ManchesterLondon Budapest CopenhagenGlasgow Birmingham StockholmVienna WarsawMilanRomeParisLyonLille Marseille AVERAGEHSR BarcelonaMadridBerlinPrague AmsterdamBrusselsLisbon HamburgMunich Frankfurt Cologne AVERAGEOFFICE
DublinMadrid LondonParis Barcelona Stockholm FrankfurtLisbonMilan MunichBerlin Glasgow Budapest Hamburg Warsaw BirminghamLyon AmsterdamPragueRome Copenhagen Cologne ManchesterVienna Brussels MarseilleLille
Exhibit 5: European High Street Markets—Maximum Drawdown
In times of severe property value declines, high street retail has proved defensive on average versus o;ce.
Sources: PMA, Hines Research
Note: Data are as of 3Q2017Q for the trailing 20 years. Quarterly price returns in percentages were calculated from local currency. Property
prices for the 27 high street retail metro markets covered by Hines were averaged by quarter and then used to create an independent average
high street retail (“Average HSR”) and o;ce return series. The maximum drawdown for each market and for each average series was then calculated. This is a measure designed to quantify an asset class’s performance during times of severe market stress. It was calculated as the largest
peak-to-trough decline su;ered over any given period. The maximum drawdown for each market generally occurred over the 2001–2010
period, with German markets su;ering their largest declines in the early part of the period and other markets su;ering during the latter half.
Because the calculation was market-specific, start and end dates may di;er from metro to metro.
Exhibit 6: European O;ce Markets—Beta Versus European Average
Several high-profile European o;ce markets have higher beta than others.
Sources: PMA, Hines Research
Notes: Data are as of 2Q2017 for the trailing 20 years. Quarterly o;ce-sector price returns in percentages were calculated from local currency.
Property prices for the 27 metro markets for which Hines provides data for both high street retail and o;ce were averaged by quarter and then
used to create an independent average o;ce return series. The beta was then calculated for each market’s quarterly return compared to the
average o;ce return series. The seven markets highlighted have betas greater than 1.0.
highlighted given four scenarios: (1) 100% allocation
to of;ce, (2) of;ce plus a 10% allocation to high street
retail in the local market, ( 3) of;ce plus a 20% allocation to high street retail in the local market, and
( 4) equal weighting of the local of;ce and high street
retail markets. Exhibit 8 employs proprietary forward-looking ;ve-year forecast returns for each metro
across the two property types paired with covariance
and volatility assumptions based on trailing data.
Across all seven metros, portfolio volatility (Exhibit
9) and risk-adjusted returns (Exhibit 10) show improvement relative to the 100% of;ce portfolio, reinforcing the higher allocation to retail. The scale of improvement from scenario to scenario is also relatively
similar across the seven metros, with exceptions for
London and Frankfurt on the risk-adjusted measure
(Exhibit 10). London’s relatively ;at improvement is
driven by price forecasts that currently favor of;ce