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Erik van Dijk
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Hi! I am Erik L. van Dijk, principal at LMG Emerge. LMG Emerge is an internationally-operating institutional investment consultant with offices in the Netherlands and at Mauritius. Our clients are pension plans and other institutional investors, family offices and HNW individuals. In close... More
My company:
LMG Emerge
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LMG Emerge - New Economies
My book:
Asset Pricing and Risk in Emerging and Frontier Markets
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  • Flawed Investor Behavior; A Random Walk Down Today's Financial Newspaper


    After reading the newspaper this morning, I decided to write this reflective piece about private investors (and maybe for that sake: also those professional investors who do not qualify as 'Best-of-Breed'). It felt like a Random Walk Down the Newspaper (slightly modifying the title of a famous investment book) which explained quite a bit about a lot of problems investors are facing today. The interesting part of it is that different components of what we write below are not  from one big, major article in that newspaper but they are linked to different articles. Some that were investments-related and others that aren't.

    It was already known and documented in tons of articles including scientific books like Prof Burton Malkiel's A Random Walk Down Wall Street that it is very difficult (even for professional investors) to beat the market index structurally and consistently. But it is also true that around this average there is some sub-categorization in groups going on. The US Defined Contribution market that allows individuals to take care of their own pensions is a fantastic pool of information about the investment style and performance of private investors. More information about that style will follow below. What is important now, as a basic premise, is that studies seem to conclude that (whereas private investors always - at parties, on their websites or in their well-known discussions with friends, family and neighbors - proudly present their own investment successes) the group as a whole underperformed. This implies that - so as to reach the average net return for the market as a whole - there are others who outperform. And I am not talking about those with non-diversified, 'lucky' one-shot portfolios then. No, I mean outperformance over a couple of years, with stable risk profile and realistic returns. There are best-of-breed grandmaster investors who create well-structured portfolios of outperforming products so as to  achieve this result.

    Burton Malkiel: Wall Street's Randomness Makes the Investment Game Complicated.

    LMG: But that doesn't imply non-existence of a sub-group of grandmasters and a sub-group of under performers.

    Early Adopter Bias 

    One of the problems is that different asset classes and products outperform at different times. So long-term investment success is about getting the averages right. Not about going all the way with one or the other temporary success. And that was exactly one of the main problems. Today, Hollands financial newspaper quoted a scientific study by scientists from the universities of Groningen and Maastricht who surveyed a representative group of Dutch investors. Compared to investors in most countries on this planet, Dutch investors are reasonably educated, reasonably cosmopolitan in their orientation, reasonably exposed to (international) investment news, acting in a market with reasonable cost levels, quite well regulated etc. We do therefore not believe that the bias is typically Dutch. Result of the study: private investors - even relatively experienced ones - had a tendency to be so-called early adopters . Normally it is good to be not too late in a cycle, but being an early adopter with a new product is not the same as riding the tide and being an early adopter in a new cycle for an existing security within a well-known traditional asset class.

    EarlyAdopter: Testing the waters before the others dare to do so.

    Receiving awe for it: but was the water safe?

    There is a kind of early adopter premium which brings them awe and admiration from other investors. However, very often these new products are structured products created by financial institutions in an effort to transfer risks from the bank or insurer's balance sheet to the buying investor. Or products especially created to fulfill the needs / new demand for a 'hot' niche in which case performance and quality are of lesser importance than having something to sell. 'Turbos', 'Teak wood funds', 'Trackers', 'Guarantee Products', 'Shipping Ventures with positive tax treatment', 'Green Funds' you name it. There is so much. Most of the time the early adopter investors do not even completely understand what they are buying. And almost always these innovative products are added to portfolios that from the start weren't even neatly structured or diversified as far as standard, traditional asset classes are concerned. And in almost all cases these products are offered by parties that did not establish themselves a reputation as 'Best-of-Breed' in this new asset category, but simply offered it being the  bank or insurance firm with which the investor had a relationship already. You could even say that to some extent they were misusing their fiduciary relationship. But then again: looking at the early adopter premium one could also say that these investors wanted to be fooled because they derived non-monetary gains from buying these products. 

