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Portfolio Risk Analytics

Portfolio and Security Analytics for Multi-Asset Portfolios

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Real-time Analysis of Multi-Asset Portfolios using Holdings, Returns and Risk Data


Analyzing multi-asset portfolios that contain complex instruments requires not just basic exposure and ex-post analysis but also deep-dive details into forward-looking risk, scenario and attribution analysis.

Use of legacy systems for managing holdings, performance, and risk makes the integration a challenge to such analysis in real-time.

There is, therefore, a need to bring these systems together using modern (‘cloud’) technology to enable real-time portfolio analysis for users. This in parallel to technology teams working on plans to upgrade/rebuild legacy systems.


A minimalist approach to a solution to the above is to look at it from both the user’s perspective (the what?) and also from a systems perspective (how to?)

Users Perspective – (the what?):


1. Market Value/Exposure (Gross/Net, Long/Short, Groupings by Currency, Asset category(ies), Industry, Region, ESG categories, etc) 
2. Look through analysis
3. Liquidity Analysis
4. Portfolio/Security Analytics – DV01, CS01, Duration, Greeks, Yield, KRD, …


1. Holding Period Returns – Times series, breakdown by currency, industry, ..
2. Other Returns – IRR, Annualized Returns, ..
3. Return Attribution – Bottom up/Top-down
4. Risk vs Return Analysis


– Risk Ratios – Standard Deviation, Sharpe Ratio,…
– Regression Analysis – Covariance, Correlation, Treynor, R2, …
– Benchmark Stats – Up/Down Capture, Active Share
– Relative Risk – Tracking Error, Information ratio
– Other – Kurtosis, Skewness, Drawdown, Sortino Ratio, …

– Historic Simulation/Parametric VaR and Conditional VaR
– Component/Marginal VaR
– Absolute vs Relative VaR
– VaR Limit Analysis
– Backtesting VaR
– EaR/EvE
– Historical Stress Scenario Analysis
– Stress Testing
– What-If Analysis

Other features such as use of ESG attributes(provided we have the right data), Peer Group Analysis and support for new asset classes (such as Crypto) will be a must have soon.

Systems Perspective (How to?):

– Integrate with legacy systems using APIs to leverage new technology for real-time analysis

  – This API layer is critical and needs to be built at ‘Domain’ level and not just access to every existing legacy system. Teams with good domain experience and new technology knowledge will be necessary for success of this critical effort.

– Use cloud databases such as Snowflake/Redshift for real-time BI and reporting

– Plan to upgrade and/or build using ‘cloud’ technology (microservices) architecture

We will deep dive into each of the above user needs in the next article…



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