Solve Advisors CEO Eugene Grinberg recently joined Thinknum’s Co-Founder Justin Zhen in a webinar titled “Alternative Data for Fixed Income Investors: Insights and Use Cases,” to explore how buy-side investors can leverage fixed income data to generate alpha. More specifically, can superimposing Solve’s pricing data and Thinknum’s alternative fundamental data result in strong relationships indicating that one is a leading indicator of the other. If that is indeed the case, such analysis can be used to identify situations where changes in fundamentals have not yet been reflected in the markets, enabling the buy side to generate alpha. Three illustrations were reviewed and below are highlights of their discussion.

• Performance of the bonds issued by ecommerce players exhibit very strong correlation with Web-traffic

We began with a hypothesis that a company’s web traffic patterns could be a leading indicator of shifts in bond pricing. If this were validated, fixed income investors could gain an edge by leveraging alternative data in pricing decisions. Correlation analysis was run between Thinknum’s web traffic and SolveQuotes’ EBAY, ETSY and WIX corporate bond pricing data. Between the months of March 2020 and January 2021, ETSY and WIX exhibited a clear correlation between increased web-traffic and bond price. ETSY’s correlation of .88 and R2 of 77% was particularly notable.

In this case, Eugene and Justin agreed there is actionable insight that can be leveraged by fixed income investors. In this case WIX and ETSY bonds are convertibles, which will reflect changes in the underlying equity prices, but nevertheless the data suggests that significant changes in web traffic will quickly be reflected in the bond price.

• Increased job listings indicate business expansion and hence better outlook for the issuer in medium term

• But in short term, increased hiring means higher capex for the company and increased liquidity risk for the investors

• Overall job listings shows direct relation with spreads in near term

Our second hypothesis was that a company’s job postings might be indicative of future bond performance. We looked at a scatter plot of the delta in job postings for a half a dozen issuers. The y axis is their treasury spread. What intuitively made sense to us was that as job postings increased, it would be perceived as an indication of positive things happening at the company and be reflected in the tightening of the spreads. But the data showed the opposite. Instead, there may be an expectation of higher capex or liquidity risk in the near term. As the delta in the job postings increased, so did the delta in the treasury spread.

The analysis and discussion illustrated a large opportunity to leverage alternative data and bond pricing data in fixed income investment strategies and processes. Solve’s offerings include four types of datasets which create unparalleled transparency and insight into the market – (1) granular real-time observable bids, offerings, and other market color that can be sources from firms’ own messages, (2) similar granular pricing data that Solve collects from its contributor network, (3) composite pricing which allows consolidating granular levels into consensus bids and offers utilizing Solve’s proprietary algorithms, and (4) post-trade TRACE executed levels. In competitive markets, the combined datasets can be leveraged to get an edge and more effectively generate alpha.

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