Property And Casualty Industry Hedge Fund Crowding

0
Property And Casualty Industry Hedge Fund Crowding
2014-2015 Underperformance due to Property and Casualty Industry’s Portfolio Factor Exposures

Property And Casualty Industry Crowding by AlphaBetaWorks Insights

Property and casualty insurance company portfolios share a few systematic bets. These crowded bets are the main sources of the industry’s and many individual companies’ relative investment performance. Since the end of 2013, these exposures have cost the industry billions.

Identifying Property and Casualty Industry Crowding

This analysis of property and casualty (P&C) insurance industry portfolios resulted from collaboration with Peer Analytics, the only provider of accurate peer universe comparisons to the insurance industry.

In analyzing property and casualty industry portfolios, we follow the approach of our earlier articles on crowding: We created a position-weighted portfolio (P&C Aggregate) consisting of all property and casualty insurance portfolios reported in regulatory filings. P&C Aggregate covers over 1,300 companies with total portfolio value over $300 billion. We analyzed P&C Aggregate’s risk relative to Russell 3000 index (a close proxy for the U.S. Market) using AlphaBetaWorks’ Statistical Equity Risk Model to identify sources of crowding.

GrizzlyRock Value Partners returned 30 percent in the fourth quarter; Here are their favorite stocks

GrizzlyGrizzlyRock Value Partners returned 30.31% net for the fourth quarter, bringing its full-year return to 7.57% net. During the fourth quarter, longs added 42.8%, while shorts detracted 10.3%. Q4 2020 hedge fund letters, conferences and more In his annual letter to investors, which was reviewed by ValueWalk, managing partner Kyle Mowery noted that 2020 was Read More


Property and Casualty Industry 2014-2015 Underperformance

P&C Aggregate systematic (factor) performance lagged the market by over 4%, or over $12 billion, since the end of 2013. This is largely due to low (short, underweight) exposures to Market (Beta), Health, and Technology factors:

Below are the main contributing exposures, in percent:

Factor Return Portfolio Exposure Benchmark Exposure Relative Exposure Portfolio Return Benchmark Return Relative Return
Market 16.64 91.90 99.97 -8.07 15.25 16.63 -1.39
Health 21.12 6.59 13.09 -6.50 1.30 2.58 -1.29
Technology 5.93 8.93 19.10 -10.17 0.53 1.13 -0.60
FX 21.94 -3.72 -1.19 -2.53 -0.75 -0.24 -0.51
Energy -25.18 7.26 5.67 1.59 -1.99 -1.56 -0.43

For some companies, these exposures may be due to conscious portfolio and risk management processes. For others, they may have been unintended. For industry as a whole, robust risk and portfolio management would have generated billions in additional returns.

Property and Casualty Industry Year-end 2013 Crowding

Property and casualty industry’s recent crowding has been costly in practice. P&C Aggregate’s relative factor bets have cost it over 4% since year-end 2013. The industry made $12 billion less than it would have if it had simply matched market factor exposures.

Year-end 2013 Systematic (Factor) Exposures

Below are P&C Aggregate’s most significant factor exposures (Portfolio in red) relative to Russell 3000 (Benchmark in gray) as of 12/31/2013:

Factors Contributing Most to the Relative Portfolio Risk for Property and Casualty Industry Aggregate on 12/31/2013

P&C Aggregate’s factor exposures drive its systematic returns in various scenarios. The exposures above (underweight Market and Technology factors) suggest the P&C industry is preparing for technology crash akin to 2001. This and other historical regimes provide the stress tests below, similar to those now required of numerous managers.

Property and Casualty Industry Year-end 2014 Crowding

Year-end 2014 Systematic (Factor) Exposures

Property and casualty industry portfolio turnover is low. Consequently, industry factor exposures at year-end 2014 were close to those at year-end 2013. Below are P&C Aggregate’s most significant factor exposures (Portfolio in red) relative to Russell 3000 (Benchmark in gray) as of 12/31/2014:

Property and casualty industry
Factors Contributing Most to the Relative Portfolio Risk for Property and Casualty Industry Aggregate on 12/31/2014

The main exposures of the property and casualty industry were: short/underweight Market (Beta), long/overweight Size (large companies), short Health, and short Technology. The industry crowds towards large and low-beta Consumer and Financials stocks:

Factor Portfolio Exposure Benchmark Exposure Relative Exposure Factor Volatility Share of Absolute Factor Variance Share of Absolute Total Variance Share of Relative Factor Variance Share of Relative Total Variance
Market 90.39 99.97 -9.58 13.44 98.18 96.21 55.19 26.60
Size 13.32 -1.01 14.33 8.03 -0.91 -0.90 46.71 22.51
Health 7.68 13.09 -5.41 6.91 0.29 0.28 6.19 2.98
Technology 9.31 19.10 -9.79 5.80 -0.06 -0.06 4.16 2.00
Mining 1.54 0.63 0.91 15.61 -0.20 -0.19 1.76 0.85
Energy 3.93 5.67 -1.74 10.47 1.04 1.02 1.62 0.78
Consumer 27.11 23.04 4.08 3.91 -0.68 -0.66 1.53 0.74
Finance 21.48 18.92 2.56 5.48 -1.93 -1.89 1.49 0.72
Value 1.52 0.78 0.73 13.45 -0.04 -0.04 0.61 0.29

