Tuesday 28th September 2010

Olswang Offices, 90 High Holborn, London, WC1V 6XX

From our experience working with lawyers across a number of city firms we have identified characteristics that appear to persist.

1. The investment approaches that have been adopted bear little relevance to the outcome the individual or family is trying to achieve. More often than not, risk has been shunned in favour of hope-for  lower volatility, using standardised portfolios that will result in lower outcomes, such as less spending in retirement.
2. Despite overwhelming evidence that it consistently fails to deliver better returns for retail investors, most solicitors are still paying a high price for active fund management and almost all believed  they were paying less to the financial services industry than they actually were, or needed to be.
3. Most solicitors had a lack of clarity about the relative attraction of property versus financial assets, particular when considering leverage in the form of a mortgage.
4. Confidence and trust in advisers was low, with many of your peers refraining from action, taking advice from multiple sources and some reluctantly driven to a self-directed approach.

We have been invited to speak to the Olswang partners for a second time because a group of existing partners valued highly the work that we completed for them and believe others should be offered an opportunity to learn a little more about how we work with clients.

In this workshop, Stuart and Joe will describe an approach that focuses on your goals and not those of the industry, including:

• The benefits that come about from goal-based financial planning, including a hierarchical framework that makes financial decisions easier and more consistent;
• How best to implement a simple low-cost structure suited to those in the early stages of high savings; and
• How we design and manage a portfolio of investments to deliver specific, duration-matched, quantified outcomes as defined by the client during the planning stage.

The Budget announced a change from RPI to CPI as the basis of future inflation adjustment to certain benefits, including the state pension. Subsequently the DWP announced that it would use CPI, not RPI as currently, as the basis of Limited Price Indexation for private pensions and of indexation of public-sector pension benefits. 

The Government’s message is consistent, based on the context of the index use and therefore the components of the index. If benefit claimants do not own their own home, mortgage costs and housing depreciation are not relevant but rent is. If recipients of public sector pension do not have a mortgage, mortgage costs are not relevant. By emphasising the home ownership components, it has (possibly unintentionally) led people into thinking the inclusion of home ownership costs explains the past higher trend increase in the RPI than the CPI and is the basis of a systematic and sustainable bias.  

Media reporting has picked up on this implication and reported it without question. But it misses an important point. The reason why, other things being equal, we should expect RPI to lead to higher levels (and so increase the cost to the taxpayer of providing indexed benefits) is that it uses arithmetic means whereas the CPI uses geometric means. The NSO has quantified the effect since the CPI was introduced in 1997 as an average downward bias of 0.5% pa. This is almost exactly the actual difference in the indices that has been widely attributed in the media to the housing component.

House prices affect both the mortgage interest payments and the housing depreciation components of the RPI. They affect mortgage costs because the NSO attempts to capture the changing national average mortgage level as the base for multiplying by a current interest rate, as distinct from the unchanged mortgage of the same typical household. Similar tricky concepts influence the differences in competing house price indices. House prices affect the depreciation component (whose presence I will not try to explain) similarly although the effect ought to be less because it separates the building element from the plot. Both mortgage interest payments and depreciation have a weight of about 5% in the RPI. Rents have a similar weight but are common to both indices.

Over the long term, it is reasonable to expect house prices to rise faster than general costs, because of the links to earnings, via credit. A realistic long-term trend in relative prices is about 2% pa. I suspect it would be less (it was zero in the US until the late 1990s) if development land were more freely available. Building costs ought not to have a trend different from general prices. With a mean interest rate change of zero, this translates into a bias between 0.1 and 2% pa, mainly depending on the dodgy depreciation component. Clearly, the component difference between the two indices is smaller than the computational difference and also overwhelms the debate about which index is right according to the context.  

For pensioners in particular, who either rent or own homes but do not typically have mortgages, including or excluding a 5% weight for mortgage interest payments, however logical,  is trivial relative to the computational bias.

There is a debate to be had about the most appropriate index based on its computation as well as its components, so that we can be clear that the change is fair to both beneficiaries and taxpayers.

Generally, we might expect statisticians to prefer to compute a series with a mean change different from zero using geometric means. In the specific case of the CPI, it also applies a concept that consumption patterns change with shifts in relative prices, which seems intuitively more accurate and would not arise if aggregating arithmetic means.  I can see why a fair-minded, disinterested decision maker (a politician?) might opt for the CPI.

