A SIMULATION APPROACH ERES 2015, 26 th June 2015 Charles Ostroumoff, Mark Clacy-Jones, Malcolm Frodsham

A SIMULATION APPROACH

ERES 2015, 26th June 2015Charles Ostroumoff, Mark Clacy-Jones, Malcolm Frodsham

Agenda

1. IPD Property Futures pricing2. IPD UK Index analysis3. Simulation

“The object of our analysis is, not to provide a machine, or a method of blind manipulation which will furnish an infallible answer, but to

provide ourselves with an organised and orderly method of thinking out particular problems: and, after we have reached a provisional

conclusion by isolating the complicating factors one by one, we then have to go back on ourselves and allow, as well as we can, for the

probable interactions of the factors amongst themselves.”JM Keynes

Risk Premium

FuturesPrice

TR Estimate

IPD Index Level

IPD Property Futures Pricing

August

September

October

November

December

January

FebruaryMarch April

MayJune

July

August

September

October

November

December

0.00%

2.00%

4.00%

6.00%

8.00%

10.00%

12.00%

14.00%

16.00%

18.00%

20.00%

Cal 14 Futures Pricing YTD IPD UK Monthly Property Index YTD IPD UK Annual Property Index

2013 2014

2014 Calendar Year

Basis Risk

• This Paper is focused on the tracking error (creep) between the IPD Monthly and IPD Annual Indices

• There also exists the tracking error (basis risk) between the total return of a portfolio and the total return of the IPD Index

• Our aim is to devise a simulation model to quantify this “basis risk” and increase the accuracy of our short term forecasting

Systematic and idiosyncratic risk• Property has the highest divergence of return i.e. the highest level of

standard deviation of excess return relative to its benchmark – For 95% of the variation in returns to be explained by the market, over

200 properties required*• c.f. Equities 45%

– To reduce the tracking error / basis risk to less than 1% requires an exponential increase*

• ‘Portfolio Structure’ & ‘Asset Quality’ – 2 Key Factors– Difficult to assemble a market-tracking portfolio at reasonable cost– Different segments reveal immensely different lot sizes and require

immensely different capital investment• Can price smaller players out of the market (Byrne & Lee 2001)

– Some properties in some segments experience higher variations in return than others

• Equally weighted portfolios do not exist

8

• Why does the IPD UK Monthly Property Index not more closely track the IPD UK Annual Property Index?

• Sampling Issue?– Samples should be large enough & diverse enough to not be

biased• If sample is unbiased tracking error is a function of

individual asset returns & number of assets• Hypothesis:

Tracking error between the two indexes must be due to structural differences

Hypothesis

9

• Indexes are samples of assets• IPD Index samples should be materially free

from bias– Multiple portfolios– Heterogeneous assets– Assets valued by multiple valuation firms– Diffused client influence

Index composition - theory

10

Size & structure of the uk commercial market

39%

41%

11%

9%

Retail

Office

Industrial

Other

Source: IPF – The Size & Structure of the UK Property Market

Retail £150bnOffice £157bnIndustrial £43bnOther £35bn

Investable Universe£385bn*

*End 2013

11

IPD UK Annual & monthly index composition

Source: MSCI

*End 2013

48%

27%

16%

9%

RetailOfficeIndustrialOther

45%

31%

18%

6%

Retail

Office

Industrial

Other

IPD UK Annual Property Index IPD UK Monthly Property Index

12

IPD UK Annual & monthly index composition

IPD UK Annual Property Index IPD UK Monthly Property Index

Capital Value (£m) % CV No. Props No. Funds No. Valuers

Max Prop Dominance

(% CV)

Max Fund Dominance

(% CV)

Max Valuer Dominance

(% CV)Capital Value

(m) % CV No. Props No. Funds No. ValuersMax Prop

Dominance (% CV)

Max Fund Dominance

(% CV)

Max Valuer Dominance

(% CV)

Std Retail South East 17,507 9.8 1,327 192 34 2.3 11.8 31.2 3,056 7.1 353 42 16 3.7 10.7 49.9

Standard Retail Rest UK 11,221 6.3 1,369 188 31 0.7 4.1 37.6 3,216 7.4 532 45 15 2.3 7.9 41.6

Shopping Centre 26,198 14.6 275 102 18 8.3 32.8 47.4 2,402 5.5 88 33 9 7.2 13.8 43.3

