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Investment Valuations

Investment Valuations. Flexi-leases. Valuation of flexi-leases. Greater uncertainty requires valuers to consider probability of various outcomes: Will tenant renew short lease? Will break be exercised? Will there be a rent void, how long will it be? What will terms of new lease be?

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Investment Valuations

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  1. Investment Valuations

  2. Flexi-leases

  3. Valuation of flexi-leases • Greater uncertainty requires valuers to consider probability of various outcomes: • Will tenant renew short lease? • Will break be exercised? • Will there be a rent void, how long will it be? • What will terms of new lease be? • What will the covenant strength of the tenant be? • Financial impact will depend on: • Length of lease • Terms of break • State of market • Valuation issues: • Comparables harder to find • Temptation to focus on worst-case scenario • Risk of double-counting risk • Valuation techniques: • ARY • Yield adjustment • Insert rent void • DCF • Short-cut • Full • Modelling, probability analysis…

  4. Valuation of flexi-leases- Yield adjustment • A modern office property has just been let on a 15-year FRI lease at a market rent of £50,000 per annum with five-year rent reviews. There is a break option in the tenant’s favour in year five, just before the rent review (to prevent the tenant from using it as a bargaining tool). Comparable evidence suggests that rack-rented office investments let on 15-year FRI leases with five-year rent reviews to market rent sell at prices that generate initial yields of around 7%.

  5. Valuation of flexi-leases- Rent void using ARY On a standard lease a rent of £50,000 per annum and a yield of 7.5% would produce a valuation of £666,667

  6. Valuation of flexi-leases- Rent void using DCF • Long-term gilts currently yield 8% and a typical property risk premium is 2% • Assuming a target rate of return of 10% and an ARY of 7.5%, this implies a growth rate of 2.88% per annum

  7. Over-rented property

  8. Over-rented property • Valuation issues • Properties let at rent > market rent • Includes properties let at ‘headline’ rents • Valuation techniques • ARY • Value rent passing in perpetuity at an ‘adjusted’ ARY if the lease is long contains upward-only rent reviews and no break clause • Because overage is more risky, use a modified core and top-slice (layer) method • DCF • Allows explicit estimation of length of void period

  9. Over-rented property- modified core and top-slice Value a property let four years ago at a rent of £250,000 per annum on a 15-year lease with five-year upward-only rent reviews. The current market rent is £200,000 per annum. Comparable properties have recently sold for yields averaging 6%. [a] Gilt yield plus a 2% risk premium But…

  10. Over-rented property- modified core and top-slice • There is a lack of evidence on which to base the overage yield • No attempt has been made to estimate the length of time that the property will remain over-rented. Many valuers capitalise the overage for the whole period that the tenant is contracted to pay it, but the market rent may overtake the contract rent before the end of the lease and part of the overage is capitalised twice – the property will be over-valued

  11. Over-rented property- Short-cut DCF Using a growth rate of 5.57% per annum (implied from ARY of 6% and target rate of 11%) the market rent will grow to the following amounts at the next two rent reviews: £200,000 x (1+0.0557)1 = £211,140 £200,000 x (1+0.0557)6 = £278,868 So market rent overtakes contract rent between first and second rent reviews. The growth-explicit short-cut DCF valuation is as follows… The valuation is lower than the layer approach above because double-counting has not occurred

  12. Over-rented property- Short-cut DCF IPD provide time series over 1, 5 and 10 years epochs by sector, location & type • Drawback of growth-explicit DCF is the lack of evidence to support rental growth rate • Target rate may need to be adjusted to reflect covenant strength of tenant, length of remaining lease term and extent of overage • In between reviews rent is only subject to tenant (default) risk and if the contract rent is very high in comparison to market rent for long periods (e.g. beyond the first rent review) then it is exposed to a greater degree of tenant risk. As such it may be more characteristic of a corporate bond-type investment issued by the tenant

  13. Valuation uncertainty

  14. Introduction • A valuation is not a permanent part of the property • Analysis of market data only suggests what happened in the past and it is for the valuer to interpret these data to assess current market value • Values can be difficult to assess due to • Heterogeneity of property • Paucity of market information • Large number of inputs / assumptions • Disparity in valuations of the same property is valuation variance • Discrepancy between a valuation and exchange price is valuation inaccuracy • Valuation uncertainty acknowledges the fact that valuation variance and inaccuracy are inevitable and influenced by type and location of property

