0. Model risk in unusual corners
the case of home price indices (HPI)
Edinburgh chapter
14 FEBRUARY 2017

1. 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)

2. Overview of talk “Index” Back to basics The role of models
Implications

3. Index /ˈɪndɛks/
Source: Oxford Dictionary

4. 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

5. 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

6. 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?

7. 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

8. 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…

9. Enter: models to the rescue
Source: IHS Markit

10. Enter: models to the rescue
Source: IHS Markit

11. Enter: models to the rescue
Source: IHS Markit

12. 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

13. 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

14. 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

15. 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

16. Questions?
The information contained herein is proprietary. © 2016 True North Partners LLP