Zweimal pro Woche - Kostenlos per E-Mail. Jeden Werktag neu - Kostenlos per E-Mail.

Der Newsletter ist selbstverständlich kostenlos und kann jederzeit abbestellt werden.

Bausteine der 3. Asset Allocation Generation

Investoren stehen immer häufiger ratlos vor der Frage, wie sie ihre Portfolios in Zeiten finanzieller Repression und steigender Tail Risks diversifizieren können. Markus Schuller (Panthera Solutions) skizziert gemeinsam mit Dr. Rania Azmi (Advisor großer SWFs in Middle East), wie mittels 5 praktischer Bausteine die sich nun ausprägende, 3. Asset Allocation Generation angewandt werden kann. Markets | 27.12.2013 15:00 Uhr

    1. The Evolution of Asset Allocation Generations

    With his dissertation ”Portfolio Selection“, US economist and Nobel laureate Harry M. Markowitz did a big favor to the financial industry (Markowitz, 1952). He introduced the Mean-Variance-Optimizer as core component of the Modern Portfolio Theory (MPT). The industry welcomed the single-factor, single period tool as its theoretical foundation and practical implementation allowed a new set of business models.

    Markowitz model has been simple enough to teach it to business school students and complex enough to impress investors with efficient frontier-based allocation explanations for the last 5 decades. To be clear, Markowitz´ model marked a milestone in professionalizing the asset allocation process by defining and measuring risk and return as well as how to combine assets through a repeatable, standardized process. It acted as starting point for a series of complementary single-factor, single-period models like the Capital Asset Pricing Model-CAPM (Sharpe, 1964). The Efficient Market Hypothesis-EMH (Fama, 1970) added a contextual framework for a rationality-driven world and completed the triumvirate of MPT-CAPM-EMH that laid the theoretical foundation for first generation of asset allocation strategies- 1GEN (1950-2000). The derived 1GEN strategies like Balanced Portfolios (60/40 Portfolios), Long-Only or Buy-and-Hold led to the rise of the mutual fund industry; a success story that still manages about USD 26 trillion worldwide (ICI, 2013). However, the problem is as follows: of the three involved parties, mutual fund manager, mutual fund distributor and mutual fund investor, only the first two benefit from the success of this segment. The investor pays high fees for insufficiently diversified portfolios and an unfulfilled promise of alpha exposure (Carhart, 2002; Gottesman, 2013).

    Driven by an emerging insight of insufficient diversification effects of first generation basic assumptions and models, institutional investors began to add further asset classes and strategies to their classic balanced portfolio allocation. The second generation arose (2GEN). Multi-Asset, Long/Short Equity and Risk Parity strategies serve as an example for the widening alternative scope during the 2000s. Multi-factor, multi-period models, academically developed during the 1970s and 1980s, were used as quantitative optimization techniques for this second generation. It shares most of the basic assumptions with 1GEN models while trying to overcome their limitations. Exemplary, econometric methods like autoregressive conditional Heteroskedastic models- ARCH (Engle, 1982), Generalized Autoregressive Conditional Heteroskedasticity-GARCH (Bollerslev, 1986) and Copula (Nelsen, 1999) methods can be named.

    Despite the efforts, those optimization techniques, combined with alternative asset classes, could not buck the trend of increasing correlations of holdings in portfolios. Especially hedge funds began to suffer from what we call “mutualfundization”, a classic main-stream-effect as a result of hedge fund investments turning from a High-Net-Worth-Individual (HNWI) play into an investment alternative for institutional investors (Asness, Krail, and Liew, 2001).

    Overall, 2GEN is suffering of the following problem: on the basis of congruent assumptions with 1GEN, risk remains defined as volatility measure to minimize correlation between allocated assets. Even when including more sophisticated mathematical modeling, supported by computer-programmed algorithms, volatility based risk perception implies significant blind spots. Exemplary, VaR-optimized portfolios (Schuller, 2012) or Risk Parity portfolios (Schuller, Kula, 2012) can be named as part of this undesirable development. Furthermore, due to a dynamically encompassing globalization and an increasingly heterogeneous definition of asset classes as a mix of strategies, structures and geographies, the potential portfolio impetus of those blind spots increases.

    1GEN & 2GEN Summary (Jones, 2011)

    - They ignore the strong evidence of regime dependence, regime persistence, and time-variation in long-term asset returns.

    - They assume rebalancing is the best form of risk-management, ignoring a role for hedging strategies or bubble identification as alternative risk mitigation approaches. Besides ignoring the costs involved in any rebalancing of portfolios.

    - It assumes stable stock/bond correlations and stable diversification benefits – it ignores the fact that stocks and bonds are positively correlated in 2 out of 3 macro states.

    - Risk weights are not the same as dollar weights – in a 60/40 mix of stocks and bonds equities account for around 95% of portfolio variability.

    - Lengthy and severe drawdowns are commonplace.

    - The 60/40 portfolio was ill-equipped to handle the stagflationary macroenvironment of the 1970s, a period bearing similarities to today.

    - Most alternatives are short systemic liquidity risk, and so can compound losses of a equity-centric portfolio in a crisis (high “stress beta”).

    Although empirical evidence suggests otherwise, Modern Portfolio Theory and its descendants are still dominating the investment committees of institutional investors. Especially for defining the risk budgets per asset class during the Strategic Asset Allocation (SAA) process, the traditional approaches enjoy great popularity. If nothing else, since the Great Recession now followed by a Financial Repression in the developed economies, institutional investors do not know how to get any further as they recognize the limits of traditional asset allocation generations.

