Investment Management

Solving challenges for financial industry professionals


The strategic asset allocation process is a core element for institutional investors, pension funds and family offices. It basically represents the matching process between investment objectives (e.g. liabilities, return/risk targets) and the available investment/asset universe.

The strategic process is less frequent than the tactical process (typically on an annual basis) but nevertheless the most relevant for defining the available degrees of freedom during the investment process.

Typically, many investors include external return/risk estimates from renowned providers into their process. The OpenMetrics® portfolio modeling framework allows to incorporate external estimates as well as data driven estimates or Black-Litterman blends.

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Tactical asset allocation, in contrast to strategic asset allocation is the "daily driver" for most investment managers in order to steer the portfolio(s) trough changing market dynamics.

Most tactical asset allocation processes rely on various risk measures or signals from active allocation models. OpenMetrics can support investment managers with a proper calibration of risk measures and models as well a delivering the ready-to-use exposure management via SaaS.

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Risk management is the core component of the investment management process. Therefore, the main element of proper risk management is to use the correct mathematical models, which provide fast and accurate risk signals. OpenMetrics Solutions has published many papers in this regard (e.g. Stable Portfolio Design using Bayesian Change Point Models and Geometric Shape Factors and many others)

Besides correct mathematical models, the ease of use and the straightforward interpretation of risk signals are key for practical use.

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Dynamic hedging is the appropriate approach for managing investment risks when the underlying portfolio cannot be changed frequently due to involved rebalancing costs (e.g. large pension fund portfolios) or when the portfolio strategy requires specific exposure (e.g. factor models).

In these cases, we propose to hedge on a proxy level. Either on benchmark index level, on sector/regional level or on a synthetic benchmark level (e.g. index blend).


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