Non-normal real estate return distributions by property type in the UK

Investment risk models with infinite variance provide a better description of distributions of individual property returns in the IPD UK database over the period 1981 to 2003 than normally distributed risk models. This finding mirrors results in the US and Australia using identical methodology. Real estate investment risk is heteroskedastic, but the characteristic exponent of the investment risk function is constant across time – yet it may vary by property type. Asset diversification is far less effective at reducing the impact of non‐systematic investment risk on real estate portfolios than in the case of assets with normally distributed investment risk. The results, therefore, indicate that multi‐risk factor portfolio allocation models based on measures of investment codependence from finite‐variance statistics are ineffective in the real estate context

The uncertainty of valuation

Valuation is often said to be “an art not a science” but this relates to the techniques employed to calculate value not to the underlying concept itself. Valuation is the process of estimating price in the market place. Yet, such an estimation will be affected by uncertainties. Uncertainty in the comparable information available; uncertainty in the current and future market conditions and uncertainty in the specific inputs for the subject property. These input uncertainties will translate into an uncertainty with the output figure, the valuation. The degree of the uncertainties will vary according to the level of market activity; the more active a market, the more credence will be given to the input information. In the UK at the moment the Royal Institution of Chartered Surveyors (RICS) is considering ways in which the uncertainty of the output figure, the valuation, can be conveyed to the use of the valuation, but as yet no definitive view has been taken apart from a single Guidance Note (GN5, RICS 2003) stressing the importance of recognising uncertainty in valuation but not proffering any particular solution. One of the major problems is that Valuation models (in the UK) are based upon comparable information and rely upon single inputs. They are not probability based, yet uncertainty is probability driven. In this paper, we discuss the issues underlying uncertainty in valuations and suggest a probability-based model (using Crystal Ball) to address the shortcomings of the current model.

Non-normal real estate return distributions by property type in the U.K.

Investment risk models with infinite variance provide a better description of distributions of individual property returns in the IPD database over the period 1981 to 2003 than Normally distributed risk models, which mirrors results in the U.S. and Australia using identical methodology. Real estate investment risk is heteroscedastic, but the Characteristic Exponent of the investment risk function is constant across time yet may vary by property type. Asset diversification is far less effective at reducing the impact of non-systematic investment risk on real estate portfolios than in the case of assets with Normally distributed investment risk. Multi-risk factor portfolio allocation models based on measures of investment codependence from finite-variance statistics are ineffectual in the real estate context.

Valuation accuracy: reconciling the timing of the valuation and sale

Carsberg (2002) suggested that the periodic valuation accuracy studies undertaken by, amongst others, IPD/Drivers Jonas (2003) should be undertaken every year and be sponsored by the RICS, which acts as the self-regulating body for valuations in the UK. This paper does not address the wider issues concerning the nature of properties which are sold and whether the sale prices are influenced by prior valuations, but considers solely the technical issues concerning the timing of the valuation and sales data. This study uses valuations and sales data from the Investment Property Databank UK Monthly Index to attempt to identify the date that sale data is divulged to valuers. This information will inform accuracy studies that use a cut-off date as to the closeness of valuations to sales completion date as a yardstick for excluding data from the analysis. It will also, assuming valuers are informed quickly of any agreed sales, help to determine the actual sale agreed date rather than the completion date, which includes a period of due diligence between when the sale is agreed and its completion. Valuations should be updated to this date, rather than the formal completion date, if a reliable measure of valuation accuracy is to be determined. An accuracy study is then undertaken using a variety of updating periods and the differences between the results are examined. The paper concludes that the sale only becomes known to valuers in the month prior to the sale taking place and that this assumes either that sales due diligence procedures are shortening or valuers are not told quickly of agreed sale prices. Studies that adopt a four-month cut-off date for any valuations compared to sales completion dates are over cautious, and this could be reduced to two months without compromising the data.

Influences on secured lending property valuations in the UK

A significant part of bank lending in the UK is secured on commercial property and valuations play an important part in this process. They are an integral part of risk management within the banking sector. It is therefore important that valuations are independent and objective and are used properly to ensure that secured lending is soundly based from the perspective of both lender and borrower. The purpose of this research is to examine objectivity and transparency in the valuation process for bank lending and to identify any influences which may undermine the process. A detailed analysis of 31 valuation negligence cases has been followed by two focus groups of lenders and valuers and also questionnaire surveys of commercial lenders and valuers. Many stakeholders exist, for example lenders, borrowers and brokers, who are able to influence the process in various ways. The strongest evidence of overt influence in the process comes from the method of valuer selection with borrowers and brokers seen to be heavily involved. There is some also some evidence of influence during the draft valuation process. A significant minority of valuers feel that inappropriate pressure is applied by borrowers and brokers yet there is no apparent part of the process that leads to this. The panel system employed by lenders is found to be a significant part of the system and merits further examination. The pressure felt by valuers needs more investigation along with the question of if and how the process could dispel such feelings. This is seen as particularly important in the context of bank regulation.