    Is it therefore surprising that both these products and the buying investors were underperforming? Not really.

    Fiduciary Problems

    But why did these investors buy those products? Partly because of the non-monetary utility derived from being able to receive awe from other private investors. 'Waw, you are so good at this stuff. I didn't even know that this product existed!' or 'It is such a complicated product. Amazing that you already understand it!' and similar lines are a kind of bonus to the admired early adopter. And in an industry in which performance analysis and keeping track of performance over time are already underdeveloped when it comes to most professional product providers and their institutional clients, it is not a surprise that the admired early adopters get away with things the moment those products do not deliver. Solution: you simply stop talking about it, and instead spread the gospel about some other product that you were successful with and/or think to be successful with in the future. The trend followers will do what they always do: follow.

    But, OK, what about the early adopters themselves? They are not crazy, are they? Why did they and do they continue to buy these products? In another article in the same newspaper we got our answer. Stefanie Tzioti of the Erasmus University Rotterdam received her Ph.D for a very interesting piece of research. What she did in her experiments was the following: she provided the participants in her experiments with choices between i) types of wine; ii) investments in stocks or bonds; iii) this or that mobile phone offer. In the first part of the research participants could make the choice themselves, based on a concise information package about the choices. In the next stage of the research they were offered additional help by advisers. They did not only receive the additional information, but were also shown pictures of the advisers and some information about them.

    Result: the power dressing guy with the big car (or better phrased 'right car'; there was also something going on like specific brands of cars, watches being more expensive but 'wrong'!) was more often believed than his more casual 'guy-next-door' colleague. This is something banks and other financial firms know quite well. No matter how lousy their back office situation (compare news yesterday about insurer Aegon who some 10 years ago acquired Scottish Equitable in the UK and continued to be sluggish about a known back office problem to such an extent that there are now more than 200,000 (!) clients that cannot be traced due to problems with addresses) or the actual quality of a financial product, in the end they still seem to be capable to impress their clients with their size, wealthy looking front and branch offices and power dressed sales staff (with or without long legs; male or female). In other words: fiduciary relationships  were often more about 'form' than about 'content'.

     There were however other factors at stake as well. 'Age' was also a positive factor, and so was 'content'. So, genuine, non-power dressed people of a certain age with great content were able to compensate their non-power dressing disadvantage. But still: it was clear but sad that 'content' seemed to be everything but the most important of these factors.


    Power Dressing instead of Power Results: Form matters at least as much as Content

    The Definition of Risk 

    Risk is a far more complex and less-understood concept than Return. But both are of equal importance when it comes to creating a good investment portfolio. Risk is a derivative concept of a return distribution. But there are types of risk: we can use 'volatility' which is basically the standard deviation of the return distribution. We can also look at 'beta' or market risk which analyzes how much - on average - a security will go up or down when the market index goes up or down one percent. We can also look at 'Value-at-Risk', 'Downside Risk' et cetera. There are a lot of indicators. And even if you incorporate them in a structural manner in your decision making process, so that you can analyze risk and return in some integrated fashion you are not there yet.

    There is a difference between Risk at the security level and Risk at the portfolio level. It was Dr Harry Markowitz (Nobel Prize Laureate 1990) who taught us about this difference when he developed his work on Modern Portfolio Theory in the 1950s (followed by equally important work by another Nobel prize Laureate Bill Sharpe in the early 1960s). When going from the individual security level to the overall portfolio level  things change because of a new dimension that is now added to the investment problem: 'correlation'. 'What is the relationship between the various components within your portfolio?' Over the last 10 years I have worked with Dr Markowitz on a new asset allocation framework based on i) a more efficient integration of bottom-up, security and asset class level information and top-down market information (including correlation analysis); and ii) some of the basic principles laid down in his earlier work. Prof Kritzman of MIT performed a series of tests that confirmed the value of this new approach. The approach was not really rocket science, just a careful integration of all factors involved when taking investment decisions and its results are therefore more indicative of the problems others have with the treatment of risk.

