{"id":8020,"date":"2019-12-06T09:34:47","date_gmt":"2019-12-06T14:34:47","guid":{"rendered":"https:\/\/www.bloomberg.com\/company\/press\/bloomberg-receives-three-risk-markets-technology-awards\/"},"modified":"2019-12-09T11:43:18","modified_gmt":"2019-12-09T16:43:18","slug":"bloomberg-receives-three-risk-markets-technology-awards","status":"publish","type":"press","link":"https:\/\/www.bloomberg.com\/company\/press\/bloomberg-receives-three-risk-markets-technology-awards\/","title":{"rendered":"Bloomberg receives three Risk Markets Technology Awards"},"content":{"rendered":"
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This article first appeared on Risk.net<\/em><\/p>\n

Risk Markets Technology Awards 2020<\/em>
\nMarket liquidity risk product of the\u00a0year
\nPricing and analytics, structured products and cross-asset
\nCollateral management and optimisation product of the year<\/p>\n

Global regulators have increased their focus on market liquidity and now require firms to generate accurate, defendable metrics. Although initially a compliance issue, the monitoring and management of market liquidity is becoming an intrinsic part of firms\u2019 risk management frameworks.<\/p>\n

Bloomberg\u2019s Liquidity Assessment Tool (LQA) takes a data driven approach to estimating liquidity risk and combines prevailing market conditions to make this assessment. The company has access to significant volumes of relevant trade data from a range of sources, including exchanges, trade repositories and clearing houses, as well as bilaterally negotiated contribution agreements for more difficult to price securities. Where there is a lack of data for a given security, various algorithms\u00a0\u2013 including machine learning techniques\u00a0\u2013 fill the gaps to provide comprehensive coverage.<\/p>\n

LQA\u2019s models capture the unique behaviour of each asset class (from fixed income to listed derivatives), while providing consistent metrics, making it easy to aggregate results at the portfolio level or even across portfolios, and compare liquidity metrics across securities.<\/p>\n

Detailed out-of-sample backtesting ensures model performance is accurate and provides detailed feedback for further model development or tuning where required.<\/p>\n

Clients can also customise the model inputs where their specific view does not align to LQA\u2019s default market parameters. Stress- and scenario-testing are supported at the security level. Clients are also able to request transaction-level output metrics based on different centiles of liquidation cost and horizon distributions.<\/p>\n

Workflow and the integration of liquidity measures into firms\u2019 ecosystems are flexible. Multiple channels for consuming the liquidity analysis are available, ranging from the Bloomberg Terminal to a programmatic application programming interface\u00a0(API) and Excel add-in. To help streamline model validation exercises, the company has produced a single comprehensive set of standard documentation.<\/p>\n

Pricing and analytics, structured products and cross-asset <\/strong><\/p>\n

The value and opportunity presented by the structured product markets is something an increasing number of firms understand. Bloomberg\u2019s integrated solution for structured products covers the whole value chain, from underlying data to pricing, risk and reporting.<\/p>\n

Derivatives Library (DLIB) is a cross-asset pricing and risk system that enables firms to create any type of structured product quickly and easily using packaged or custom templates. The solution facilitates the workflow between sell-side firms and their clients, allowing them to structure deals, price them individually and on a portfolio basis, and analyse them for risk, credit, funding and pre- and post-trade margin requirements.<\/p>\n

Covering equity, fixed income, repo, rates, inflation, credit commodities, foreign exchange and mortgages, Bloomberg\u2019s solutions enable manufacturers, distributors and buyers of structured products to save and share ideas, deals and portfolios on the Bloomberg terminal. On DLIB, all sides view the same deal and have the same understanding of its terms, such as inputs, lifecycle events and cashflows, negotiation and agreement is faster and more efficient, and the potential for misunderstanding is minimised.<\/p>\n

Customised exotic products can be added in minutes using the company\u2019s scripting language and parametrised user interface templates. Once a product is created, all Bloomberg\u2019s front-to-back solutions \u2013 such as lifecycle management, intraday and end-of-day mark-to-market, scenario analysis and stress-testing \u2013 can be applied without additional effort. Bloomberg\u2019s Multi-Asset Risk System (MARS) can be used in conjunction with DLIB to provide comprehensive risk analysis for portfolios containing structured products.<\/p>\n