Understanding the concepts behind the Government’s change is important if reacting to clients’ questions and suspicions. Clients are not helped by comments such from Buck Consultants in the Sunday Times last weekend that ‘the change had effectively wiped £67,000 off the total value of the pension pot’ for someone earning £100,000 with 30 years service. For a start they assumed 0.75% pa difference in trend (where does that come from?) and in any case why assume this is their right?

Understanding the concepts is also important for assessing the impact on the ILG market. Here we need to separate the impact on investors betting against the implied inflation rate or breakeven rate of inflation from the impact on investors hedging the inflation risk implicit in their liabilities or goal outcomes.

The first ought to affect yields almost immediately, as a once off change. It would reflect the expected difference in RPI and CPI not as a long-term trend but over the term of their bet. This impact may now be complete.

The second poses a technical problem, until the market creates CPI as well as RPI swaps. But the impact on risk preferences is neutral. ILGs, whatever the index used, still represent a tight hedge for inflation compared with the very loose match provided by real assets like equities and property. The separation of risky bets and risk free hedges will still look to many clients like a better way to manage risks than relying on diversification effects from using more and more building blocks with less and less certainty about the correlations.

Click No Monkey Business Home truths to download a pdf version of the full paper. We have edited the original version we posted to reflect feedback, including adding a section on the tax effects on the comparison of buying and renting. Only our summary and conclusions are extracted below.

Summary

Popular opinion about home ownership in the UK is that it has created real wealth, more than the stockmarket and with much less risk. By contrast, renting is ‘money down the drain’. Naturally, because people think house prices can grow faster than the economy, young people fear the bottom rung of the housing ladder will tend always to be moving out of reach.

These are false notions, based on imperfect accounting of people’s own experience, gained in a particular period of economic history, and interpreted with a shaky grasp of basic economics, both national and household. Though the popular illusions might well have been shattered by the credit crisis, they appear to have survived largely intact.

In this paper we explain in laymen’s terms the economics underlying decisions about home financing and suggest how they might be applied in different circumstances to reflect the benefits individuals most value.

Conclusion: ten economics-based home truths

1. There are no foregone conclusions about how best to pay to put a roof over your head: buy or rent. It has to be a bet.
2. Be clear about what you most value in life or at different stages in your life. It may not be satisfied by large and inflexible bets. We show how many of the benefits people say they value are actually put at risk by their home financing choices.
3. Comparisons before the event should not (but usually do) exclude the opportunity cost of higher savings when renting rather than repaying a mortgage. Overlooking opportunity costs explains many of the false assumptions people have about buying versus renting.
4. The factors that after the event will prove what worked best are inextricably linked by national economics but can still vary dramatically through time and in different economic environments. Partial interpretation of history, such as your own or your parents’ experience, are likely to be misleading.
5. Individual outcomes will be shaped by entry and exit points, not secular trends that are immutable and known to all. Much of the results of entry and exit points will be down to age and luck.
6. If you really do believe in secular trends, remember that the corollary is that deviations from trend ‘revert to the mean’. That means that if leveraged home ownership was a winner for a long time, it might be about to be a loser for a long time.
7. For most people, the eventual ‘balance sheet’ outcomes count for less than the impact of borrowing on household ‘profit and loss accounts’.
8. Willingness to take on mortgage debt, and the size of that debt, should therefore be more about the ability to bear the additional financial stress that follows from adverse events.
9. We find that the key determinant of long-term outcomes is the different impacts of general inflation on the cost of borrowed money and the return on investment. This makes leveraged home ownership a bet on the economic variable, inflation, which is the hardest to predict.
10. The tax effects of owning versus renting that are widely touted in favour of owning are actually neutral except when either the main home or financial assets are sold to support spending; but the CGT advantage of property in that case is weakened by the scope to shelter, spread and time disposals of financial assets.

I single it out because outsmarting the smarts with simple thinking is very No Monkey Business. In fact, the same data has regularly featured in No Monkey Business posts since 2006 (about a year behind Paulson) as an obvious parallel with the Nationwide deflated index of UK average house prices which I regularly monitored on the No Monkey Business blog from about 2002. Just don’t ask me where my $4b is.