    Harry Markowitz, often misunderstood or misinterpreted: No Power Dressing, but Enormous Content when it comes to Risk.

    But back to the difficult relationship between private investors and the concept of risk.


     Investors are not just relatively bad in getting their partial or individual security risk calculus right, they are even worse when it comes to getting the correlations and portfolio structuring right. To some extent this is understandable. In an earlier piece that we wrote for the first issue of UK asset allocation journal Portfolio Institutional, we explained that regime shifts imply shifts in correlations and not just that: in different regimes return patterns seem to change as well. That complicates things tremendously.

     We had to think about these aspects when reading yet another article in today's financial newspaper, again totally coincidental that it ended up in the same issue. But it illustrates the intensity of the problem and its many different faces. It was a piece about private investors and their visions about markets in 2011 and beyond. It was based on a survey by a prestigious Dutch, independent market bureau. The pool of participants was a representative group of private investors with portfolios in excess of Euro 50,000 each. That 50,000 cut-off rate is important, because it is the hurdle rate applied by the Dutch regulator to distinguish between those private investors that are small (and who therefore need to be protected) and those that are big enough to assume that they can shop around and know what they are doing. An important distinction of course for providers of investment solutions, because for minimum investments below 50k you need a hard-to-get private investor market license and above 50k you don't.

     This is therefore the group of private investors who supposedly knows what they are talking about. Here are some of the most remarkable results of the survey:

    1. Private investors in the Netherlands are currently considering the US market as the most risky one. Only the African market was considered to be of 'similar or higher risk level'.
    2. The bulk of investors is not convinced that the crisis is over. Only 21 percent is willing to reduce the size of their savings account and invest more in equities. So even with today's relatively low interest rates, fear is still there. And market momentum of the last few weeks is the result of actions by a few (when it comes to private investors) and institutional investors. But in the latter group pension plans were relatively quiet due to problems with coverage ratios.
    3. The so-called Home Bias is immense. Almost all investors over-invest first and foremost in their home country (in this case the Netherlands), and within the foreign component of their portfolio Europe is highly overrepresented. 
    4. Emerging Markets are popular when it comes to talking about them. But when looking at portfolio allocations, either current or planned, private investors are far less enthusiastic than the big banks who advise them. Only 13 percent indicates that they want to invest more in China during the next 6 months versus 24 percent who want to expand their Dutch holdings when interest rates remain low. And when replacing China by some lesser known or smaller, less spectacularly growing Emerging Market things are even worse.

    A more than remarkable result. Whatever will happen in the world, if anything, the US market is not going to be the most risky one. And definitely not something comparable to Africa. And actually - with us being positive about the long-run prospects of Africa - don't forget to integrate return and risk at both the individual security and portfolio level when taking decisions. The Home Bias is an indication of cultural and news intensity related mistakes most investors seem to make all the time: 'if I know a market better, because I live in or close to it my risk is lower'. They forget that their investment outcome is a function of the quality of their information vis-a-vis other participants in the investment game. When there is far more information available about a specific market, this does not translate automatically into lower risk and/or higher returns. It is about differential information vis-a-vis the competitors in the market place. And then I even forget to what extent available data is really information. Most investors don't really understand that distinction, thereby mistakenly interpreting their excess data for the home market as priced information.

      Basically: what is very clear from this feedback is that investors extrapolate. The uncertainty about the US is nothing more or less but an extrapolation of Global Crisis related factors ('didn't it all start in the US with the sub-prime crisis and bank problems?') and fluctuations in the Dollar-Euro exchange rate. But if you want, you can hedge currency risks, and when looking beyond the financial sector the US economy is so much more. In market value it is still more than 30 percent of the world. And well-diversified in terms of industry distribution. No way that this market will be riskier than the not-so-well-diversified economies of Africa with all their political risk and corruption as a not-so-welcome add-on. OK, less risk will translate into lower return, but that is another story.

     The relationship between private investors and the concept of 'risk' remains a troubled one.

     Extrapolation/Trend followers Bias

     When analyzing studies about the behavior of private investors (and actually the not-so-good institutional investors as well), it becomes clear that they are trend followers while at the same time being early adopters (see above).