Retail Warehouse 26,677 14.9 1,232 188 34 1.3 6.2 39.2 9,307 21.5 484 47 17 3.8 16.9 52.0

Office City 7,459 4.2 237 104 22 4.4 14.4 51.8 1,869 4.3 77 31 12 4.7 7.3 39.3

Office West End & Mid Town 22,513 12.6 851 131 24 1.9 11.4 51.4 4,655 10.8 136 39 13 4.0 21.3 55.5

Office Rest South East 13,755 7.7 914 184 32 2.6 7.1 41.8 5,178 12.0 367 51 15 2.6 11.0 39.9

Office Rest UK 7,073 4.0 624 159 26 2.3 5.3 41.6 2,579 6.0 241 40 12 3.1 13.8 45.6

Industrial South Eastern 18,498 10.3 1,385 190 31 5.1 8.8 39.0 4,540 10.5 432 46 15 1.9 7.5 42.1

Industrial Rest UK 11,066 6.2 1,577 191 35 1.6 5.1 30.8 3,810 8.8 470 45 15 2.9 10.3 40.0

Other 16,899 9.4 2,304 200 37 1.6 9.5 20.1 2,671 6.2 299 36 9 3.3 9.2 42.6

Retail 81,602 45.6 4,203 234 38 2.7 10.8 33.6 17,981 41.5 1,457 50 18 2.0 8.8 48.6

Office 50,800 28.4 2,626 220 36 0.8 7.6 47.5 14,282 33.0 821 53 17 1.3 7.5 45.8

Industrial 29,564 16.5 2,962 209 36 3.2 5.5 36.0 8,350 19.3 902 49 16 1.3 6.3 41.1

All Property 178,865 100.0 12,095 288 48 1.2 4.8 36.2 43,283 100.0 3,479 55 20 0.8 7.8 45.7

Distribution of asset total returns 2014

13

Distribution of asset returns has profile which is indistinguishable between the two index frequencies

Distribution of portfolio total returns 2014

14

15

Index tracking errors

Annual Index tends to underperform in years of higher return

Average difference is 0.2 percentage points

Tracking error is 1.3 (standard deviation of differences)

• No difference to data collection or index construction between Annual & Monthly Indexes

• IPD UK Monthly Property Index “frozen” so historic data corrections not included but may be corrected in time for IPD UK Annual Property Index

(Though this is not the case at segment level which is unfrozen)

• Valuations should in theory all be done as at year-end so no extra information should be available for inclusion in annual valuations

Index methodology differences

16

Index tracking errors, Evolution by year

17

Tracking errors tend to grow in a relatively linear fashion throughout the year

1993

1994

2007

18

Segment weight differentials change throughout year

Difference between segment weight in monthly & annual indexes changes month on month, as in this 2014 example

Annual index weights are only known after year end

Asset Quality differs between indexes

19

In most segments equivalent yield is lower in the annual index suggesting assets are on average better quality in the annual index

20

Occupation levels differ between indexes

Monthly Index has marginally higher void rates than the Annual Index and has a higher level of over-renting

21

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Notice and disclaimer

Simulation Drivers

1. Income & occupancy at start of the simulation

2. Yield levels by segment, asset quality and income security

3. Rental growth by segment and asset quality4. Lease events by segment and asset quality5. Yield changes by segment, asset quality and

income security

RENTAL GROWTH TRENDS VARY BY ASSET QUALITYYear to Q3 2014, %

23

Low* asset quality High* asset quality

Standard retails:

Central London 9.5 7.4

South east -0.1 1.3

Rest of UK -1.5 -0.1

Shopping Centres -0.9 0.3

Retail Warehouses 0.0 0.2

Standard offices:

City 13.1 6.6

West End 8.3 10.6

South east 2.8 6.4

Rest of UK 1.0 0.9

Office Parks 3.1 0.1

Standard Industrials

South east 2.6 3.6

Rest of UK 1.6 1.7

Distribution Warehouses 1.7 1.8

VALUATION CAP RATES & CASH FLOW ASSUMPTIONSMAJOR REGIONAL OFFICES, Q2 2014

Yield - by term certain (rack-rented)

