Friday, December 30, 2011

Mechanical Trading Strategies & Backtesting and how they Create Bias

Mechanical-based trading strategies produce unintentional style or sector bias in portfolio construction. Backtesting is not the key to generating returns.

The argument behind this article is that purely mechanical-based trading strategies have a tendency to produce unintentional style or sector biases. This is problematic because the investor will find himself manifesting a viewpoint or weighting that he may have purposefully set out to avoid.

Indeed, many favour a mechanical-based strategy because it obviates the necessity for a discretionary viewpoint. This is important because an investor might want to avoid the pitfalls of selecting sector/stock weightings. Similarly, from a behaviourial finance prospective, he might want to avoid the psychological pressures of having to adjust his positions by constantly having to make discretionary decisions. In particular, value investing is seen as being susceptible to these pitfalls.

Back Testing of Trading Strategies and Why it Doesn’t Work

There is another danger here that may prove to be more pervasive via its insidiousness. Mechanical trading strategies always involve substantial back testing and, investors try to test conditions across a range of market conditions. However, what if the strategy results in a sector/style weighting that is favourable across the period of back testing, but not likely to repeat itself going forward?

The likelihood is that he will reject the system outright, or else try to refine, or add new factors to, the system in order to incorporate the new results. If the argument of this article is correct, than this process of curve fitting is likely to break down again, and the investor will find himself disappointed again.

All that this refinement is likely to achieve, is to produce a new sector/style bias -which works as
 a ‘best fit’ solution to the updated results-that will may fail as future conditions change.

Mechanical Trading Strategies Produce Unintentional Style or Sector Bias?

In a sense this is an epistemological question. In producing a mechanical strategy, traders will be trying to define a set of universal and consistent parameters upon a series of results that is actually ever-changing and evolving. Markets don’t have memories and they are not obliged to follow rules. Similarly, there is little regard for sentiment in market based strategies. This is a pity because, many believe that sentiment- think Geenspan’s ‘irrational exuberance’ and Keynes ‘animal spirits’- is what guides markets.

Furthermore, in creating the parameters for mechanical evaluation of, say stocks, they will struggle to avoid defining a factor, that doesn’t intrinsically favour a style or sector.

The latter argument is best expressed by some examples of the type of investment ratio, or filters, that are used by traders. Namely, dividend yield, price to book, price to earnings or PE ratio, price to cash flow.

Using Fundamental Filters

This section is best expressed by a series of snapshot examples within bullet points:

*Dividend Yield. Stocks that pay dividends tend to be more mature and generating cash flow. Therefore, selecting on the basis of yield tends to result in slower growth, mature companies that have previously doing well. In other words, yield would have guided investors in buying banking and housing stocks before the crash of 2008!

Similarly, favouring stocks without a dividend, would have resulted in favouring technology and internet stocks right up until the dot com bust. Furthermore, high yield companies tend to have less free cash to invest for growth. These types of stocks maybe favoured in a recession but not in a recovery.

*Price to Book. This is a favoured measure for value investors. The problem here is that different industry sectors require different amounts of tangible assets in order to generate profits. For example, a plant hire firm must hold substantive amounts of capital machinery, whilst an intellectual property company (biotech, semiconductor design, software etc) does not.

Similarly, mechanically evaluating the assets of a company does not tell investors about the quality of those assets and, its ability to generate returns in future.

*Price to Earnings. PE ratio will tell investors little about cash flow, or the capital expenditure requirements of the firm. Furthermore, they will differ in relation to where the company is in its growth cycle. However, the most damaging aspect of solely focusing on PE ratio is that it encourages a focus on companies that already have earnings. Whilst superficially attractive, this strategy means investors will rarely expose themselves to sectors like biotech or oil exploration.

*Price to Cash Flow. Focusing on this metric has many of the pitfalls of the PE ratio. In addition, it can encourage investors into low growth companies. Similarly, the market could be pricing these sectors cheaply because, they are about to be structurally challenged. For example, large cap healthcare companies currently generates huge cash flows, but how sustainable is it with the onset of an ongoing Obama health care reform process? What threats do generics pose? What drugs are in the pipeline? None of these questions are answered by solely focusing on the mechanical approach.

