Model risk in unusual corners the case of home price indices (HPI) Edinburgh chapter 14 FEBRUARY 2017
Introduction Vijay Krishnaswamy is a Partner at True North Partners, a specialist consulting boutique 18 years of front-office, finance and risk management experience Previously, worked at the FSA, KPMG, Standard Chartered, ANZ Co-editor of “Managing Illiquid Assets”, published by RiskBooks incl. a chapter on model risk Set up model governance framework for the FSA (now PRA)
Overview of talk “Index” Back to basics The role of models Implications
Index /ˈɪndɛks/ Source: Oxford Dictionary
Why have indices become important? Uses Outcomes (Re-)Valuation of assets Credit scoring Pricing Capital reserving, P&L provisioning/ IFRS 9 Stress testing Benchmark for pricing Overall barometer of the market Asset in itself The use of HPIs in mortgage portfolios is very common Variety of sources: Banks (Halifax, Nationwide,…) Property firms (Knight Frank etc…) Government (Land Registry) Easy, quick, inexpensive Exposure to a diverse portfolio Highly prevalent…. … and abused EU Benchmarks Regulation
Where do HPIs come from? 1 ordinary share of Unilever Trade 1: 3310p latest valuation Update to FTSE indices Trade 2 (within a few milliseconds/ end of day): 3350 Change is 1.2% Update to FTSE indices intra-day/ end-of-day Enabling feature: Trades 1 and 2 involve an identical share Source: LSE website
Where do HPIs come from? House at <address> Trade 1: Sold at £ 200k latest valuation Update to HPI Trade 2: Sold next month at £ 220k Change is 10% in 1 month Update to HPI of the month Assumptions needed: Same house has to be sold again the following month House has not changed intrinsically during the month What happens if we relax these assumptions?
Where do HPIs come from? Houses: Trade 1: Sold at £ 200k latest valuation Update to HPI Trade 2: Sold next month at £ 250k Change is 25% in 1 month Update to HPI of the month Does not mean a 25% increase in asset price Why? Result: The analogy to equity prices breaks down Forming an index on home prices in the same way is not possible
Enter: models to the rescue Create a “standardised” house Serves as a reference point for indexing Take each house sale transaction and “break-down” into constituents House price = m * Value of a bedroom + n * Value of a garden + …. Re-assemble the standardised house in the base period with the latest prices All this is achieved through a regression model…
Enter: models to the rescue Source: IHS Markit
Enter: models to the rescue Source: IHS Markit
Enter: models to the rescue Source: IHS Markit
So how good is this model? First built in the late 1970s/ early 1980s First published 1983 Initial explanatory power: high 80s Steady decline in model explanatory power; latest: ~70% Why? If the bank’s portfolio is not similar to the portfolio used to build the index, then the bias can be significant E.g. granular geographical variations Reference portfolio: disclosures are limited
And not all indices are equal… Aspect Halifax/ Nationwide HPI Land Registry HPI Coverage Mix-adjusted Yes No However, how much does the mix change? Registry Halifax Nationwide
Some implications of using HPIs Blind use of indices can add to model risk More a model than a “traditional” index Model risk framework Identify the index as a source of model risk? Familiarise with (whatever) available documentation? Be aware of pros and cons of different HPIs
Recap Raise awareness of model risk in HPIs Understand how HPIs compare with equity price indices and the differences The role of models in making HPIs feasible Understanding what drives the performance of such models Similar issues apply in the case of indices built on assets that are non-identical Recognise the use of a HPI as a source of model risk
Questions? The information contained herein is proprietary. © 2016 True North Partners LLP www.tnp.eu