In March 2020, several of the largest banks famously shut down their auto-quoters as the pricing algorithms couldn't keep up with the unprecedented volatility. This withdrawal of liquidity provision, presented a learning opportunity for the algos and the humans at the wheel, and ensured those same auto-quoters to handle more recent volatility (e.g., the regional bank crisis) without a hitch." This indicates a need for analytic features that can adapt to and handle extreme market conditions.

Bond traders face a set of challenges not seen in most other markets for tradeable securities. There's no comprehensive centralized record of fixed income trade price or size data because most bonds are traded over-the-counter. Additionally, many bond issues are small and trade infrequently or not at all. As a result, it's often difficult for bond traders to assess the liquidity and volatility of the issues they're trading.

A buy-side perspective on electronification and automation of corporate bond trading. A group of leaders from the trading desks of Europe’s largest asset managers and pension funds joined representatives from the vendor community at the exclusive Institutional Investor European Fixed Income Trading Summit, from March 2nd to March 3rd, 2023. Before the session, representatives from Institutional Investor and buy side participants aligned on a set of questions designed to gauge the practices of the buy side in terms of execution, electronic trading and automation. The answers were tabulated and are presented in this exclusive report.

With a multi-year decline in dealer inventories and higher capital requirements, sharp increase in aggregate outstanding debt instruments, and proliferation of riskier instruments like leveraged loans, the subject of bond market liquidity risk has been attracting attention throughout financial institutions, regulators, and policy makers. Although liquidity risk affects most, if not all, bond market participants, it has a tremendous impact on open-ended mutual funds and several similar product categories, which allow their shareholders to request redemptions at any time. Therefore, effective liquidity risk management is most critical during times of market distress.

With CAD$12.445 billion of outstanding bonds as of April 2020, Hydro One had several challenges when it came to monitoring its credit spreads and those of its peers in order to issue bonds in the most cost effective manner. By working with the Overbond Treasury Debt Capital Service and automating its data intake and analytics, Hydro One can now identify opportunities to reduce the cost of funding faster and more efficiently. In short, “price tension” in markets, benchmarks, historical data and investor sentiment can now be identified more quickly. Going forward, Hydro One will be looking to incorporate Overbond’s COBI Liquidity scoring feature to strengthen understanding of the liquidity of their own bonds as well as their peers’ bonds in the secondary market. The COBI Liquidity module utilizes metrics such as bid-ask spreads, trade count and volume, and intraday price volatility for the wide spectrum of bonds to derive a daily liquidity score for each bond.

Overbond’s primary fixed income prediction model for global issuance, COBI Bond Issuance International AI, combines the capabilities of COBI-Pricing, COBI-Issuance and COBI-Bond Buyer Matching and delivers on issuance discovery in all G-10 currencies with issuance opportunity monitoring and matching with institutional investment preferences. It is an advanced three phase AI algorithm engineered to measure best fit correlations with respect to company fundamental valuation and secondary market pricing for their bonds across sector peers and markets conditions at large and build relative value pricing curves in all G-10 currencies that issuer has bond denominated in (EUR, CAD, GPB, JPY, NOK, AUD, NZD, CHF, and SEK)

Overbond’s Bond Buyer Matching Algorithm, COBI-Matching, provides analytics platform for issuers, dealers and investors to discover traditional and non-traditional buyers for new bond issuances as well as profiling pricing tension in secondary market and risk appetite for target buyers, enabling systematic opportunity monitoring and market signal alerts.

Overbond’s Primary Fixed Income Pricing model, COBI-Pricing, delivers on Price Discovery with competitive indicative new issue pricing. Clients can arrive at accurate indicative new issue pricing levels for issuers with only a fraction of the time and manual work required. Through this, clients can mitigate risk, increase efficiency and generate portfolio alpha.

Overbond’s Primary Fixed Income Issuance Prediction model, COBI-Issuance, delivers on Issuance Discovery with issuance opportunity monitoring and matching signal alerts. Market counterparties can focus their pre-trade analytics on most likely new bond issuances with optimal pricing and supply-demand trend, resulting in increased efficiency and portfolio alpha.

On April 7th, 2017, treasurers from some of Canada’s largest corporate and financial debt issuers gathered at the CFA Society Toronto luncheon to provide insight and share their considerable experiences in accessing international markets to meet their debt funding requirements. Overbond team engaged with the industry professionals to discuss key trends and considerations in cross-border bond issuance.

On June 21st, 2017 AIMCo joined the list of pension funds issuing debt by launching its initial debt offering, a AAA rated C$400M 7-year note priced at 2.266%. This report analyzes the key trends and reasons for why large pension funds in Canada are starting to issue more and more debt.

Global M&A activity has been robust in recent years, fueling the growth of the acquisition finance market. Debt financing, in particular, has become increasingly common for M&A transactions, thanks to the record low interest rate environment. While bridge financing is often imperative for the success for an acquisition, acquirers are recommended to promptly contemplate long-term financing.

Overbond research team compared the cost of funding implications for an investment grade issuer using four different debt portfolio issuance strategies. The data utilized includes all U.S. treasury rates and generic “BBB” index spreads from 2002 to 2016. In aggregate, there are over 7,000 unique data points. The analysis concludes that issuing debt on a more frequent basis and in smaller issuance sizes has been shown to lower the average cost of borrowing and better diversify investor base.

Overbond team performed a bond market simulation that empirically demonstrated differences in market connectivity utilizing traditional communication channels and fintech enhancements. The simulation results demonstrate significant cost decrease and increased network connectivity by implementing a more versatile infrastructure through fintech providers such as Overbond.

Overbond team engaged with the industry professionals at the CFA Society Toronto luncheon to uncover key trends and challenges in the fixed income markets. Treasurers stressed the importance of an engaged investor base and actively managing their new issue process to align investors’ goals with the issuers. In addition, it is critical to manage relationships with multiple stakeholders, including dealer syndicates, regulators, rating agencies and legal counsel.

With the Overbond suite, buy-side desks around the globe can generate systematic return with a real-time, fully back-tested, proven and transparent methodology that is scalable and interoperable. Overbond’s rich-cheap model (RCM) provides a quantitative method for screening for mispriced fixed income securities. It’s a mean-reversion valuation model designed to pre-identify bonds as rich “sale” and cheap “purchase” candidates based on proprietary Overbond valuation metrics.

The overall aim is the measurement of transaction costs on a sample set of actual Q1/21 cash transactions.

While the absolute goal in trading corporate bonds from a transaction cost perspective is to buy as close to the bid side of the market as possible, and to sell at as close to the ask side as possible in order to reduce costs of transaction.

An appropriate yardstick would be to consider a mid-price quote (half-way between the bid and the ask), that is for contrasting trades execution prices against Overbond bond mid-price levels.

Interoperability is the ability of different systems or programs to communicate with each other, exchange information and use that information. It is particularly important for bringing automated trading to the sell-side and buy-side desks because these desks traditionally have five to 10 pre- existing systems necessary to conduct trading. Automating trading workflow is possible because COBI-Pricing Live is fully interoperable with the existing technologies on the desk.