  15. Valuation accuracy • RICS / IPD annual study… • Ave difference of 10.9% (9.6% when weighted by sale price) between sale prices and ‘adjusted’ valuations in IPD UK Annual Databank • 63.8% within +/-10% • 88.5% within +/-20% • 75% transaction prices > valuation (ave 6% higher) Why? • MV definition precludes bids by special purchasers • Vendors may selectively dispose of properties • Vendors actively present assets to market • Growth assumptions in analysis not picking up true picture • Valuers conservative and backward-looking • IPD contains prime properties so evidence more consistent; non-prime may include more variation and more incentives…

  16. Valuation variance • How much variance? • 9.53% from the mean valuation of each property (Hutchison et al, 1996) • Why? • Client pressure, esp. mortgage lending vals (Kinnard et al, 1997) • Knowledge of the asking price or pending sale price (Gallimore and Wolverton, 1997) • ‘Behavioural characteristics’ of the valuer (Bretten and Wyatt, 2001) • Solution? • Red Book now contains stricter guidelines regarding • external pressure • QA • Conflicts of interest

  17. Variance and themargin of error • A means of establishing whether a valuer has been negligent? • Singer & Friedlander v John D Wood and Company, 1977: +/-10% around the subsequent transaction price (or some other notion of ‘correct’ market value) would be permissible. • In 38 High Court valuation negligence cases between 1977 and 1998 • +/-10% (26.1%) • between 10% and 14.99% (30.4%). • Why? (Crosby et al, 1998) • Expert witnesses are unfit to present themselves as ‘experts’ • The margin of error principle and the ‘brackets’ applied are too onerous • Expert witnesses are being ‘influenced’ to produce a valuation to suit their client’s need • But how is the ‘correct’ valuation reached? • The courts fail to examine the processes involved and focus instead on the outcome

  18. Valuation uncertainty • Current reporting (RICS GN5): • Single estimate plus comment on • cause of the uncertainty and the degree to which it is reflected in the reported valuation • robustness of the valuation, perhaps noting the availability and relevance of comparable market evidence • Potential quantitative measures: • Sensitivity analysis • Scenario testing and discrete probability modelling • Simulation and continuous probability modelling

  19. Sensitivity analysis • Examines the degree of change in the valuation caused by a pre-determined change in an input variable • One variable at a time • Usually 10-20% either side of expected value but can be more realistic • Look at equivalent yield spreadsheet… • £200k p.a. contract rent • £250k p.a. market rent • 7.96% equivalent yield • Can see which inputs have greatest impact • Usually the ARY • Usually focus on downside shifts

  20. Key Variables Valuations

  21. Sensitivity Analysis Sensitivity analysis of reversionary freehold valuation (ARY equivalent yield)

  22. Sensitivity Analysis Sensitivity analysis of reversionary freehold valuation (Short-cut DCF)

  23. Scenario testing • Examines impact of simultaneous changes in input variables • Pessimistic • Realistic • Optimistic • Look at rack-rented FH valuation using full DCF… • £250k p.a. MR • 10% TRR • 8% ARY/Exit yield • 2.33% p.a. implied growth rate • Use ‘scenarios’ option on the ‘tools’ menu… • As with sensitivity analysis, no real sense of probability

  24. Scenario testing • Discrete probabilities • Subjectively derived • Not a proper measure of variation (variance, standard deviation) • Simplistic way of dealing with uncertainty • Table shows two properties with the same weighted ave valuation but…

  25. Continuous probability modelling • Look at central tendency (mean, median, mode) and variation (variance, standard deviation) in valuations (dependent variable) • Ask 50 valuers to value two properties: • Property 1: mean = £3.2m, sd = £0.5m • Property 2: mean = £3.5m, sd = £1m • Coefficient of variation = sd/mean (a measure of spread relative to the mean) • Property 1: CoV = 15.63% • Property 2: CoV = 28.57% • Property 1 is less volatile by sd and CoV measures • Need more data and need to assume valuations are normally distributed • But this isn’t what happens in practice – instead we have one valuation but variations in inputs…

  26. Simulation • How does variation in valuation inputs (the independent variables) affect the valuation? • Use simulation program to • assign probabilities to inputs • run simulations of combinations of input values based on their probability of occurrence • produce a probability distribution of valuation figure (with stats that summarise this distribution: mean, sd, confidence range) • Involves a series of steps • Build valuation model and identify key input variables… • Short-cut DCF with and without a void at a break in year 5 • ARY/Exit yield, MR and void period

  27. Simulation • Ascribe probability distributions to key inputs • Break void: triangular distribution (most likely = 0.25 yrs, min = 0 yrs, max = 1.5 yrs) • MR: normal distribution (mean = £50k, sd = £5k) • ARY: triangular distribution (most likely = 8%, min = 6.5%, max = 9%)

  28. Simulation • Construct correlation matrix… • Run simulation • Distribution of valuation outcomes generated by sampling combinations of input values selected according to their probabilities of occurrence • Output

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