Robert Shiller Lecture

I get daily Google Alerts from http://www.google.com/alerts on Behavioural Finance. Normally it is rubbish searches, but it does bring up new stuff. Today, this came through....

Geary Behavioural Economics Blog: Robert Shiller Lecture from ...
By Liam Delaney 
A really superb lecture on behavioural finance from Robert Shiller - those doing my courses will recognise hopefully all of the topics - looking at him lecture is rekindling my ancient ambivalence with respect to powerpoint - chalk and ...
Geary Behavioural Economics Blog - http://gearybehaviourcenter.blogspot.com/

linking to a lecture by Robert Shiller on the role of psychology in Behavioural Finance. Tyler Cowen of Marginal Revolution also pointed out http://academicearth.org/ which records lectures from America's top universities. Very useful.

Behavioral Finance and Wealth Management

I had started by reviewing or summarising the descriptions Pompian gave of various Biases and their impact on financial decision making. What may be better is to do a post specifically dedicated to each bias with links I can accumulate over time to various sources which review those biases.

Pompian follows a formulaic examination of each bias, discussion of it's implications, a test for determining whether a client has the bias, and steps to try and counter that. In the end, his proposal is to adjust for a balance between the optimal portfolio according to traditional Markowitz's Efficient Frontier style analysis. His focus is very much at the individual Independent Advisor Level. How can they understand their client's and adjust the client's portfolio to maximise the possibility that they will stick to the optimal allocation strategy. Once that strategy is in place, it would be a case of reviewing the strategy to make sure it is still correct (given unexpected life changes) but otherwise attempting to interfere as little as possible.

The book is useful introduction to Behavioural Finance, and opens the door to questions that need to be asked when providing advice.

I still have an uneasy feeling about an over-reliance on a system (MPT) that has as it's basis a belief that returns are normally distributed and uses Volatility as a definition of risk.

What I like about the book therefore, is not so much it's solution but the fact that it highlights a question.

Finance for a long time has tried to understand the question of the optimal strategy and how best to allocate assets. While that question has not yet been answered, the parallel discussion of how to best approach the emotional side of investing.

Creating Benchmarks

The Dalbar study is the only one that I am aware of that attempts to create Benchmarks for Investor Behaviour. There are obvious advantages to having a widely established benchmarks that you can use to measure your performance. The key though is to establish that they make sense.

Here are the characteristics of a good benchmark as according to the AIMR Benchmark & Performance Attribution Subcomitee Report (1998) by 'Insurance Finance & Investment', Oct 31 2006 issue, a publication of World Trade Executive. Comment welcome.

1. Representative of the asset class or mandate
2. Investable
3. Constructed in a disciplined and objective manner
4. formulated from publicly available information
5. acceptable by the manager as a neutral position
6. consistent with underlying investor status (regarding tax, time horizon etc.)

A 'Behavioural Benchmark' would obviously be different from a fund benchmark. There are a few issues that come up.

How do you measure what the client did with the money when they withdrew it? Did it sit in cash or did they maybe put it in another vehicle that actually outperformed? Is it possible to measure the impact of client behaviour without knowledge of their entire portfolio?

You can use systematic behaviour patterns as benchmarks since they are implementable (i.e. like being 'investable'). This allows comparison with methods such as dollar-cost averaging and buy and hold strategies.

It is possible to know the actual return of the investor or IRR. Why is an attempt to work out the average investor behaviour better than just using the actual return they got? Why should we model what they would have got based on 'average behaviour' such as in the Dalbar study?

Traditionally we try stripping out the effect of cash flows by giving the Time-Weighted Rate of Return rather than the IRR. The fund manager has no control of the cash flows and so we attempt to give a fairer view of the value add.

In order to accurately measure the impacts of a clients behaviour, you would need to have a detailed knowledge of their actual cash flows and then measure their decisions against their default or passive allocations. I am a bit concerned that the Dalbar measures don't really do this. By giving a simple flat $10,000/20 years it ignores the impact of cash flows and of what the clients alternative choices were.

Obviously though, benchmarks have to be simple and implementable as well which is what the Dalbar's benchmark is.

QAIB 2008

Quantitative Analysis of Investor Behaviour (2008)

This post is longer than I would like, and I will break it up at a later stage. I basically just wrote thoughts down as I read through the DALBAR study. The study looks at the 20 year period ended December 31 2007, and the equity section focuses on investments in the US through S&P Index.

The intention is that the QAIB be used to establish benchmarks. It further suggest that you can contact DALBAR for further information on using the QAIB benchmark and making comparable calculations.

The benchmark attempts to simulate the behaviour of the 'average investor' by tracking net inflows/outflows into Mutual Funds. This allows them to establish a pattern in which a $10,000 investment was made relative to that of a systematic investment of $10,000 over time.

Does the Dollar Cost Averaging/Systematic approach assume level contribution in nominal or in real terms?

