Can AI solve for bond market illiquidity?
Historically a fractured market for data dissemination, OTC bond market participants have been yearning for a consolidation, similar to that of the public equities markets. With the emergence of machine-learning technology, the hopes of a fully transparent market are now on the horizon. Overbond can solve this problem for clients through its unique data aggregation methodology, automated AI-modelled bond pricing workflow and best executable issuer curve visualization.
Source: Overbond
Since the financial crisis in 2008, the bond market has gone through significant changes. Liquidity problems have remained since, with many analysts from top asset management firms voicing their concerns, such as BlackRock Investment Institute in “The Liquidity Challenge, Exploring and Exploiting (Il)Liquidity published”, and more recently AllianceBernstein in “Fixed Income Trading Liquidity Update”. It has been over a decade but why has the secondary market liquidity not improved? One of the reasons for sustained bond market illiquidity is difficulty to assemble pricing data from incomplete, non-standardized, and various fragmented parts of the market that are traded on electronic venues and parts that are traded OTC. Consolidating quoting systems to aggregate pricing data across multiple sources is greatly needed. Coupled with complexity of bond securities reference data, it necessitates the application of AI historical benchmarking and curve building approach to optimise prices across multiple sources and bonds of different types and tenors.
These market conditions and the lack of state-of-the-art AI bond pricing solutions led to sustained inability to price illiquid securities with precision, in addition to the inability to compare similar bonds and build pricing curves per issuer efficiently. Resulting in limited price discovery for bonds without strong liquidity.
Overbond’s Corporate and Government Bond Intelligence (COBI)-Pricing AI can solve this problem for clients through automated bond pricing workflow with AI modelled bond price and best executable issuer curve visualization. Overbond provides bond pricing automation and modelling capabilities that aggregate transactions data with fundamentals, sentiment, and settlement layer data.
What is Overbond?
Overbond is a fixed income fintech platform for AI predictive analytics and visualizations. COBI-Pricing is a comprehensive suite of Overbond algorithms and analytics tools that systematically price bonds and identify trade ideas across global fixed income markets.
Overbond’s COBI-Pricing AI systematically prices end-of-day or intra-day live best-executable individual bond price or spread, and constructs issuer curves in spread or yield, for all global investment grade fixed income securities.
Overbond COBI-Pricing powers users’ fully automated bond trading workflow by providing precise executable prices in up to 30% more situations when there is no directly observable trading price in the market. Bond trading execution cost can be greatly reduced, or desk revenue can be grown significantly through access to this insight.
Overbond COBI Pricing
Overbond COBI- Pricing AI models aggregate historical data from multiple sources and optimize pricing for bonds with varying liquidity profiles. Overbond COBI Pricing can enhance users’ bond trading workflow by providing precise executable prices in situations when there is no directly observable trading price in the market or bonds rapidly change their liquidity profile. Bond trading execution desk revenue can be grown significantly through their access to this insight.
COBI-Pricing enables fully automated bond trading workflow with various curve visualizations and front-end trade analytics tools.
Sell-side credit and rates traders can grow their RFQ response significantly with precision and confidence, growing accordingly desk P&L.
Buy-side trade execution and portfolio management groups can achieve best-execution on fixed income trades.
Issuers can better monitor debt capital markets, benchmark against their peers and identify pricing tension and liquidity changes in their borrowing program.
Connectivity
Overbond pre-integrates and sources data from major data vendor aggregators, electronic exchanges and credit rating agencies. Overbond also pre-integrates and maps additional data from corporate fundamentals data providers, investor sentiment and settlement data on OTC fixed income trades to provide deep and all-comprehensive data access to AI models.
The successful data pre-processing is the key stage and pre-requisite for the Overbond COBI-Pricing algorithm operation. Overbond pre-integrates and pre-processed input data from several providers below and can also work with any client preferred vendor or trading venue feed
- Refinitiv
- S&P Global
- ICE
- Exchange Data International
- Six Group
- Euroclear
Overbond Key Capabilities
- Data aggregation capability across multiple input data sources (vendor, venue or settlement layer data sources)
- Liquidity score and pricing confidence scores for every bond
- Finds similar issuers and bonds per various criteria (credit rating, quality, fundamentals, industry etc.)
- Curve builder approach on per issuer basis
- Live or intra-day pricing output for MTM, IPV or Best-Ex use case
- Historical time series tracking and visualization of all modeled data
- Clustering of similar issuers and similar bonds
- Distance to cover (Margin Optimization) model add-on
- Probability of Buy/Sell Indicators per ISIN model add-on
Read our recent case study with Hydro One: https://overbond-static.s3.amazonaws.com/public_downloads/Overbond+-+Hydro+One+Case+Study+-+Final.pdf
Read our COBI-Pricing White Paper: https://s3.amazonaws.com/overbond-static/public_downloads/Overbond-COBI-Pricing-White-Paper.pdf
Contact:
Vuk Magdelinic | CEO
+1 (416) 559-7101
Justin Hui | Sales Manager
+1 (289) 544-7975
Sources:
- https://www.blackrock.com/corporate/literature/whitepaper/bii-the-liquidity-challenge-us-version.pdf
- https://www.alliancebernstein.com/funds/abii/documents/FI-Market-Liquidity-Update/FI-Liquidity-Market-Update_051920.pdf
- https://www.newyorkfed.org/medialibrary/media/research/staff_reports/sr796.pdf
- https://www.bruegel.org/2015/08/the-decline-in-market-liquidity/
- https://s3.amazonaws.com/overbond-static/public_downloads/Overbond-COBI-Pricing-White-Paper.pdf
- https://overbond-static.s3.amazonaws.com/public_downloads/Overbond+-+Hydro+One+Case+Study+-+Final.pdf
- https://www.youtube.com/watch?v=dZQbnO16SNc&app=desktop
- Sommer, P., and S. Pasquali (2016): “Liquidity–How to Capture a Multidimensional Beast,” The Journal of Trading, 11(2), 21–39.
- Trebbi, F., and K. Xiao (2015): “Regulation and Market Liquidity,” NBER Working Paper Series, 21739.
Video Analytics | CCTV Analytics | Cognitive Media Analytics | Security and Surveillance | AI
4 年Insightful and an excellent read. Thanks, Vuk Magdelinic
CFA | FRM | CQF | Investment Risk & Analytics
4 年Currently the problem is magnified due to lack of reliable trading infrastructure and price discovery for end users. The job is done by multiple intermediaries (broker/dealers) introducing their own information asymmetry and costs.
Product @ Priceline | E-Commerce | Digital Marketplace | Schulich MBA
4 年Vuk Magdelinic Thanks for sharing the article. Overbond adds a lot of value to both buy-side and sell-side given that the platform provides flexibility to choose from multiple financial market data feeds and optimize bond pricing using Artificial Intelligence.