Portfolio Evaluation

The examples above are just a few considerations of the complexity or even impossibility of not manifesting a sector or style bias by taking an mechanical approach. Many believe that the correct approach to portfolio construction is to understand that portfolio construction is as much an art as it is a science. Furthermore, for a rational investor, taking an outright style or sector ‘view’ is a necessity, because he will serendipitously do it via mechanical strategies investing in any case!

Keynes, John Maynard "The General Theory of Employment,Interest and Money" Palgrave, 1936

Saturday, December 17, 2011

Sanjeev Shah and Anthony Bolton with Fidelity Special Situations

Fidelity Special Situations fund manager Sanjeev Shah has come under sustained criticism for his management for Anthony Bolton’s legendary fund. Shah took over when Bolton left and the performance of the special situations fund has been less than stellar. It is no matter that Bolton’s subsequent performance with his Chinese investment fund has been poor, Shah has inherited a lot of assets under management and goodwill from investors, so his investment performance will be highly scrutinized in its own right.

The usual criticisms are that his performance has been little more than a tracker fund and that he is not really engaging in special situations investing. The argument in this blog is that investors often underestimate the role of the asset manager’s (Fidelity) interests in determining investment fund returns.

Fidelity Special Situations Performance

Firstly, looking at the returns over the last six years…

Fidelity Special Situations
IMA UK All Companies

…it does indeed start to look like a tracker fund at best!

However, Sanjeev Shah took over from Bolton at the start of 2008 and the tracker like performance predates Shah’s custody. Therefore, comparing the track record of Sanjeev Shah with Anthony Bolton is fraught with difficulty.

This is not only due to the size of the fund at £2.2bn making the generation of differentiated returns difficult, but possibly also due to the incentives of Fidelity. To understand this, it’s worth looking at Anthony Bolton’s career in fund management.

Anthony Bolton and Special Situations Investing

When Bolton first took over the management of some funds at Fidelity in the UK, they were not anywhere near the kind of household name that they are today. Therefore, they had a direct interest in allowing Bolton to try and generate some supra market returns in order to garner assets under management.

Fortunately for Fidelity, Bolton achieved these results and, spectacularly so. Indeed, his funds became the darling of every little IFA out there who was grabbing some commissions from a client, who could just as easily have invested in the fund themselves.

Now turning to the incentives at Fidelity now, the situation is different. Bolton left them with billions under management and the incentive to take a risk in going for outperformance is much less. Indeed, behavioural finance teaches that the impact of a loss is psychologically weighted at double that of a gain.

Therefore, a fund that with significant assets under management, has a built in incentive not to be significantly below its benchmark. Whilst the upside from outperforming is not large enough to justify taking on the extra risk in order to generate it.

Should Fund Investors Stay With Sanjeev Shah?

On balance, fund investors would be better advised to stay with Shah and give his special situations fund some more time. Early on in his career, Bolton had some bad periods and, inevitably, investors made redemptions. Moreover, he may well be constrained by Fidelity in being able to generate non-correlated returns. We shall see.

 However, if he has the latitude than special situations investors need to recall that this style of investing requires conviction. And sometimes it takes time for the market to wake up and realize the value in someone else’s special situation! Shah needs more time.

Tuesday, December 13, 2011

China Real Estate and Housing Statistics Indicate a Slowdown

China’s real estate market is slowing. So, whilst the world is focusing on the Euro Zone sovereign debt crisis, another threat to the Global Economy appears to be gaining momentum. Let’s look at statistics on China’s housing market garnered from the official National Bureau of Statistics of China.

China Housing Market Statistics

Firstly, house prices appear to be falling as indicated in this link here for November

“Comparing with the previous month, among 70 medium and large-sized cities, the sales prices of newly constructed residential buildings declined in 34 cities while that of 20 cities remained the same level.”

“Comparing with the previous month, the sales prices of second-hand residential buildings decreased in 38 cities, while that of 19 cities remained the same level. Number of cities with decreasing chain indices rose by 13 in October as compared with September. The month-on-month increases were less than 0.5 percent for the cities with increasing price.”
…and this is having an effect on the growth rate of investment in real estate assets…


…and inevitably upon the rate of growth in industrial production…



Perhaps, Jim Chanos is right with his bearish view of China’s housing and construction market?  Whether, it is going to be a hard or soft landing, it doesn’t look like the time to pile into commodities.
...and for existing homes...