What drew me to the study of the trend and deviations from trend in real house prices was that it was itself a parallel application of an important insight about equity returns: historical time series for ‘real total returns’ (ie cumulative indexed performance with income reinvested, deflated by a consumer price index) contain valuable predictive information for investors, and more so than conventional valuation measures like price/earnings multiples and dividend yields. This was one of the big but simple ideas set out in my book in 2002. Since 1999 it has been the basis of horizon-specific probabilistic return projections in a model we now use to manage Defined Outcome portfolios.  

Such an apparently naive solution to a complex problem is deeply offensive to most investment professionals as it implies redundancy for much of their industry. I naturally therefore warmed to the naivete of the Sunday Times account, as typified by this extract.

'Everybody said home prices never had declined on a nationwide basis except during the Great Depression,” Paulson later recalled. He sent Pellegrini scurrying back to his cubicle to determine how overheated the property market was.Tracking interest rates over the decades, Pellegrini concluded that they had little impact on house prices. But as he reviewed academic and government literature and figures, Pellegrini grew frustrated. He couldn’t quantify how excessive housing prices were or show when a bubble might have started. He couldn’t even prove the price surge was distinct from historic moves.Grasping for new ideas, Pellegrini added a “trend line” to the housing data; this illustrated how much prices had surged lately. That’s when Pellegrini took a step back to view things over a longer period, ordering up data on home prices all the way back to 1975. Suddenly, the answer was as plain as the paper in front of him: housing prices had climbed a puny 1.4% annually between 1975 and 2000 after inflation was taken into consideration. But they had soared by more than 7% a year in the following five years, until 2005. The upshot: US home prices would have to drop by almost 40% to return to their historic trend line. Not only had prices climbed like never before, but Pellegrini’s figures showed that each time housing had dropped in the past, it fell through the trend line, suggesting that an eventual drop was likely to be brutal. Pellegrini sat upright, staring at his trend line, amazed at how simple and clear it was.The next morning, he raced in to show Paulson. “This is unbelievable,” said Paulson, unable to take his eyes off the chart. “This is our bubble. Now we can prove it.” Pellegrini just grinned, unable to mask his pride.'

The standard source material for real house prices, deflated by general inflation as measured by the CPI, was the S&P Case-Shiller Index. Pellegrini refers to data going back to 1975 but there is in fact earlier data which I came across a little later in the form of index creator Professor Robert Shiller’s submission to a Congressional commitee. In September 2006 I posted an item on the No Monkey Business blog called US house prices: you thought we had a problem which included a chart of over one century of real prices for single-family homes.

It was important that the data be real. Real prices are perhaps better decribed as relative house prices, because they measure prices relative to general price inflation. But even real price series were rarely publicised because of people’s obsession with changes in the price level, treating house price inflation as the key information rather than the level of relative prices itself. This was a widespread problem in the US just as it was in the UK. I still berate newspaper editors for repeating this error.

As I pointed out in my article, fitting a regression trend to the long time series data was not helpful because there were several distinct phases of price behaviour, including just two since the end of WWII, up to and after about 2000: no real growth followed by a growth explosion. In my article, I contrasted the absence of any overall trend in US real house prices prior to 2000 with the trend in post-war real prices in the UK, which has been fairly persistent at about 2% per annum, in line with growth in personal incomes.  The 0% trend in the US for some 50 years means that relative to personal incomes US housing had become progressively more affordable. I agreed with Prof Shiller’s interpretation that this was due to easy access to new development land, an endowment we clearly do not enjoy in our planning-constrained small island.

More important, the only plausible explanation for the change in price dynamics after 2000 was the change in credit availability. The fact that people wanted to believe in endless rapid growth, a new twist to the American dream, was a necesssary condition but it also required bankers and mortgage investors to throw caution to the wind or the boom would have simply run out of fuel. And it was the massive stock of derivatives created on the back of securitised mortgages, two symptoms of the credit-induced madness that overtook the housing market, that gave Paulson & Co the instruments, in the form of credit default swaps (insurance contracts that would pay out if the underlying securities fell in price), which had the inherent leverage to turn £147m into $20b.  That was convenient but it was also smart and gutsy.