Portfolio risk analysis and performance Tender in USA - 21835993

Procurement Summary

Country: USA

Summary: Portfolio risk analysis and performance attribution system product for the united nations joint ...

Deadline: 02 Apr 2018

Posting Date: 26 Mar 2018

Other Information

Notice Type: Tender

TOT Ref.No.: 21835993

Document Ref. No.: RFINM3125

Competition: ICB

Financier: United Nations Secretariat

Purchaser Ownership: -

Tender Value: Refer Document

CPV Classification

79410000 - Business and management consultancy services

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Tender Details

PORTFOLIO RISK ANALYSIS AND PERFORMANCE ATTRIBUTION SYSTEM PRODUCT FOR THE UNITED NATIONS JOINT ...
Deadline: 02-Apr-2018 00:00
Time zone: 0.00
Description:

Overview of the Fund 1. The United Nations Joint Staff Pension Fund (“UNJSPF” or “the Fund”) was established by the General Assembly of the United Nations ("UN") to provide retirement, death, disability and related benefits for the staff of the UN and other international intergovernmental organizations admitted to membership in the Fund. 2. The UNJSPF is an internally managed fund, with over US $65 billion under management as of 1 March 2018. At the same date, the Fund’s assets were invested in 25 currencies and in 34 countries (including emerging markets), in regional institutions and international institutions. Please consult the Fund’s website at http://imd.unjspf.org/ for a breakdown of the Fund’s assets per type of investment. Purpose of this Request 3. IMD is requesting proposals for a Portfolio Risk Analysis and Performance Attribution System (the “PRA System”), which will effectively support IMD monitor, assess and evaluate the risk and performance of the Fund’s global portfolio(s) and assist with the reporting of such information. The system should be able to dynamically adjust and update reports, allocation limits, stress testing, sensitivity analyses, factor analyses, tracking risk limits, and risk budget so they are in line with overall fund’s risk tolerance and target return. The analytics, research, data feeds and integrity, onsite service and educational spillover, training, technical and nontechnical support will help IMD’s Risk Team to efficiently translate IMD’s risk management practices into portfolio management implications. The PRA system could be accessed online. Moreover, IMD’s independent global custodian bank will provide the data feed and indices. The Portfolio Risk Analysis and Performance System will be used to dynamically and should update allocation limits, stress testing, sensitivity analyses, factor analyses, tracking risk limits, and risk budget so they are in line with overall fund’s risk tolerance and target return. Functionalities that should be provided by the system: (i) Return Assessment: Comprehensive analysis at total portfolio, sub-portfolio, industry, sector, position levels, including: Asset class exposure; geographic region exposure; currency exposure; market capitalization exposure; economic revenue exposure; risk/return profile calculation; and provision of covariance analysis. ? Performance Attribution: Analyze active investment decisions, assess the skill of managers and determine how excess returns were generated using appropriate performance modules for respective asset classes i.e.: equity decomposition by GICS sector, and fixed income decomposition by term-structure (duration), rate spreads, etc. based on appropriate fixed income models. Ability to have performance models for real assets and alternatives asset classes like real estate and private equity. In addition, Factor Performance Attribution is required (ii) Risk Assessment: Analyze the amount of risk contributed by each investment decision and quantify various risks driving the excess returns. Statistical distributions used for risk measurement are computed from asset classes’ “pricing functions” (equity, fixed income, options, FX, Mortgages, etc.) based on risk factors such as market data: equity prices, foreign exchange rates, commodity prices, interest rates (marked-to-market). In addition to risk measurement based on economic/fundamental risk factors such as Country, Industry, Style, Size; ideally same risk factors used for factor performance attribution: ? Relative Risk Decomposition: Parametric, and non-parametric approaches for Tracking Error, Value-at-Risk (VaR), Expected Shortfall computations on an ex-ante basis using Monte Carlo techniques, in addition to historical risk analysis. Risk Decomposition should be based on pricing models underlying the statistical distributions used to compute the risk measurements. Factor Risk Decomposition is also required. ? Absolute Risk Assessment: Parametric, and non-parametric approaches for standard deviations, Value-at-Risk (VaR), Expected Shortfall computations on an ex-ante basis using Monte Carlo techniques, in addition to historical. Stress testing designed to capture historical events, by risk factors (stressing stock prices, rates, currency etc.) or