Smart Beta Strategies for Global REITs Presentation ARES 2015

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SMART BETA STRATEGIES FOR REIT MUTUAL FUNDS Alex Moss, Consilia Capital Kieran Farrelly, The Townsend Group American Real Estate Society Conference Fort Myers , Florida April 2015

Transcript of Smart Beta Strategies for Global REITs Presentation ARES 2015

Page 1: Smart Beta Strategies for Global REITs  Presentation ARES 2015

SMART BETA STRATEGIES FOR REIT MUTUAL FUNDS

Alex Moss, Consilia Capital Kieran Farrelly, The Townsend Group

American Real Estate Society Conference Fort Myers , Florida

April 2015

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CONTENTS

• Background

• Purpose of the Study

• Data

• Methodology

• Results

• Conclusions and Next Steps

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BACKGROUND – KEY POINTS

• Post GFC, there has been a change in emphasis on the factors which influence investment decisions, affect performance, and determine asset allocation mixes, and product design, which are particularly relevant for real estate. Namely;

• Focus on income based assets in a low interest rate environment (real estate)

• Increased emphasis placed on liquidity (REITs*)

• Interest in combining asset types for specific solutions ( listed/unlisted for DC schemes)

• Emphasis on diversifying away equity and bond market risk (low correlation “alternative” buckets)

• Greater use of maximum drawdown as a key risk measure (DC funds )

• Growing acceptance of certain Smart Beta strategies (active management at passive cost)

*For simplicity the term REITs is used to describe all global listed real estate markets in this paper.

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BACKGROUND –KEY QUESTIONS

• Against this background, what Smart Beta strategies can be developed to provide the

investment solutions and risk/return profiles currently required by asset allocators?

• Is it possible to devise automated trading strategies (with a low turnover) which will enhance performance?

• Are there likely to be more Smart Beta products for REITs ? Currently we are aware of the Kempen Fundamental Index strategy and the Dow Jones Townsend Core REIT Index.

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BACKGROUND - DOW JONES TOWNSEND CORE US REIT INDEX

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• This Index aims to measure the performance of a basket of securities that could serve as a public-market analog for privately-held institutional “core” real estate investments

• To be eligible , a company must be both an equity owner and operator of commercial and/or residential real estate and meet minimum requirements for size and liquidity

• Specifically excluded are companies invested in the following property types: Factory Outlets, Hotels, Manufactured Homes, Mixed Industrial/Office and Suburban Office

26.0%

14.6%

18.0%

9.9%

22.7%

15.4% 17.7%

9.3%

1-year 3-year 5-year 10-year

Annualized Total Return - Gross of fees as of end of February 2015

Dow Jones Townsend Core U.S. REIT Index MSCI US REIT Index Total Return

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PURPOSE OF THE STUDY

In this study we are interested in discovering whether the free float market capitalisation weighted global benchmark would have consistently underperformed a Smart Beta strategy utilising the following factors :

1) Gross Assets

2) Equal Weighting

3) Gearing - Loan to Value ( Low and High) - EW

4) Valuation - Price to Book Value (Low and High) - EW

5) Size – Gross Assets (Small and Large) - EW

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CAVEATS

• No transaction costs are taken into account

• Portfolios are only rebalanced at calendar year ends and then held for the next 12 month period

• No constraints such as minimum liquidity , maximum number of portfolio constituents etc have been applied

• No account has been taken of resultant regional weightings

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DATA

• EPRA Global Developed Index constituents

• COMPUSTAT for fundamental data

• Bloomberg and CRSP for share price and total returns data

• Frequency: Annual

• Currency: US$ (Unhedged)

• Return: Total Return

• Period: 2004-2014

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METHODOLOGY

• Key metrics used: Loan to Value (LTV) , Gross Assets (GA), Price to Book Value (PBV)

• Establish benchmark constituents on an annual basis – this is the initial selection criteria

• Determine annual returns for all constituents

• Determine fundamental data (LTV, GA, PBV) for all benchmark constituents

• Sort by quartile (if appropriate)

• Apply weighting criteria (EW, Gross Assets)

• Calibrate portfolio annual return

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RESULTS – GROSS ASSETS

2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014

FTSE EPRA/NAREIT Developed Index TR 32.13% 15.25% 41.93% -7.20% -47.39% 37.55% 20.08% -5.65% 28.99% 4.31% 15.72%

Total Asset Weighted 38.04% 17.21% 43.70% -9.12% -47.61% 80.66% 24.02% -9.37% 30.94% 13.56% 16.97%

Smart Beta Relative 5.91% 1.96% 1.77% -1.92% -0.22% 43.11% 3.95% -3.72% 1.95% 9.26% 1.25%

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RESULTS – EW

2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014

FTSE EPRA/NAREIT Developed Index TR 32.13% 15.25% 41.93% -7.20% -47.39% 37.55% 20.08% -5.65% 28.99% 4.31% 15.72%