Most mutual fund companies use the return of a lump sum invested at the beginning of an investment period. This only really works for someone who starts at the beginning of those periods and makes one contribution. Perhaps there should be three measures:

1) Lump sum from start of period
2) Annual Contribution from start of period
3) Monthly Contribution from start of period

The issue then becomes, what are the regular contributions? Do you use $1 per period, or do you allow for inflation. For Domestic Funds, you could allow for inflation. For Global Funds it becomes a little more difficult. You could benchmark it against the same currency benchmark as the fund's benchmark and use weighted average inflation measures.

The results show the average investor over the last 20 years having gained 4.48% vs. 11.81% performance of the underlying S&P index. This is often used to suggest a passive investment strategy and regular contributions. I think those are separate considerations.

1) Do you remove your decision making from when to invest?
2) Do you believe your chosen asset manager can beat a passive index?

The big problem is that both questions are not easy to answer and overconfidence would lead people to answer Yes to both. My feeling is that it is possible for a manager to beat an index, but finding those managers is tough. Partly because the best ones seem to make a lot less noise than the average ones. I think the first question is a more difficult one to claim that you can do.

The Guess Right Ratio

The next measure that is a useful suggestion is one of how often an investor makes the write call. So, if there are inflows and the next month has positive returns, they score 1. They also score if there are outflows and the market goes down. The average score over the period under investigation was 61%. Naturally, the period under investigation was an incredibly long bull market. It will be interesting to see how next years results to the end of 2008 look! If you invest every month, you would expect to have a ratio greater than 50% in a rising market.

Perhaps a better measure would be to divide the `Guess Right Ratio' by the % up months? If the market went down, so you were wrong more often, the base would also go down, so your `Guess Better than Randomly Ratio' would stay close to 100%. If you destroy value, it would fall below and if you are adding value it would go above 100%. Both the GRR and the GBTRR aren't weighted by money, so you wouldn't be able to use them to check consistency with actual value added or destroyed.

Holding Period

`The holding period reflects the length of time the average investor holds a fund if the current redemption rate persists'

This measure is useful if you assume that it is more likely the investor will share the funds returns if they stick around and don't do much. That seems intuitive.

The paper gives a methodology for calculating the investor return which can be applied to markets other than the S&P. I would like to see if others have taken DALBAR's work and applied it to other markets, or have any critical comment on the way they have done it. I need to let what they have done wallow in my head for a while to think of my take. First take is that it provides a very useful start to the process of providing measures of client behaviour.

Irrational Exuberance (2000)

I have just finished Irrational Exuberance by Robert Shiller. I am aware that there are updates, and new editions, as the edition I read was released in 2000 before the `Internet Bubble' burst.

I am wary of quoting too many of the passages that he wrote here. It is worth reading the book. Like a lot of the other literature, much time is spent on discussing whether or not the market is efficient. In an efficient market, you could safely leave people to do as they pleased since timing would neither help nor hinder them. I think Shiller makes a very compelling argument that this is simply not true. In this edition he closes the book by making various suggestions as to how we could improve market efficiency and opens the debate as to how we can prevent some of the wealth destruction. 

A large part of his discussion centers around the flow of information, and how that is used. Market Efficiency is based on perfect information being available. And it is true, we have easier access to an absolute wealth of information. The thing is not so much the availability of information, but also the ability to process that information. Ability and willingness. A lot of investors are not professionals and often `play the market' as a source of entertainment. In addition people have a lot of other things to worry about.

Shiller:

On the average investor...

'During the most significant financial events, most people are preoccupied with other personal matters, not with the financial markets at all.... People think they know more than they do. They like to express opinions on matters they know little about, and they often act on these opinions'

On the essence of the EMH:

`At its roots, the efficient markets theory holds that differing abilities do not produce differing investment performance. The Theory claims that the smartest people will not be able to do better than the least intelligent people ito investment performance. They can do no better because their superior understanding is already completely incorporated into the share price.'

One of his most convincing rebuttals:

'Stock Prices appear to be too volatile to be considered in accord with efficient markets. If stocks prices are supposed to be an optimal predictor of the dividend present value, then they should not jump around erratically when the true fundamental value is growing along a smooth trend.'

And, lastly a warning about another risk that EMH can incorrectly lead people to thinking that Equities will always outperform:

The evidence that stocks will always outperform bonds over long time intervals simply does not exist... at least one genuine fundamental truth about stocks: that they are a residual claim on corporate cash flows, available to stockholders only after everyone else has been paid. Stocks are therefore, by their very definition, risky.

For the most part, I think Shiller's book for me is a warning against accepting too closely conventional wisdom without doing your homework.

The stock market is after all just a price setting mechanism for businesses. Once set though, the price acts independently, and while there is an argument for the availability of information, a belief that in general, the aggregate average interpretation is right is not one that I subscribe to. 

As always, I am happy to read arguments that may convince me otherwise, but I think it is both possible to create and to destroy wealth over time.

My aim is to try find measures to help people stop themselves from destroying wealth.