Quantitative Portfolio Management Dynamic asset allocation

Transcription

1 P R O D U C T S Quantitative Portfolio Management Dynamic asset allocation Member of the Swiss Bankers Association

2 The present global economic environment and the correlative structural changes make it difficult to predict returns on asset classes over the medium- and long-term. This situation affects the risk profiles of asset classes which, for several years, have shown a lack of stationarity. Academic studies have shown that about 90% of portfolio risk measured by its variance and on average 100% of its performance are explained by the asset allocation (1). These findings call into question the relevance of static asset allocation approaches and have led Dynagest to develop a dynamic approach to asset allocation which offers better control of overall portfolio risk. This approach meets the client s need for a dynamic and flexible process that is more closely attuned to the client s objectives. Dynagest s strengths independent portfolio management quality macroeconomic research mastery of modern risk management techniques ability to form synergetic partnerships. Fees Annual advisory/management fees vary between 0.20% and 1.00% depending on management constraints, range of services and the amount under advisory or discretionary management. Medium- and long-term objectives To provide its clients with innovative solutions, Dynagest continues to invest in research and development in the following areas: modern risk management techniques integration of the different quantitative management techniques with Dynagest s macroeconomic research.* *See brochure "Quantitative Portfolio Management. Ratchet Management and Portfolio Insurance".

3 Customised implementation determination of strategic allocation choice of risk limits (boundaries for each asset class, risk aversion coefficient, maximum volatility) definition of the asset class universe selection of investment vehicles: external or in-house management mandates* investment funds index linked products (ETFs, index derivatives).* *See brochure Quantitative Portfolio Management. Index Tracking and Enhanced Indexing. Strengths of Dynagest s allocation model customised allocation to meet clients specific needs dynamic risk modelling flexibility: the model can be entirely systematic, can integrate clients expectations or Dynagest s macroeconomic research strategy implementation can be adapted to all types of investment vehicle a more stable risk profile in order to improve asset liability management rigorous control of predefined risk budget framework. Investment mandates Dynagest successfully applies dynamic asset allocation for several Swiss pension fund providers. Insight articles authored by Dynagest* Gestion des actifs: les atouts de la co-intégration La dynamique interne de la gestion indicielle Les Key Rate Durations surpassent la duration modifiée La gestion à cliquets appliquée au secteur des obligations/dynamic Ratchet: Anwendung in der Anleihenverwaltung From pure protection to real asymmetric profiles Les modèles GARCH pour gérer la volatilité L'art d'anticiper les anticipations. *Available from Dynagest SA or on the website at

4 Example: specific asset classes limits for a LPP 25 profil Money Market Bonds Equities Real Estate Private Equity Hedge Funds CHF CHF EUR Swiss Europe Emerging Swiss CHF Indice Benchmark Pictet (2005) LPP LPP 25 plus 25 Bandwidth Min Max CHF Libor 1 Month SBI Swiss Bond Index Barclays Euro Aggregate Barclays Aggregate Swiss Performance Index MSCI AC World Free MSCI Europe MSCI EM SWX Immofonds DJ Willshire Real Estate LPX 50 (Private Equity) HFRX Hedge Funds % % % Source: Dynagest SA, Geneva Investment process The process is based on recent theoretical work which enables dynamic modelling of volatility and correlation risk in different asset classes. GARCH models (2) are used to model conditional volatility in these classes, while correlations between the different asset classes are measured using a DCC model (3). The confluence of these techniques permits real-time monitoring of portfolio risk, thereby ensuring close alignment between the risk profile of the allocation and the risk limits defined by the client. Dynagest s dynamic asset allocation can be used as a decision-making tool by the client s investment committee or integrated into Dynagest s balanced mandates. Outline of the investment process definition of the client's needs: overall risk limit, risk aversion, specific limits for each asset class, asset liability management determination of expected asset class returns, using fundamental techniques, with or without client input and/or a systematic quantitative approach application of risk modelling techniques to the client s portfolio, using a dynamic approach (GARCH and DCC) dynamic optimisation of asset allocation, in line with expectations and the different risk constraints adjustment of allocation to changes in market conditions.

5 35% 30% Conditional volatility evolution: a better control of the risque profil Dynagest TAA Model LPP 25 (risk aversion of 20) Pictet (2005) LPP 25 Source: Dynagest SA, Geneva 25% 20% 15% 10% Conditional Volatility 5% 0% 31/12/ Performance evolution of the Pictet (2005) LPP 25 Index and Dynagest's dynamic asset allocation model * Source: Dynagest SA, Geneva 200 Dynagest TAA Model LPP 25 (risk aversion of 20) Pictet (2005) LPP Performance indexes /12/99 31/12/00 31/12/01 31/12/02 31/12/03 31/12/04 31/12/05 31/12/06 31/12/07 31/12/08 31/12/09 31/12/10 31/12/11 31/12/12 31/12/13 31/12/00 31/12/01 31/12/02 31/12/03 31/12/04 31/12/05 31/12/06 31/12/07 31/12/08 31/12/09 31/12/10 31/12/11 31/12/12 31/12/13 *Pro forma figures generated by Dynagest's proprietary dynamic asset allocation model.

6 The information provided in this brochure is valid as of 31 May ) Ibbotson Roger G. and Kaplan Paul D., Does Asset Allocation Policy Explain 40, 90, 100 Percent of Performance?, Financial Analysts Journal, Jan/Feb 2000, Vol. 56, No 1. 2) Bollerslev Tim, Generalized Autoregressive Conditional Heteroskedasticity. Journal of Econometrics, 1986, Vol. 31, issue 3, pp ) Engle, Robert F., Dynamic Conditional Correlation: A Simple Class of Multivariate GARCH Models, Journal of Business and Economic Statistics, July 1, 2002, 20(3): Dynagest sa Quai de la poste 12 CP 1211 Geneva 11 Phone Fax MAIL@dynagest.ch