risk type (equities, bonds, VIX etc.) allowing users to design own stress tests, and theme stress test designed by vendor’s applied research and emerging from contemporaneous events. (iii) Coverage of Specific and General Risk Factors: Specific risk factors for equity securities are log returns of stock prices, as for bonds, free and risky interest rates are typically used as risk factors in the Net Present Value pricing function of generic debt securities. General risk factors, such as style, size, dividend yields, momentum, volatility, P/E ratio etc. are also used to derive similar risk measurements. Access to market data indices such as official benchmarks, which can be downloaded onto other applications for comparative analyses. (iv) Risk Budget Calculation and Investment Implications: Setting up risk budgets for SAA allocation limits is compliant with tracking error thresholds or risk budgeting defined under large changes in allocation. Monitor risk budgets on a regular basis and perform root cause analyses if risk budgets have crossed there limits, is consistent with tracking error sensitivities or risk budgeting for allocation decision with risk considerations i.e.: risk budgeting in dynamic sense designed for recent market uncertainties and co-movements of securities/assets, leading to the following requirements: ? Covariance (Sensitivity) Analyses: able to generate correlation, covariance, marginal/incremental risks, and beta reports that can be defined as per user specifications, with both short and long-term estimation horizons; capable of handling systematic, automated process. ? Simulated Returns, Optimization, and Pricing Models: able to provide results of MC simulation derived from statistical distributions used to compute risk statistics; Optimization module for portfolio construction, with constraints capable of handling restricted securities as defined by IMD; Transparency, and fully documented pricing models that are supported with research and academic literature The system should be able to calculate risk budget for the asset classes, sectors, regions and countries. (v) Framework and Specifications. Portfolio construction, and portfolio aggregation will have greater impact on returns (relative, and especially absolute) as the fund’s size grows in market value, due to market concentration, suitable investment universe, restricted securities, mid-caps exposure, small caps, ESG, real assets, alternative investments, all presenting ongoing challenges to portfolio diversification, risk, and performance measurements. Thus, the following considerations apply: ? Service provider ? Reporting: Capable of generating fully automated reports provided and accessible through managed services process, password-protected internet website in addition to on-site application systems ? Analytics: Robust analytics based on asset classes pricing models, as well as factor based, and Monte Carlo Simulation module. In addition, analytics specific to sustainable, green equity investments. Capable of handling large data feed offerings, covering most of the fund’s assets as measured by market value and part of SAA policy statement. Examples of such assets are real estate, private equity, and commodities. ? Technical Aspect: All UN portfolios, benchmarks should be modeled at the individual security level (users can drill down from the total fund, portfolio levels to the individual security level). Tools should have ability to aggregate security’s specific risks, and return drivers into portfolio risk & return profiles, summing up to the total fund level. Services include technology, analytics required to measure risk and performance statistics, produce reports, and deliver the risk and performance reports. Systems training. ? Operational Aspect: Vendor should provide constant monitoring, data quality control, and administration, with operations team that monitors all client environments. IMD’s independent master record keeper and “Global Custodian” will send holding information to the service provider on a daily basis or depending reporting needs. The service provider will maintain a historical data set of the Fund’s holdings and returns. Capabilities to provide raw reports analytics, data aggregation & processing through automated XML interface, txt, excel documents for use by IMD’ internal systems. The service provider should be able to receive security, market, and index data from Global Custodian.
UNSPSC:

G - Business, Communication & Technology Equipment & Supplies

43000000 - Information Technology Broadcasting and Telecommunications

43230000 - Software

43232600 - Industry specific software
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NOTE: Multiple Countries (Total: 45)
Type of notice :Request for information
More Details :G - Business, Communication & Technology Equipment & Supplies
43000000 - Information Technology Broadcasting and Telecommunications
43230000 - Software
43232600 - Industry specific software

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