Collateral management and optimisation product\u00a0 <\/strong><\/p>\n

MARS Collateral is Bloomberg\u2019s solution for complying with evolving collateral regulations and meeting the challenges of valuations, margin call management, dispute resolution and reconciliations. It provides automated, straight-through, end-to-end workflow for managing, processing and monitoring collateral for multiple asset classes. Users can view all margin calculations, legal entity and agreement data, inventory, reconciliations, risk analytics and other relevant information. The functionality and data integration capabilities maximise workflow efficiency and reduce operational and credit risk.<\/p>\n

MARS Collateral is built within Bloomberg\u2019s Mars risk management framework and can be installed standalone or with the rest of the MARS suite, as well as integrated with Bloomberg\u2019s order management systems \u2013 Asset and Investment Manager for the buy side and Trade Order Management Solutions for the sell side. MARS provides consistency and consolidated valuation across product lifecycle analysis, market risk, counterparty risk and collateral management. It receives deal and valuation information from Bloomberg\u2019s single security pricers in real time, covering rates, equity, forex, commodities and credit, as well as complex exotics from DLIB. Deals are consolidated into Mars portfolios and linked to collateral agreements in MARS Collateral. Users have a holistic view of exposures and collateral inventory, with posted collateral across all agreements displayed, as well as collateral available to post.<\/p>\n

Legal agreement terms are captured on Bloomberg\u2019s Legal Entity and Documentation Manager tool\u00a0\u2013 a central legal document repository that also serves to provide the terms for margin processing. Bulk import and export tools are available via XML for simple document\u00a0management.<\/p>\n

Bloomberg has licensed the International Swaps and Derivatives Association\u2019s standard initial margin model\u00a0(Simm), enabling it to calculate the initial margin on non-centrally cleared derivatives using the Simm method and the underlying sensitivities using Mars. The solution is linked to several central counterparties to calculate initial margin on cleared swaps and futures.<\/p>\n

Judges said:<\/p>\n

\u201cBloomberg provides a good, innovative market liquidity risk service that is energetically being enhanced.\u201d<\/p>\n

\u201cThe extensive integrated end-to-end framework for structured product and cross-asset pricing, with a choice of proprietary Bloomberg applications or in-house add-ons, make this a powerful tool.\u201d<\/p>\n

\u201cBloomberg has created a well-designed collateral management system and service. The administration, workflow, data, pricing, analytics, regulatory compliance and integration are high-quality and comprehensive. The company has released the product in a progressive, disciplined manner, starting with small departments and moving towards larger organisations.\u201d<\/p>\n

Brad Foster, global head of enterprise content at Bloomberg, says: \u201cLQA stands apart by using a robust dataset with a machine learning framework that ensures all the relevant factors influencing liquidity are considered, resulting in a data-driven solution for risk assessment and stress-testing. LQA is now also available through an interactive API, allowing clients to interact with the models in real-time, with low latency, making this an ideal solution for front-office users doing pre- and post-trade analysis.\u201d<\/p>\n

Jose Ribas, global head of risk and pricing solutions at Bloomberg, says: \u201cRisk management is a key priority at Bloomberg and we are particularly pleased that our modular, on-screen and programmatic API-based approach is recognised with these awards. We see growing demand for more sophisticated risk solutions that streamline workflows front-to-back, and our collateral management and pricing and analytics tools are part of a wider offering that addresses these needs in a consistent way. Helping investors create, trade, price and risk manage vanilla to complex derivatives is one of our key strengths.\u201d<\/p>\n\n<\/div>\n\n\n<\/div>\n\n\n\t\t\n\t<\/div>\n<\/div>\n\n","protected":false},"excerpt":{"rendered":"This article first appeared on Risk.net Risk Markets Technology Awards 2020 Market liquidity risk product of the\u00a0year Pricing and analytics, structured products and cross-asset Collateral management and optimisation product of the year Global regulators have increased their focus on market liquidity and now require firms to generate accurate, defendable metrics. Although initially a compliance issue, [...]","protected":false},"featured_media":0,"template":"","format":"standard","categories":[1337],"press_tag":[1331],"class_list":["post-8020","press","type-press","status-publish","format-standard","hentry","category-award","press_tag-media-mentions"],"yoast_head":"\nBloomberg receives three Risk Markets Technology Awards | Press | Bloomberg LP<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/www.bloomberg.com\/company\/press\/bloomberg-receives-three-risk-markets-technology-awards\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Bloomberg receives three Risk Markets Technology Awards | Press | Bloomberg LP\" \/>\n<meta property=\"og:url\" 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