     When it comes to existing products, they want to buy after receiving confirmation that something is doing well. Some want more confirmation, others less. But all wait for confirmation signals. That explains why it is so much easier to sell Morningstar Five and Four Star Funds. It also explains why stocks with a good looking share price development over the last year experience continued 'momentum'. But sooner or later this trend following translates into 'buying expensive'. If you wait for confirmation, you actually skip the security in its cheapest phases. Nothing wrong with one or two confirmations, but when combining this with the risk analysis in the previous paragraph it becomes clear that the bulk of people wait for a lot more confirmation. They will start thinking about something  after that something had a fantastic ride already. And then obviously, with the chance of disappointments going up the more expensive you bought, sooner or later it translates into buying high, selling low.


    The Private Investor Trendfollowing Cycle



     Is it therefore - when just browsing through today's newspaper - strange that tons of investors under perform? Not at all. Is it strange that what we wrote here for private investors does also apply to dozens of institutional advisers and / or large financial institutions offering products to private investors and/or not-so-well-informed institutions? Again: not at all. In the end the bulk of people - even professionals - is a private person as well. With all the flaws that come with it. And it is therefore not surprising that Behavioral Finance has gained so much in importance during the last 20 years.

     But the academics were wrong to translate this into the conclusion that there are no grandmasters in this game. You can conclude that they are hard to find, sure. But the same applies to any competitive sport, because that is what investing is. There are always far more lousy amateurs than excelling stars. Investment performance of investment managers has to be disentangled into several components


    • Skill

    • Market

    • Peer Group

    • Other Relevant Factors 

    before you can distinguish between those that most likely did something 'special' and those that were just plain 'lucky'. That does not only apply to finding the best advisers. It also applies to your own portfolio performance. But as long as there is no structural, state-of-the-art performance analysis available investors and not-so-good advisers will often be trend followers with all the flaws written about above. And in the mean time the true investment grand masters will continue to struggle with ways how to distinguish themselves from the poor and mediocre. And even when they do show the value of their 'content', they still have to fight against the power dressed marketing managers of huge financial institutions with great front offices and branches all around the world.

     When looking at the possibilities of approaches like our 'Best-of-Breed' concept for manager selection and our cooperation with UK database provider Camradata (one of the largest institutional databases of performance of investment procucts vis-a-vis their peer group), we believe that increased transparency requirements, the role of the internet in general and the increased speed and depth of information dissemination will help things to improve. And that is good news for both private and institutional investors. But there is still a long way to go.

    Disclosure: I have no positions in any stocks mentioned, and no plans to initiate any positions within the next 72 hours.

    Additional disclosure: We are an institutional investment adviser focusing on Asset Allocation, Manager Selection and Emerging Market advise to institutional clients only. As part of our Money Flow Analysis we do also analyze the behavior of private investors.
    Dec 18 9:28 AM | Link | Comment!
  • Geo-political and economic shifts in Russia-Western Europe relations create opportunities in Emerging Europe


    We start this note with a picture of one of the most important elements of the European Infrastructure: the pipelines that connect Russia with Western Europe. With gasoline prices in Europe hitting record levels again, we felt that it was good to use the attached article (see below) from the excellent Frontier Markets blog for this note.

    It is of course not totally coincidental that we wrote our previous entry on Gazprom, the Russian energy powerhouse, and one on our Facebook page on the fact that Russia was awarded the World Championships Football in 2018. Add to that the fact that the country will also organize the 2014 Winter Olympics in Sotchi and you know that a lot of good infrastructure dynamics will be going on during the next 3-5 years and beyond. Another indication is the fact that Sotchi will be on the calendar soon as a new spot on the Formula 1 car racing map. Gossip even states that it was Vladimir Putin himself who translated his personal love for motorsports into sponsoring by the Russian state after Russian driver Petrov's great performance in the last race of this season in Abu Dhabi. It was to quite some extent Petrov's driving that ensured that Vettel and not Alonso took back home the world championship.

