Presentation is loading. Please wait.

Presentation is loading. Please wait.

© Henley Business School 2008www.henley.reading.ac.uk School of Real Estate & Planning Optimal Portfolio Allocation using TLI Tommaso Gabrieli University.

Similar presentations


Presentation on theme: "© Henley Business School 2008www.henley.reading.ac.uk School of Real Estate & Planning Optimal Portfolio Allocation using TLI Tommaso Gabrieli University."— Presentation transcript:

1 © Henley Business School 2008www.henley.reading.ac.uk School of Real Estate & Planning Optimal Portfolio Allocation using TLI Tommaso Gabrieli University of Reading Davide Manstretta IPD

2 School of Real Estate & Planning Introduction Motivation –Property market returns (IPD) are based on Valuers’ appraisal –Vast literature argues that data underestimates true volatility (smoothing) –New IPD series Transaction-Linked Index (TLI) should represent true returns and correct for the problem Devaney and Martinez Diaz JPR 2011 Research Questions: –Is TLI series different form de-smoothed Valuers’ Based Index (VBI) series? –Implications for portfolio allocation? 2

3 School of Real Estate & Planning Agenda Introduction and Results Overview A little bit of theory: –Problem definition Empirical Results: –Differences between TLI and de-smoothed VBI –Portfolio Allocation analysis Conclusions Main Result –TLI and de-smoothed VBI are very different; strong implications for portfolio allocation 3

4 School of Real Estate & Planning TLI vs. VBI capital growth, QTLY 2002-2010 4

5 School of Real Estate & Planning Smoothing Assumptions: –Property Market Returns are Valuation Based May Lag Market Movements – Distorts Correlation May Be “Smoothed” – Understates the Volatility –“De-smoothing” Procedures Remove the Impact of Valuations in Data –Reported return is a blend of “true” and previous return De-smoothing: –R v t =  R v t-1 + (1-  )R t Therefore R t = {R v t -  R v t-1 } / (1-  ) where  is the “smoothing parameter” Vast literature: –Blundell and Ward (1987), Quan and Quigley (1991), Brown and Matysiak (2000), Geltner et al. (2002) and many others… 5

6 School of Real Estate & Planning TLI vs. De-smoothed TLIDes 0.8Des 0.65 Des 0.5Des 0.25 Des 0.1VBI St Dev6.415.28.86.55.14.74.5 AR10.20.10.30.40.60.70.76 Corr with TLI1 0.380.520.620.720.740.74 6

7 School of Real Estate & Planning TLI vs. De-smoothed 7

8 School of Real Estate & Planning TLI vs. De-smoothed (Q3 2002 – Q1 2007) TLIDes 0.8Des 0.65 Des 0.5Des 0.25 Des 0.1VBI St Dev4.805.12.82.01.41.31.2 AR1-0.34-0.4-0.3-0.10.30.50.6 Corr with TLI1.000.330.340.350.320.300.29 8

9 School of Real Estate & Planning TLI vs. De-smoothed (Q2 2007 – Q4 2010) TLIDes 0.8Des 0.65 Des 0.5Des 0.25 Des 0.1VBI St Dev 6.9522.7912.949.306.906.285.93 AR10.500.170.250.360.540.620.69 Corr with TLI1.000.420.560.680.800.840.84 9

10 School of Real Estate & Planning Optimal Portfolio with TLI 10

11 School of Real Estate & Planning Optimal Portfolio, TLI vs. VBI 11

12 School of Real Estate & Planning Optimal Portfolio, TLI vs. VBI (Q3 2002 – Q1 2007) 12

13 School of Real Estate & Planning Efficient Frontier 13

14 School of Real Estate & Planning Conclusion Findings –According to TLI, property is a very attractive asset class –TLI and De-smoothed VBI are very different, which is theoretically worrying... Extensions –Annual Data –Implied smoothing parameter 14

15 School of Real Estate & Planning Thank you for your attention Questions? Comments? 15


Download ppt "© Henley Business School 2008www.henley.reading.ac.uk School of Real Estate & Planning Optimal Portfolio Allocation using TLI Tommaso Gabrieli University."

Similar presentations


Ads by Google