Scenario Analysis: 2000-2001 Outperformance

Given property and casualty industry’s under-weighting of Market and Technology, it would experience its highest outperformance in an environment similar to the 2001 technology crash. In this environment, industry’s systematic exposures would generate 2% outperformance:

Property and casualty industry
2000-2001: Stress test of outperformance due to Property and Casualty Industry’s Portfolio Factor Exposures

Below are the main contributors to this outperformance, in percent:

Factor Return Portfolio Exposure Benchmark Exposure Relative Exposure Portfolio Return Benchmark Return Relative Return
Technology -36.83 9.31 19.10 -9.79 -3.96 -7.99 4.04
Market -29.28 90.39 99.97 -9.58 -26.75 -29.27 2.52
Consumer 19.60 27.11 23.04 4.08 5.03 4.26 0.77
Finance 27.27 21.48 18.92 2.56 5.48 4.81 0.66
Value 42.82 1.52 0.78 0.73 0.58 0.30 0.28
Mining 32.25 1.54 0.63 0.91 0.47 0.20 0.28

Scenario Analysis: 1999-2000 Underperformance

Given property and casualty industry’s under-weighting of Market and Technology, it would experience its highest underperformance in an environment similar to the 1999 technology boom.  In this environment, industry’s systematic exposures would underperform the market by more than 10%:

Property and casualty industry
1999-2000: Stress test of underperformance due to Property and Casualty Industry’s Portfolio Factor Exposures

Below are the main contributors to this underperformance, in percent:

Factor Return Portfolio Exposure Benchmark Exposure Relative Exposure Portfolio Return Benchmark Return Relative Return
Technology 53.04 9.31 19.10 -9.79 4.30 8.95 -4.66
Market 29.23 90.39 99.97 -9.58 26.22 29.22 -3.00
Size -18.83 13.32 -1.01 14.33 -2.63 0.20 -2.83
Consumer -16.57 27.11 23.04 4.08 -4.72 -4.02 -0.70
Finance -20.59 21.48 18.92 2.56 -4.54 -4.01 -0.54
Energy 14.38 3.93 5.67 -1.74 0.62 0.90 -0.27
FX 6.84 -3.74 -1.19 -2.55 -0.25 -0.08 -0.17
Value -14.04 1.52 0.78 0.73 -0.17 -0.09 -0.08
Mining -8.54 1.54 0.63 0.91 -0.08 -0.03 -0.05
Communications 0.52 1.30 2.06 -0.76 0.02 0.04 -0.01

Conclusions

  • There is factor (systematic/market) crowding of property and casualty insurance companies’ long U.S. equity portfolios.
  • The main sources of systematic crowding are short (underweight) exposures to Market (Beta), Technology, and Health.
  • Since year-end 2013, factor exposures have cost the property and casualty industry over 4%, more than $12 billion, in underperformance.
  • For some portfolios, this may be a conscious risk management decision; for others, it is a costly oversight.
  • By managing its exposures in recent quarters, the industry would have generated billions in additional returns.

Previous article Short Selling: Lies, Damned Lies, And Statistics
Next article What Borders Mean To Europe
AlphaBetaWorks provides risk management, skill evaluation, and predictive performance analytics. Developed by finance and technology veterans, our proprietary platform combines the latest advances in financial risk modeling, data processing, and statistical analysis. Our Risk Analytics are more robust than alternatives and our Skill Analytics are predictive. Risk Analytics AlphaBetaWorks pinpoints risks missed by other offerings and delivers unique insights. AlphaBetaWorks Risk Analytics were developed by investment professionals seeking usability and a deeper understanding of portfolio exposures. Predictive Performance Analytics Starting with robust, proprietary risk models, AlphaBetaWorks adds layers of attribution and statistical analysis. Our Skill Analytics describe a multitude of specific skills that are strongly predictive of future returns for any fund, manager, or analyst with a sufficient sample of investment history. The AlphaBetaWorks Advantage Our Risk and Performance Analytics provide unique insights: For portfolio managers, we identify overlooked exposures, hidden risk clusters, and crowded bets. Managers can focus on risks in areas where they have proven ability to generate excess returns and avoid undesired risks in areas where they do not. For fund allocators, we identify the skills, crowding, and hidden portfolio bets of individual funds and portfolios of funds. Allocators can identify differentiated and skilled managers that are deploying capital in areas of proven expertise – and more importantly, those that are not. Background As finance professionals, we spent the last decade focused on fundamental investment analysis and the study of great (and seemingly great) investment managers. We asked of ourselves: Where are the unintended risks in a portfolio? What is the chance that a manager possesses true investment skill and was not just lucky? Does investment skill persist and is past skill a predictor of future results? There was no product, service, or technology that rigorously and consistently answered these questions. With decades of fundamental investment analysis, risk management, mathematics, and technology expertise, AlphaBetaWorks professionals have developed risk and skill analytics to address these and related questions.

No posts to display