    Eastern Europe = Central Europe 

    Dynamics characterized by one thing: sufficient money to create an infrastructure boom in Russia. If you add to that ongoing tensions in the Middle East and European suspicions about Asian domination, it is not totally impossible that old geopolitical enemies will find each other: Western Europe / EU and Russia. OK, this will not be a marriage of passionate love, but it will be one of two parties who need each other. They might even continue to live separately. Or at least meet each other often at neutral territory. And that neutral territory between them is Central Europe, often called Eastern Europe in the past.

    Eastern Europe consists of three parts according to the Frontier Markets blog:

    1. A central core consisting of Poland, Czech Republic and Slovakia where the banking system is already developing and proximity to Western Europe has already translated to some substantial integration. Budget deficits and debts are still worrying (and so are Polish actions against the second pension pillar), but all in all - helped by substantial investments from Western European parties - these countries are already transitioning. Large infrastructure investments go hand-in-hand with positive stimulus derived from industries like logistics and transportation (just drive through Europe and it seems that all trucks are from these countries!) and Polish workers flocking labor markets in Western Europe offering their services for far less than their Western European counterparts, followed by a weekend drive back to their country where they are then relatively rich citizens who have something to spend.
    2. The Baltic States. Still struggling with the aftermath of the Global Crisis, but we believe that there are some indications that the fact that these states (especially Lithuania and Latvia) have invested heavily in education over the last 10-20 years will translate into opportunities in IT, Banking and other industries heavily dependent on higher education. The proximity to markets in Scandinavia - where labor costs are high - has already led to the first large foreign direct investments by corporations from Sweden and Finland active in these sectors.
    3. The Balkans (including Hungary and the Ukraine). Still struggling and trying to ignite positive fire. But take a look at our map. The likelihood of these - now cheap - countries not benefiting from an increased interest in increased West-East lateral business and political contact in Europe is highly unlikely. The fact that they are mainly financed by now expensive loans from abroad a problem? Well, might be in the short run, but then again: taking into account their relative size compared to Western Europe and Russia we do not believe that this will be a big problem. Short-run tension will - as so often - translate into low valuations and low valuations are basically something that makes those countries interesting in the longer run for those who have a longer run agenda.

    And we believe that the longer run agenda in Europe will be one of increased interest of Western Europe in Emerging Eastern / Central Europe. And the other way round? The Russians know about their linkage with Western Europe and interest in German exports. LMG believes that quite a few of the Eastern European negatives and low valuations do therefore translate into opportunities for Emerging Markets investors.

    Click here to see the original Frontier Market Blog article on Eastern Europe

    Dec 09 8:33 AM | Link | Comment!
  • Adding Value by Integrating Asset Allocation in a Coherent Investment Framework: The Importance of Getting the Correlations Right

    1.       Introduction

    Brinson, Hood & Beebower (NYSEMKT:BHB) wrote a seminal paper in 1986 in which they derived that the bulk (80-90 percent) of overall investment performance is the result of asset allocation decisions. The paper almost became a gospel in the academic world, but in the practitioner world it was often mentioned in research publications by large investment management firms but it was hard to find out to what extent they had changed their investment approach as a result of it.

    BHB used a time-series approach and later work by Ibbotson & Kaplan (2000) and Xiong, Ibbotson, Idzorek & Chen (2010) showed that the BHB conclusions were to a large extent related to the use of this approach. Overall market movements dominate total return time series. But investors can and should also be compared cross-sectionally. Ibbotson & Kaplan (2000) and Xiong et al (2010) derive that the relative importance of asset allocation decisions doesn’t come anywhere close to the 80-90 percent suggested by BHB and their addicts. It is ‘at best’ 50 percent.

    Is this a downgrading of the importance? We don’t think so. Look carefully at what has been done here in the newer studies. The newer studies look at the overall investment process – both top-down and bottom-up – of investors in an integrated manner, whereas BHB looked at just one aspect. We believe that the result of the integrated studies and correct derivation of asset allocation importance will just do that: make asset allocation more important in a truly integrated, active framework.

