Alternative Investment Management Software

Risk Shell

Institutional portfolio management, risk analytics and portfolio construction for alternative and multi-asset portfolios.

Integrated investment data, stress testing, portfolio optimization, alternative investment analytics and shadow accounting within one platform.

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FoF Manager

Shadow Accounting for Alternative Portfolios

Manage hedge funds, private equity and multi-asset portfolios with liquidity controls, custom classifications and flexible historical accounting.

35+ hedge fund liquidity settings
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Portfolio Optimization

Nonlinear Portfolio Optimization

Construct hedge fund-of-funds and multi-asset portfolios with stress-test, factor-exposure, liquidity and other user-defined constraints.

Custom Constraints for market-neutral and risk-controlled portfolio construction
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Risk Shell AI

Natural-Language Access to Risk Shell

Use natural language to access investment research, risk analytics and portfolio workflows.

2.3B tokens in our in-house financial LLM
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Macroeconomic Scenario Screening

Select Assets for the Scenario You Define

Screen managers by risk and return targets under user-defined macroeconomic scenarios.

Trend Segmentation™ proprietary regime-analysis engine
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Peer-relative Stress Testing
Portfolio Stress Testing

Peer-Relative Stress Testing

Compare extreme-event outcomes with a relevant peer group.

500K+ live stress-tested instruments
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Although institutions have been conducting due diligence on investment managers for years, their routine protocols mainly focus on the qualitative side. Thus, the main drawback of commonly used due diligence frameworks is a lack of the quantitative component, arguably most important.

Conducted blindly and relied on filling formal questionnaires, such procedures are largely worthless, because cannot provide a deep analysis of managers' trading strategies and employed risk management techniques. This hurdle is not new - even the Federal Reserve Board stated in 1999:

The due diligence and ongoing risk assessments of hedge funds were largely qualitative and lacked quantitative rigor.

On the other hand, relying primarily on a quantitative assessment methodology presents another extreme bias - also leading to likely misleading and questionable results. The quantitative evaluation of hedge funds involves a number of serious issues that need to be addressed properly:

  • low consistency of data leads to questionable results of any calculations whatever models are used;
  • non-transparency of hedge funds implies difficulties of measuring risks since the underlying assets are not disclosed;
  • short data series cannot provide statistical significance of calculations, thus making statistical analysis problematic;
  • past performance is a weak indicator of future returns;
  • non-normality of hedge fund distributions of returns makes the commonly used mean-variance theory inapplicable.

We have been witnessing endless arguments and discussions of a right balance between quantitative and qualitative due diligence approaches for years. Our standpoint on that matter could be summarized as follows:

  • there is no point to discuss a balance between these two due diligence parts. Due diligence on hedge funds should access all applicable risks, while risks could be evaluated either quantitatively or qualitatively;
  • the accessed risks should include, at least: market, credit, event, liquidity, volatility, operational, currency, legal, fraud, concentration and strategy risks;
  • the traditional Markowitz's mean-variance methodology is hardly applicable to hedge fund evaluation and, as such, should not be used. The employed frameworks should address numerous peculiarities of hedge funds: non-normal distributions of returns, index biases, low correlation with their indices, and limited return series.

ABC Quant Due Diligence Workflow

ABC Quant Due Diligence Workflow
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