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UK Property And Recovery Valuation. Our Service. Given a portfolio of properties we provide Current house price Postcode level house price index Short-term price projection Given a portfolio of mortgages we provide More accurate current house price Current LTV (vital for RMBS valuation)
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Our Service • Given a portfolio of properties we provide • Current house price • Postcode level house price index • Short-term price projection • Given a portfolio of mortgages we provide • More accurate current house price • Current LTV (vital for RMBS valuation) • Loan specific house price index • Loan specific LTV projection • Impact from known and what-it default scenarios • Impact from systematic market shifts • Independent from AVMs and structurers Property specific modeling enhances accuracy Recovery levels are vital for RMBS valuation in terms of recovery and default probability
Problems with AVMs • Largely untested in a declining market • Not tailored to collateral valuation • Developed as a tool for housing sales • The UK has poor data availability • Determining the number of bedrooms is hard • Associated with the players who are perceived to be responsible for the current securitisation problems • Any consistent overvaluation leads to an underestimation of LTV • Opaque AVMs can consistently overvalue causing an underestimation of LTV
An Inflation Model • Use inflation modeling at the postcode level • Each inflation curve can be derived for a specific loan • Inflation levels show a high degree of invariance to housing specifics as they are driven by regional trends • The concept of inflation maps directly to the notion of marking to market • Use weighting and interpolation to measure inflation rather than relying on weak statistical inferences Inflation levels exhibit a high degree of invariance to parameter choices
How it works • The Land Registry maintains a record of every transaction • Determine all transactions in the neighbourhood of a target property • Using regression fit an inflation curve to the data with specialised weight parameters
Location • Weight each transaction according to its distance from the target • Ensures large but relevant data sets
Time • Key times to give weight to are • Last transaction date • Valuation date • Removes path dependence • Flood impact step-down Low influence
Results • Absolute price levels vary but inflation shape is stable Oct ‘07
Results cont’d • Housing type determines shape but this data is readily available Oct ‘07
Usage • Up to date LTV for a portfolio of loans • Impact to recovery by • 1% rise in defaults • 1% rise in value lost by administration • 1% fall in housing market • 1% increase in transaction period • Projected recoveries derived from each inflation curve • Vital input of current positions for extra models to be attached to such as • Default model • Interest rate model • etc Loss severity is easily calculated for a wide variety of scenarios and assumptions
Active Administration • Select those mortgages that have the most equity by current LTV • Focus on refinancing those mortgages where little equity exists to avoid forced sale • Use projected house prices to determine the best action and timing • Creates a clear picture of an individual’s property asset Preventative action preserves needlessly wasted equity being eroded by repossessions