The current paper is an expansion of the paper ‘Theta Model Forecasts Real Estate Values’, presented at the European Real Estate Society (ERES) Conference, 2006. In the former paper, the Theta method was compared with other forecasting methods in forecasting quarterly housing prices in the UK. The theta method had then produced the best forecasts, on average, with the smallest mean errors. Additional data are used here, representing the total average dwelling prices in the UK, and are organized into months, from January 1983 up to September 2006. This paper examines the present state of the UK housing market and tests the theta method on the new monthly data. The time-series data used for forecasting are again provided from the Halifax House Price Index, and cover different categories of buyers (all, first-time buyers and home movers) and houses (all, new and existing). Copyright © 2007 John Wiley & Sons, Ltd.

Evidence is shown, using US real estate default data from 1987–2004, that high default rates on mortgages are associated with prior period housing prices, rental income, inflation-adjusted household median income and interest rate fluctuations. This paper investigates the proposition: that the percentage of real estate defaults is a function of alternative income opportunities. Copyright © 2007 John Wiley & Sons, Ltd.

Four major home price indexes have been used in this study, and are based on different calculation methods and from different sources. The descriptive statistics indicate no meaningful differences among them. However, by analysing the orthogonalized impulse response and variance decomposition matrixes from the vector autoregressions, this study found some noticeable differences in the dynamic relationships between these indexes and three other housing factors – mortgage rates, existing home sales and new home sales – in addition to the inflation factor. The results may reflect the holding period effect in repeat sales house price indexes. Copyright © 2008 John Wiley & Sons, Ltd.

There are strong forces in the commercial real estate industry pushing banks and investors to take more quantitative approaches in assessing risks. This quantification will affect everything from loan approvals to deal structures and loan pricing. There are four main drivers for the use of quantitative tools: 1) The Basel II regulations that require banks to have risk models to calculate their minimum capital requirements; 2) The pressure to increase returns by using more complex financial structures; 3) The need to ensure that senior managers can monitor the effect of these complex structures on the risk of the portfolio; and 4) Concern that the world has become more interlinked, increasing the risk of several sectors melting down simultaneously. This article discusses some of the ways that risk can be measured, the requirements of the new regulations and how risk measurement tools can be used to increase profitability and reduce risk in structuring new deals. Copyright © 2008 John Wiley & Sons, Ltd.

Real estate investments are frequently leveraged. Leverage is an important tool for any real estate investor whose target return exceeds the expected return on core, unleveraged assets, since it can increase potential returns – although at the cost of increasing risk. It therefore competes with other means of raising risk and returns – in particular, buying riskier underlying investments – as a method of improving the performance of a portfolio. From a theoretical perspective, leverage should be preferred so long as the marginal increase in expected return per unit of extra risk from leverage exceeds that obtained from buying riskier assets. Since there are diminishing returns to leverage – primarily because costs rise as borrowing levels rise relative to value – this trade-off will become less attractive as leverage rises, leading to an equilibrium optimal level of leverage. If all investors face the same opportunity set, then, from a theoretical perspective, all investors should leverage core investments up to this level so long as their return target is at least as high as the returns generated at this equilibrium point – a conclusion that is out of line with current practice. Unfortunately, it is very difficult to measure this equilibrium point, since, while it is relatively straightforward to compute the increase in risks and returns deriving from leverage, rather little is known about the risk/return trade-off in real estate space. Copyright © 2008 John Wiley & Sons, Ltd.

From a borrower's point of view, what drives many loan negotiations is a tension between, on the one hand, the attractive pricing that the liquidity of the capital markets enables securitizing lenders to offer (when compared with their portfolio lender competition), versus, on the other hand, added up-front structuring requirements and increased ongoing ‘policing’ of and constraints on the borrower's property operations, compounded by the arguably less-responsive servicing that borrowers occasionally view as the price of doing real estate mortgage investment conduit (REMIC)-destined deals. This first part of the series highlights key issues regarding (1) matters that set the tone for subsequent negotiations by influencing the parties' relative negotiating leverage from early stages of the deal; (2) the extent of and limits on pre-funding due diligence and (similarly) life-of-loan monitoring; (3) the non-recourse carveouts; (4) transfer restrictions; and (5) bankruptcy remoteness. Copyright © 2008 John Wiley & Sons, Ltd.