    In paragraph 2 we will look at this integrated framework in an ‘ideal’, rational world and show how problems with the important correlation factor led to so many disappointments and even catastrophes witnessed in practice. And that is already before taking into account the existence of irrationalities and other behavioral factors, a topic we will address in a future piece. Paragraph 3 concludes.

    2.       Integrated Asset Allocation in an ‘ideal’ world

    At any point in time we have to take portfolio decisions (not doing anything is also a portfolio decision!) based on historical information and expectations about the future. Quantitative investors use some kind of ‘model’, which is always ‘just’ and approximation of reality. Fundamental investors do often seem to look down on ‘quants’ every time the latter have gone through some kind of bad period for their style, explaining everyone that you cannot capture the world in a model. However: they seem to forget that they are also using a model, albeit one that is far less explicit. Sometimes this lower amount of rigor works to their advantage in that the fundamentalists seem to be able to cope with regime shifts quicker and better. And that attention given to potential regime-shifts is important as we will see later in this article.

    On the other hand: without a rigorous and transparent analysis of your own mistakes it is hard to gradually adjust your investment process and approach over time. In other words: both approaches do have a certain appeal and both have certain flaws. One is good in picking up the major shifts that happen once in a while, whereas the other is better in adjusting to long series of smaller adjustments of markets. Whenever your portfolio size does allow you the incorporation of more than one manager for a certain sub-component of it, it might be wise to diversify between the two investment styles.

    The overall ‘ideal’ asset allocation and portfolio composition are a function of:

    ·         Expected Returns

    ·         Expected Risks

    ·         Expected Correlations between portfolio components

    ·         The investor’s Risk Profile

    ·         Guidelines provided by the investor’s ALM study

    We will not address the issue of ALM and Risk Profile in this paper and assume that they have been tackled by the investor. But research about Pension Fund Governance and risk profiles of Boards of Trustees – as opposed to that of individual decision takers – show that this is already quite an issue in-and-of-itself. And even when getting the numbers right when it comes to the translation of individual to collective risk profiles, one is still faced with the problem that recent research has confirmed what we did already know: risk preferences do contain all kinds of linkages – both linear and non-linear – to variables like gender, age, wealth, income, education and culture. But let’s for now assume that all of this has been tackled and that there is agreement on the ALM and risk preference.

    When looking at Return and Risk we need to distinguish between short-term and long-term expectations and bullish versus bearish market climates. Depending on the asset class we are considering, outcomes will be more or less sensitive to these distinctions. And when it comes to Risk, we also need to distinguish between various types of Risk. The ‘ideal’ framework would incorporate all these elements and then, using information about correlations between securities / asset classes assign to them the optimal portfolio weights. It may already sound like a lot of work, but technically it can be done and most professional organizations do at least have some kind of more or less structural framework to do it (which is not the same as saying that they are adding much value by doing it, because in the end it is not just about the framework, but also about the numbers that you plug into it).

    The next step would then simply be to make use of the ‘only free lunch in investing’: proper diversification based on incorporation of the right correlation coefficients within the framework. Markowitz (1952) received the Nobel Prize in Economics (1990) for his work on the framework. And the fact that it took so long – and even longer – for many practitioners to really start using it was related to the fact that Markowitz (1952) only provided rough guidelines for the various necessary steps discussed above. Markowitz used standard deviation or volatility as his risk measure, but knew that semi-variance might be at least as interesting when market returns are not normally distributed. In other words: he described the mean-variance system understanding that it was not the whole thing. Yes, it was the whole thing in terms of approach, but the proof of the pudding is in the eating and the cook (read: investor) did still need to add some additional flavors and/or change the topping. Another problem: there are far more asset classes/country(or region) combinations than today’s computer power can handle in a true mean-variance optimization. Markowitz-van Dijk (2003) derived a heuristic labeled ‘near optimization’ that according to Monte Carlo tests by Kritzman et al. (2007) does a good job. The optimization technique outperforms known alternatives (e.g. ‘rules of thumb’-based decision techniques) for large numbers of investment opportunities and comes extremely close to a ‘real’ optimization when the numbers of investment alternatives is small enough to do a real one and compare things.