Equal Weight 39.20% 17.27% 44.24% -8.49% -44.10% 60.57% 27.47% -7.90% 30.02% 11.91% 16.40%

Smart Beta Relative 7.08% 2.02% 2.31% -1.30% 3.29% 23.02% 7.39% -2.24% 1.03% 7.60% 0.68%

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RESULTS – GEARING

2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014

FTSE EPRA/NAREIT Developed Index TR 32.13% 15.25% 41.93% -7.20% -47.39% 37.55% 20.08% -5.65% 28.99% 4.31% 15.72%

Equal Weight Low LTV Quartile 40.56% 26.59% 47.75% -7.01% -47.59% 83.98% 13.12% -13.62% 28.07% 11.30% 11.07%

Smart Beta Relative 8.43% 11.34% 5.82% 0.19% -0.20% 46.43% -6.96% -7.97% -0.91% 6.99% -4.65%

2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014

FTSE EPRA/NAREIT Developed Index TR 32.13% 15.25% 41.93% -7.20% -47.39% 37.55% 20.08% -5.65% 28.99% 4.31% 15.72%

Equal Weight High LTV Quartile 37.72% 16.70% 46.62% -17.48% -42.07% 56.59% 42.95% -2.82% 30.12% 7.40% 23.09%

Smart Beta Relative 5.59% 1.45% 4.69% -10.28% 5.32% 19.05% 22.88% 2.83% 1.13% 3.10% 7.37%

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RESULTS- VALUATION

2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014

FTSE EPRA/NAREIT Developed Index TR 32.13% 15.25% 41.93% -7.20% -47.39% 37.55% 20.08% -5.65% 28.99% 4.31% 15.72%

Equal Weight Low BTM Quartile 35.21% 20.72% 39.48% -14.59% -34.29% 28.39% 29.85% -0.85% 25.05% 5.31% 25.94%

Smart Beta Relative 3.08% 5.47% -2.46% -7.39% 13.10% -9.15% 9.78% 4.80% -3.93% 1.01% 10.22%

2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014

FTSE EPRA/NAREIT Developed Index TR 32.13% 15.25% 41.93% -7.20% -47.39% 37.55% 20.08% -5.65% 28.99% 4.31% 15.72%

Equal Weight High BTM Quartile 44.41% 14.46% 46.29% -2.85% -46.06% 117.51% 37.63% -7.41% 28.06% 16.45% 9.91%

Smart Beta Relative 12.28% -0.79% 4.36% 4.35% 1.32% 79.96% 17.56% -1.76% -0.93% 12.14% -5.81%

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RESULTS – GROSS SIZE

2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014

FTSE EPRA/NAREIT Developed Index TR 32.13% 15.25% 41.93% -7.20% -47.39% 37.55% 20.08% -5.65% 28.99% 4.31% 15.72%

Equal Weight Low Total Assets Quartile 37.97% 26.16% 42.30% -3.66% -40.23% 50.27% 23.95% -8.17% 30.95% 10.17% 16.85%

Smart Beta Relative 5.84% 10.91% 0.37% 3.54% 7.16% 12.73% 3.88% -2.52% 1.96% 5.86% 1.13%

2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014

FTSE EPRA/NAREIT Developed Index TR 32.13% 15.25% 41.93% -7.20% -47.39% 37.55% 20.08% -5.65% 28.99% 4.31% 15.72%

Equal Weight Hightotal Assets Quartile 38.39% 16.62% 40.68% -13.84% -49.77% 76.34% 22.49% -7.80% 28.20% 12.73% 17.16%

Smart Beta Relative 6.27% 1.37% -1.26% -6.65% -2.38% 38.79% 2.41% -2.15% -0.79% 8.42% 1.44%

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RESULTS – OVER TOTAL PERIOD

Mean Geo Mean

FTSE EPRA/NAREIT Developed Index TR 12.34% 8.92%

Equal Weight 16.96% 13.03%

Total Asset Weighted 18.09% 13.20%

Equal Weight Low LTV Quartile 17.66% 12.48%

Equal Weight High LTV Quartile 18.08% 13.97%

Equal Weight Low BTM Quartile 14.57% 12.07%

Equal Weight High BTM Quartile 23.49% 17.25%

Equal Weight Low Total Assets Quartile 16.96% 13.72%

Equal Weight Hightotal Assets Quartile 16.47% 11.50%

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CONCLUSIONS AND NEXT STEPS

• Promising initial results

• Simple Smart Beta strategies can create material performance differentials vs the index

• Next Steps:

• Make use of higher frequency and longer time series data

• Explore additional strategies – fundamental and technical

• Incorporate additional filters such as liquidity and regional constraints

• Include transaction costs – measure ‘real’ investor level returns

• Assess regional level strategies

• Factor model, risk and diversification potential (within real estate and multi-asset levels) analysis

• Explore whether there is a cyclical dimension to the various strategies which is predictable

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