46 resultados para mortgage loan pricing

em CentAUR: Central Archive University of Reading - UK


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This paper presents the findings of the study that examines how income multiples for mortgage loan associates with home repossession using the data of the Council of Mortgage Lenders (CML). It employs a statistical measure for improving regression efficiency with conditioning information in the form of lagged instrument to unravel the pattern of association evident from the data. Based on the data, the study investigates what level of income multiples is optimum – that is the income multiple that minimises home repossession. A sensitivity analysis was undertaken to show how home repossession responds to changes in income multiples. For each of the analytical tasks, the study compares the aggregate market, first-time-buyers, and home movers.

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This paper investigates the behavior of residential property and examines the linkages between house price dynamics and bank herding behavior. The analysis presents evidence that irrational behaviour may have played a significant role in several countries, including; United Kingdom, Spain, Denmark, Sweden and Ireland. In addition, we also provide evidence indicative of herding behaviour in the European residential mortgage loan market. Granger Causality tests indicate that non-fundamentally justified prices dynamics contributed to herding by lenders and that this behaviour was a response by the banks as a group to common information on residential property assets. In contrast, in Germany, Portugal and Austria, residential property prices were largely explained by fundamentals. Furthermore, these countries show no evidence of either irrational price bubbles or herd behaviour in the mortgage market. Granger Causality tests indicate that both variables are independent.

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The recent global economic crisis is often associated with the development and pricing of mortgage-backed securities (i.e. MBSs) and underlying products (i.e. sub-prime mortgages). This work uses a rich database of MBS issues and represents the first attempt to price commercial MBSs (i.e. CMBSs) in the European market. Our results are consistent with research carried out in the US market and we find that bond-, mortgage-, real estate-related and multinational characteristics show different degrees of significance in explaining European CMBS spreads at issuance. Multiple linear regression analysis using a databank of CMBSs issued between 1997 and 2007 indicates a strong relationship with bond-related factors, followed by real estate and mortgage market conditions. We also find that multinational factors are significant, with country of issuance, collateral location and access to more liquid markets all being important in explaining the cost of secured funding for real estate companies. As floater coupon tranches tend to be riskier and exhibit higher spreads, we also estimate a model using this sub-set of data and results hold, hence reinforcing our findings. Finally, we estimate our model for both tranches A and B and find that real estate factors become relatively more important for the riskier investment products.

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Existing theoretical models of house prices and credit rely on continuous rationality of consumers, an assumption that has been frequently questioned in recent years. Meanwhile, empirical investigations of the relationship between prices and credit are often based on national-level data, which is then tested for structural breaks and asymmetric responses, usually with subsamples. Earlier author argues that local markets are structurally different from one another and so the coefficients of any estimated housing market model should vary from region to region. We investigate differences in the price–credit relationship for 12 regions of the UK. Markov-switching is introduced to capture asymmetric market behaviours and turning points. Results show that credit abundance had a large impact on house prices in Greater London and nearby regions alongside a strong positive feedback effect from past house price movements. This impact is even larger in Greater London and the South East of England when house prices are falling, which are the only instances where the credit effect is more prominent than the positive feedback effect. A strong positive feedback effect from past lending activity is also present in the loan dynamics. Furthermore, bubble probabilities extracted using a discrete Kalman filter neatly capture market turning points.

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Efficient markets should guarantee the existence of zero spreads for total return swaps. However, real estate markets have recorded values that are significantly different from zero in both directions. Possible explanations might suggest non-rational behaviour by inexperienced market players or unusual features of the underlying asset market. We find that institutional characteristics in the underlying market lead to market inefficiencies and, hence, to the creation of a rational trading window with upper and lower bounds within which transactions do not offer arbitrage opportunities. Given the existence of this rational trading window, we also argue that the observed spreads can substantially be explained by trading imbalances due to the limited liquidity of a newly formed market and/or to the effect of market sentiment, complementing explanations based on the lag between underlying market returns and index returns.

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A review of current risk pricing practices in the financial, insurance and construction sectors is conducted through a comprehensive literature review. The purpose was to inform a study on risk and price in the tendering processes of contractors: specifically, how contractors take account of risk when they are calculating their bids for construction work. The reference to mainstream literature was in view of construction management research as a field of application rather than a fundamental academic discipline. Analytical models are used for risk pricing in the financial sector. Certain mathematical laws and principles of insurance are used to price risk in the insurance sector. construction contractors and practitioners are described to traditionally price allowances for project risk using mechanisms such as intuition and experience. Project risk analysis models have proliferated in recent years. However, they are rarely used because of problems practitioners face when confronted with them. A discussion of practices across the three sectors shows that the construction industry does not approach risk according to the sophisticated mechanisms of the two other sectors. This is not a poor situation in itself. However, knowledge transfer from finance and insurance can help construction practitioners. But also, formal risk models for contractors should be informed by the commercial exigencies and unique characteristics of the construction sector.

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This study analyzes the issue of American option valuation when the underlying exhibits a GARCH-type volatility process. We propose the usage of Rubinstein's Edgeworth binomial tree (EBT) in contrast to simulation-based methods being considered in previous studies. The EBT-based valuation approach makes an implied calibration of the pricing model feasible. By empirically analyzing the pricing performance of American index and equity options, we illustrate the superiority of the proposed approach.

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We derive general analytic approximations for pricing European basket and rainbow options on N assets. The key idea is to express the option’s price as a sum of prices of various compound exchange options, each with different pairs of subordinate multi- or single-asset options. The underlying asset prices are assumed to follow lognormal processes, although our results can be extended to certain other price processes for the underlying. For some multi-asset options a strong condition holds, whereby each compound exchange option is equivalent to a standard single-asset option under a modified measure, and in such cases an almost exact analytic price exists. More generally, approximate analytic prices for multi-asset options are derived using a weak lognormality condition, where the approximation stems from making constant volatility assumptions on the price processes that drive the prices of the subordinate basket options. The analytic formulae for multi-asset option prices, and their Greeks, are defined in a recursive framework. For instance, the option delta is defined in terms of the delta relative to subordinate multi-asset options, and the deltas of these subordinate options with respect to the underlying assets. Simulations test the accuracy of our approximations, given some assumed values for the asset volatilities and correlations. Finally, a calibration algorithm is proposed and illustrated.