    What does that mean? In terms of framework the ‘ideal’ is there. But real-life investors have made terrible mistakes when plugging in the numbers. Take for instance correlation coefficients. Correlation coefficients are not stable between asset classes. Even more so: they are not stable when looking at securities within an asset class! Correlations tend to move toward one in turbulent periods. This translates into huge diversification problems, especially in periods when it is needed most. Longin and Solnik (1995, 2001) have found that correlations are highest in turbulent, high volatility periods. If we add to this that correlation coefficients are creeping upward due to ongoing globalization, we need to do something if we want to create optimal portfolios with the return-risk ratios that we are looking for. And this is especially important at a time when demographic factors are working against some of the largest institutional investors: Western pension plans that represent an overall value of more than $ 13,000 trillion in assets under management.

    So what to do? Give up? Resign? Of course not: three ‘solutions’ will help. First of all, the importance of Alternatives within the overall portfolio and asset allocation will increase. Long/short style portfolios will help mitigate the risk of increased diversification opportunities. But they will only do so when investors will learn that long/short and other hedge fund managers are no geniuses in general. Just like in any other asset class proper due diligence is important. I.e. a due diligence that incorporates asset class returns in a screening framework so as to distinguish between ‘true skill’ (as a result of selection), ‘technique’ (performance due to their going long and short) and ‘luck’.

    Second, work by Bernhart, Hochst, Neugebauer, Neumann & Zagst (2009) shows that working with a so-called regime shift model does improve returns while reducing overall portfolio risks. In this approach – also integrated in the LMG asset allocation model – returns, risks and correlations are separately calculated for high volatility and low volatility environments. One can use the Chicago Board of Options Exchange VIX index to distinguish between the two environments. Relevant factor weights and return, risk and correlation forecasts are based only on the historical observations of the regime that one is studying. In other words: instead of one model with weights based on the overall historical sample you have two sub-models[2]. Based on what is going on with the VIX you can then decide which one of the two derived forecast sets and accompanying asset allocation you will use. Table 1 shows the estimated added value of the regime-shift approach vis-à-vis the static framework.

    Table 1; The Value of Incorporating Regime Shifts in an Asset Allocation Framework

    It is remarkable to see how the regime-shift model found the following ‘high volatility, turbulent’ regimes and how it adjusted its allocation based on that fact:

    ·         1987 The Black Monday crash and its aftermath

    ·         1990 The Gulf War and its aftermath

    ·         1998 The Russian Ruble Crisis

    ·         2000-2003 The Burst of the .com Bubble

    ·         2007-2009 Global Financial Crisis

    ·         (not for the US but captured for Europe) 1997 Asian Financial Crisis

    And of course, this approach is not magic but it helps a lot. ‘Found’ does not mean that you shift from bullish to bearish exactly at the time of the big negative event. Most of the time shifts were made too early, because volatility levels creep up before the big clash. But it is definitely a considerable improvement. The low-risk investor does probably improve his returns by around 0.5% annually and the high-risk investor by somewhere close to 1.5%. And this improvement is accompanied by lower risk levels.

     But it is not only these missed regime shifts that went wrong when looking at standard investor’s approaches to their overall allocation of assets and the extent to which this could be attributed to correlation coefficients. There is a third factor that one could incorporate to improve on existing approaches. Haber & Braunstein (2009) have shown that the practice of using longer-term, allegedly stable correlations in optimization frameworks does also lead to another problem irrespective of underlying volatility regimes. Correlation coefficients are often presented by taking some longer, historical period with return and risk figures often presented over a set of shorter (sub-)intervals as well. However: what investors really care about is future correlations. The authors analyze random (!) samples of 180 monthly return observations to simulate 15 years of return patterns. Low or no correlation between two asset classes over a longer period of time might be the result of a negative correlation in good periods (bull markets) and a positive correlation in bad periods (bear markets) or vice versa. The average correlation is indeed low: but we will never be happy with the results when managing an overall portfolio on this basis when going forward knowing that we will be monitored over relatively shorter time intervals as well! Therefore: we should pay attention to sub-periods and that is exactly what the regime shift approach is doing based on a linkage with volatility. But correlation patterns might also be linked to other factors.