    Given the growing level of despair, institutional investors are increasingly accessible to reason. An example: The Portfolio Whiteboard Project (Rittereiser, 2013) brought together the next generation of institutional investment leaders with asset managers to define an asset allocation model for the future. The group agreed that the financial crisis had seriously undermined the value of Modern Portfolio Theory, yet MPT continues to dominate for manager selection and asset allocation frameworks „How can we unlearn a lot of that?, asked one investor.

    In this paper, we intend to answer this question by proposing practical building blocks for a new asset allocation generation.

    Continue reading:

    Part 2: Third Generation Asset Allocation

    Part 3: 3GEN Implementation Support

    Part 4: Twelve 3GEN Imperatives for Practitioners

    Authors


    Dr. Rania Azmi

    Dr. Rania Azmi
    Dr. Rania Azmi
    Rania Azmi is an adviser to one of the world’s largest Sovereign Wealth Funds. She enjoys a first-hand experience investing in Middle Eastern markets as well as global financial markets. Azmi enjoys 13+ years of private/institutional investing experience, and she believes that the best theory has no purpose unless it is applied in a practical manner. Azmi was chosen by aiCIO magazine as one of the forty under forty brightest stars in institutional investment. She received her Doctorate in Investment Decision Making from the University of Portsmouth and is the author of Making Investment Decisions for Portfolios (Cambridge Scholars, 2013).

    Azmi is also an activist for women's positions in business, politics, and society. She has spoken for the World Bank on gender and economics, and was awarded the Google Prize for "Most Interesting and Creative Work." Most recently, she was designated an Egyptian Woman of Influence globally by the Women Speakers Association and contributed a multidimensional model in preparation for the new generation of the United Nations Millennium Development Goals beyond 2015 in support of women.

    Mag. Markus Schuller, MBA, MScFE

    Mag. Markus Schuller, MBA, MScFE, Panthera Solutions
    Mag. Markus Schuller, MBA, MScFE, Panthera Solutions
    Markus Schuller is the founder of Panthera Solutions, a Strategic Asset Allocation Consultancy in the Principality of Monaco. Panthera Solutions provides access to the third generation of portfolio optimization techniques to European institutional investors. Panthera´s monthly macro-newsletter (PSC) reaches 10.000+ finance professionals in Germany/Switzerland/Austria and is regularly published in German quality newspapers.

    Markus has over 15 years experience in trading, structuring and managing standard and alternative investment products and was working at banks and asset management companies prior to Panthera Solutions. He graduated from his Master in Economics at Johannes Kepler University and University of Pittsburgh, his MBA at the International University of Monaco and his MSc in Financial Engineering degree at IUM. Since 2009 Markus is teaching the courses “Portfolio Theory & Alternative Assets” and “Investment Banking” at the International University of Monaco and established a 3-day workshop on “Third Generation Multi-Asset & Risk Management”, together with Deutsche Börse and Vienna Stock Exchange.

        Performanceergebnisse der Vergangenheit lassen keine Rückschlüsse auf die zukünftige Entwicklung eines Investmentfonds oder Wertpapiers zu. Wert und Rendite einer Anlage in Fonds oder Wertpapieren können steigen oder fallen. Anleger können gegebenenfalls nur weniger als das investierte Kapital ausgezahlt bekommen. Auch Währungsschwankungen können das Investment beeinflussen. Beachten Sie die Vorschriften für Werbung und Angebot von Anteilen im InvFG 2011 §128 ff. Die Informationen auf www.e-fundresearch.com repräsentieren keine Empfehlungen für den Kauf, Verkauf oder das Halten von Wertpapieren, Fonds oder sonstigen Vermögensgegenständen. Die Informationen des Internetauftritts der e-fundresearch.com AG wurden sorgfältig erstellt. Dennoch kann es zu unbeabsichtigt fehlerhaften Darstellungen kommen. Eine Haftung oder Garantie für die Aktualität, Richtigkeit und Vollständigkeit der zur Verfügung gestellten Informationen kann daher nicht übernommen werden. Gleiches gilt auch für alle anderen Websites, auf die mittels Hyperlink verwiesen wird. Die e-fundresearch.com AG lehnt jegliche Haftung für unmittelbare, konkrete oder sonstige Schäden ab, die im Zusammenhang mit den angebotenen oder sonstigen verfügbaren Informationen entstehen.

        Melden Sie sich für den kostenlosen Newsletter an

        Regelmäßige Updates über die wichtigsten Markt- und Branchenentwicklungen mit starkem Fokus auf die Fondsbranche der DACH-Region.

        Der Newsletter ist selbstverständlich kostenlos und kann jederzeit abbestellt werden.

        Für diesen Suchebgriff konnten wir leider keine Ergebnisse finden!
        Fonds auf e-fundresearch.com

        Weitere Informationen zu diesem Fonds Kennzahlen per 31.08.2021 / © Morningstar Direct
        Bereiche auf e-fundresearch.com
        NewsCenter auf e-fundresearch.com
        Kontakte auf e-fundresearch.com

        {{ contact.email }}

        {{ contact.phonenumber }}

        {{ contact.secondary_phonenumber }}

        {{ contact.address }}

        Weitere Informationen im {{ contact.newscenter.title }} Newscenter
        Artikel auf e-fundresearch.com