10% revision for a utility is very different from one for an LTL (less-than-truckload) or E&P (exploration & production). Incorporate qualitative factors like cyclicality, regulatory environment, and macro drivers to refine your rankings.

By combining these quantitative and qualitative approaches, you can create a robust framework for force ranking across sectors while accounting for their unique characteristics.

Sources: Beginners Guide to Valuation and Metrics By Sector, Beginners Guide to Valuation and Metrics By Sector, Reflections from year 4 as an equity analyst, Performance of Top Tier vs. Bottom Tier Analysts (Q&A in Comments), Private Equity Recruiting Process (From Banking)

I'm an AI bot trained on the most helpful WSO content across 17+ years.
 

Would imagine they back into some form of z score for the revision. Implied earnings move is X, we’re at Y% beat/miss. Size it Y/X relative - this corrects for the revision differences you called out between E&P and utes

Still not exactly sure what the question is - why do the sectors need to be force ranked in a mkt neutral book? Can u not just force rank conviction on individual names for sizing? Or is there sector beta being taken? If sector beta then revisions not even really the driver anymore

Unrelated, but if you’re the analyst trying to cover all three of A&D Utes and E&P in mkt neutral I feel sorry for you

 

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