    In chart 1 we present Haber & Braunstein’s results of an experiment in which they calculated the 3-, 2- and 1-year correlations between their 180-observation series of monthly random returns. They repeated the experiment 100 times and the results are shocking.

    Chart 1: Significant Correlations do even play a role in Random Long-Term Patterns!

    If we then keep in mind that shorter-term, more recent correlations are probably more relevant than longer term information about let’s say the correlation 15 years ago in a setting that is not truly random, we see that the standard approach can also go terribly wrong even when we are not in a regime-shifting situation where we go from high to low volatility environments or vice versa. An alternative approach in which we use time-weighted correlation estimates with time-weights derived in such a way that recent period estimates get a higher weight might further help improve results.


    The standard framework for rational decision taking within the context of asset allocation is more or less there. However, as always, it is garbage-in, garbage-out when you do not get your numbers right. Just like investors have always spent more time on bottom-up security selection and manager picking than on top-down asset allocation, they have also spent more time on return predictions than on risk management and measurement. The latter includes correlation analysis. Within a proper asset allocation framework correlation analysis is not less important than return, beta, volatility or currency risk. Especially now that we are moving into a world that – through globalization – will make free lunches less easy to find, it is important that investors start taking correlation a bit more seriously. In this little article we presented some thoughts on what can already be done in terms of future as well as current research. The Markowitz-van Dijk (2003) heuristic shows that an integrated approach in which the various components of an optimization are incorporated in a pragmatic way can add tremendous value. It is our belief that correlation analysis is probably the first area that investors should look at when trying to improve their asset allocation decisions. By doing so, they can improve their return-risk trade-off substantially: depending on your risk profile incremental returns of 0.5-1.5 percent per annum seem to be realistic. Another area is related to non-rationality in international asset allocation decisions. Research has shown that cultural factors have lead to home and foreign biases. With the quest for new opportunities in a globalizing world - characterized also by increasing importance of Emerging and Frontier economies – being much more international than ever before, we will address that aspect in our next contribution.


    ·         Bernhart, G., S. Hochst, M. Neugebauer, M. Neumann & R. Zagst, Asset Correlations in Turbulent Markets and their Implications on Asset Management, Working Paper TU Munich, 2009

    ·         Brinson, G., L.R. Hood & G.L. Beebower, Determinants of Portfolio Performance, Financial Analysts Journal, 1986

    ·         Haber, J, & A. Braunstein, Correlation of Uncorrelated Assets: Near-term Issues, Working Paper Allied Academies International Internet Conference, 2009

    ·         Ibbotson & Kaplan, Does Asset Allocation Policy Explain 40, 90 or 100 Percent of Performance?, Financial Analysts Journal, 2000

    ·         Kritzman M, S. Page & S. Myrgren, Portfolio Rebalancing: A Test of the Markowitz-van Dijk Heuristic, MIT Working Paper series 2007

    ·         Longin, F. & B. Solnik, Is the Correlation in International Equity Returns Constant?, Journal of International Money and Finance, 1995

    ·         Longin, F. & B. Solnik, Extreme Correlation of International Equity Markets, Journal of Finance, 2001

    ·         Markowitz, H.M., Portfolio Selection, Journal of Finance 1952

    ·         Markowitz, H.M. & E.L. van Dijk, Single-period Mean-Variance Analysis in a Changing World, Financial Analysts Journal, 2003

    ·         Xiong, J.X., R. Ibbotson, T.M. Idziorek & P. Chen, The Equal Importance of Asset Allocation and Active Management, Financial Analysts Journal, 2010

    [2] When we talk about ‘model’ here we mean the investment approach chosen for the integrated framework including asset allocation. Fundamental approaches do also fit this description, albeit that their idea of a ‘model’ is less tangible.

    Disclosure: ACWI overweight, long; structured position VIXX-XXV speculating on gradual decline in volatility during 2011-2013
    Nov 13 8:18 AM | Link | Comment!
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