Benchmarking and valuation issues in measuring depreciation for European office markets

Purpose – The paper addresses the practical problems which emerge when attempting to apply longitudinal approaches to the assessment of property depreciation using valuation-based data. These problems relate to inconsistent valuation regimes and the difficulties in finding appropriate benchmarks. Design/methodology/approach – The paper adopts a case study of seven major office locations around Europe and attempts to determine ten-year rental value depreciation rates based on a longitudinal approach using IPD, CBRE and BNP Paribas datasets. Findings – The depreciation rates range from a 5 per cent PA depreciation rate in Frankfurt to a 2 per cent appreciation rate in Stockholm. The results are discussed in the context of the difficulties in applying this method with inconsistent data. Research limitations/implications – The paper has methodological implications for measuring property investment depreciation and provides an example of the problems in adopting theoretically sound approaches with inconsistent information. Practical implications – Valuations play an important role in performance measurement and cross border investment decision making and, therefore, knowledge of inconsistency of valuation practice aids decision making and informs any application of valuation-based data in the attainment of depreciation rates. Originality/value – The paper provides new insights into the use of property market valuation data in a cross-border context, insights that previously had been anecdotal and unproven in nature.

“Financial alchemy” or a zero sum game? Real estate finance, securitisation and the UK property market

Following the US model, the UK has seen considerable innovation in the funding, finance and procurement of real estate in the last decade. In the growing CMBS market asset backed securitisations have included $2.25billion secured on the Broadgate office development and issues secured on Canary Wharf and the Trafford Centre regional mall. Major occupiers (retailer Sainsbury’s, retail bank Abbey National) have engaged in innovative sale & leaseback and outsourcing schemes. Strong claims are made concerning the benefits of such schemes – e.g. British Land were reported to have reduced their weighted cost of debt by 150bp as a result of the Broadgate issue. The paper reports preliminary findings from a project funded by the Corporation of London and the RICS Research Foundation examining a number of innovative schemes to identify, within a formal finance framework, sources of added value and hidden costs. The analysis indicates that many of the gains claimed conceal costs – in terms of market value of debt or flexibility of management – while others result from unusual firm or market conditions (for example utilising the UK long lease and the unusual shape of the yield curve). Nonetheless, there are real gains resulting from the innovations, reflecting arbitrage and institutional constraints in the direct (private) real estate market

Influences on secured lending property valuations in the UK

A significant part of bank lending in the UK is secured on commercial property and valuations play an important part in this process. They are an integral part of risk management within the banking sector. It is therefore important that valuations are independent and objective and are used properly to ensure that secured lending is soundly based from the perspective of both lender and borrower. The purpose of this research is to examine objectivity and transparency in the valuation process for bank lending and to identify any influences which may undermine the process. A detailed analysis of 31 valuation negligence cases has been followed by two focus groups of lenders and valuers and also questionnaire surveys of commercial lenders and valuers. Many stakeholders exist, for example lenders, borrowers and brokers, who are able to influence the process in various ways. The strongest evidence of overt influence in the process comes from the method of valuer selection with borrowers and brokers seen to be heavily involved. There is some also some evidence of influence during the draft valuation process. A significant minority of valuers feel that inappropriate pressure is applied by borrowers and brokers yet there is no apparent part of the process that leads to this. The panel system employed by lenders is found to be a significant part of the system and merits further examination. The pressure felt by valuers needs more investigation along with the question of if and how the process could dispel such feelings. This is seen as particularly important in the context of bank regulation.

Property company performance and real interest rates: a regime-switching approach

Linear models of property market performance may be misspecified if there exist distinct states where the market drivers behave in different ways. This paper examines the applicability of non-linear regime-based models. A Self Exciting Threshold Autoregressive (SETAR) model is applied to property company share data, using the real rate of interest to define regimes. Distinct regimes appear exhibiting markedly different market behaviour. The model both casts doubt on the specification of conventional linear models and offers the possibility of developing effective trading rules for real estate equities.

The uncertainty of valuation

Valuation is often said to be “an art not a science” but this relates to the techniques employed to calculate value not to the underlying concept itself. Valuation is the process of estimating price in the market place. Yet, such an estimation will be affected by uncertainties. Uncertainty in the comparable information available; uncertainty in the current and future market conditions and uncertainty in the specific inputs for the subject property. These input uncertainties will translate into an uncertainty with the output figure, the valuation. The degree of the uncertainties will vary according to the level of market activity; the more active a market, the more credence will be given to the input information. In the UK at the moment the Royal Institution of Chartered Surveyors (RICS) is considering ways in which the uncertainty of the output figure, the valuation, can be conveyed to the use of the valuation, but as yet no definitive view has been taken. One of the major problems is that Valuation models (in the UK) are based upon comparable information and rely upon single inputs. They are not probability based, yet uncertainty is probability driven. In this paper, we discuss the issues underlying uncertainty in valuations and suggest a probability-based model (using Crystal Ball) to address the shortcomings of the current model.

The influence of a decision support tool on real estate valuations

An appraisal task involves the rendering of market value, an unobservable and hypothetical construct. Direct feedback against this objective is typically not possible, so alternative feedback such as confirmation of previous appraised values may be employed. This may alter the appraiser’s perception of the valuation objective leading to divergence from the appraisal normative model. The real estate literature suggests appraisers have been susceptible to the influence of previous appraised values, often resulting in biased valuations. This research focuses on the efficacy of a decision support tool in eliminating or subduing this bias in the appraisal process.