Asset Quality Rent per sq ft National / Strong Covenant Local / Weak Covenant

Vacant 2015-'18 2019-'23 2023+ 2015-'18 2019-'23 2023+

Grade A New £30.00 9.25% 8.50% 6.50% 5.75% 9.00% 7.75% 7.00%

Grade A Refurbished £22.50 9.75% 9.00% 7.00% 6.25% 9.50% 8.00% 7.25%

Second Hand Good £18.00 11.00% 10.00% 7.75% 7.00% 10.50% 8.25% 7.50%

SIMULATION OF HIGH / LOW QUALITY ASSET RETURNS

Yield - by term certain(rack-rented)

Asset Quality Rent per sq ft National / Strong Covenant

Vacant 2015-'18 2019-'23 2023+

Grade A New £30.00 9.25% 8.50% 6.50% 5.75%

Capital value £32m £35m £46m £52m


Asset Quality Rent per sq ft Local / Weak Covenant

Vacant 2015-'18 2019-'23 2023+

Second Hand Good £18.00 11.00% 10.50% 8.25% 7.50%




Vacant 2015-'18 2019-'23 2023+

Grade A New £33.00 9.00% 8.25% 6.25% 5.50%


Change, % 16% 14% 15% 15%



Vacant 2015-'18 2019-'23 2023+

Second Hand Good £19.80 10.75% 10.25% 8.00% 7.25%


Change, % 13% 12% 14% 13%

4 HIGH QUALITY ASSETS:DIFFERENT LEVELS OF INCOME SECURITY

VALU

E YE

AR 1

VALU

E YE

AR 2

4 LOW QUALITY ASSETS:DIFFERENT LEVELS OF INCOME SECURITY

Change in asset capital values depends on rental growth and yield changes

MARKETAVERAGE

14%

+10% +10%

LOW QUALITY AVERAGE 13%HIGH QUALITY AVERAGE 15%

Simulating Market Returns

1. There is an asset quality / income security ‘factor’ to market segment returns– In other words the IPD Monthly Index has a

different exposure by type & region and to income security and asset quality factors.

2. Fund Managers should take into account the asset quality and income security of the IPD Index when pricing futures contracts

SIMULATION OF MARKET RETURNS



Vacant 2015-'18 2019-'23 2023+

Grade A New £30.00 9.25% 8.50% 6.50% 5.75%

Long-lease LettingNon-

renewal RenewalTenant

bust

Year 0Rent Passing0 £30.00 Vacant £30.00 £30.00 £30.00

Yield0 5.75% 9.25% 8.50% 8.50% 5.75%Capital Value0 £52m £32m £35m £35m £52m

Year 1Rent Passing1 £30.00 £30.00 Vacant £30.00 Vacant


Change, % -11.5% 62.5% -8.6% 48.6% -38.5%



Vacant 2015-'18 2019-'23 2023+

Second Hand Good £18.00 11.00% 10.50% 8.25% 7.50%

Long-lease LettingNon-

renewal RenewalTenant

bust

Year 0Rent Passing0 £18.00 Vacant £18.00 £18.00 £18.00


Year 1Rent Passing1 £18.00 £18.00 Vacant £18.00 Vacant


Change, % -8.3% 50.0% -5.9% 41.2% -33.3%

MARKETAVERAGE 15%

5 HIGH QUALITY ASSETS 5 LOW QUALITY ASSETS

LEASE EVENT-> LEASE EVENT->

MARKET AVERAGE 17%

Simulating Market Returns

1. The market average capital value change depends upon:

1. Initial income and occupancy characteristics2. Rental value and yield changes3. Lease ‘events’ (lettings, vacancies) through the year

2. The spread of asset capital value changes depends on valuation yields by asset quality

3. The distribution of asset capital value changes depends on lease event probabilities

Few of these inputs are known

Disclaimer: While every effort has been made to ensure that the data quoted and used for the research behind this document is reliable, there is no guarantee that it is correct, and Real Estate Strategies Limited can accept no liability whatsoever in respect of any errors or omissions. This document is a piece of economic research and is not intended to constitute investment advice, nor to soliciting dealing in securities or investments.

Charles OstrumoffArca PRM20 Hanover StreetLondon, W1S 1YR

Mark Clacy-JonesMSCITen Bishops SquareLondon, E1 6EG

Malcolm FrodshamRESRex House4-12 Regents StreetLondon, SW1Y 4PE

Documents

A SIMULATION APPROACH ERES 2015, 26 th June 2015 Charles Ostroumoff, Mark Clacy-Jones, Malcolm Frodsham