These frictions in fixed income markets create opportunity.
Large number of unique bonds and small number of interested participants.
Broadly blasted market info results in less connections and missed opportunities.
Less willing to use balance sheet, and only focused on the largest clients and trades.
Aim to disrupt infrastructure, change engrained market practices, and drive further segmentation.
The opportunity is to build technology that can enhance the existing market infrastructure, reduce frictions, and add value to all market participants.
We provide this technology.
Recommendation engine technologies appear in every aspect of our daily lives. They generate fast, relevant, and targeted information that focus on the needs and interests of each unique user.
Enter Item of Interest
Allow System to Process
Rank Similar Items
Receive Relevant Information
Recommender systems have fueled the growth of the largest tech and e-commerce companies in the world over the past decade.
They provide fast, relevant, and personalized information, focusing on what matters most to each user.
Enter a favorite song on your internet radio of choice or search a book title on a popular e-commerce website and a recommendation engine generates content that is most interesting and relevant to you.
Enter a bond of interest and our recommendation engine provides the most recent and relevant trade comps from TRACE, similar bonds from the universe, and eventually bonds from the available supply.
Sophisticated techniques of data science and machine learning quickly access similarities between items to classify, rank, and output the most useful information with respect to your search.
We have developed a granular classification algorithm that quickly assesses similarities between bonds allowing for institutional quality and precision in our search results.
Most of the time these systems generate useful information, but in some rare cases recommended content may seem random or unsuitable to the user. This may be problematic in an institutional context.
We account for this by applying granular classification algorithms, quality tiering so users know why results are generated, and flexible filtering to ensure users can customize the information they receive.
The ability to provide relevant information drives business and makes people's lives easier. This is why we believe recommender systems are the future of trade and commerce.
Whether enhancing transparency through trade comps, or enabling discoverability, we are confident this technology can make a valuable impact in fixed income markets.
Our first product applying this technology is designed to streamline and maximize the value of TRACE reporting data.
Transaction data only exists on a small fraction of the outstanding bonds from the universe. We use our technology to relate any bond of interest (in supported markets) to its most relevant TRACE comps.
Uncover suitable alternatives that may not have been on your radar but are actively trading in the market. Our system can greatly increase your market awareness.
Reduce bond search and aggregation times for Traders, Portfolio Managers, Sales, Strategy, Ops, or Risk personnel that need to quickly validate trade levels, research or make fast pricing decisions.
Prevent overpaying or selling too low by using our system to assemble the most meaningful trade comps at the click of a button.
Our team is composed of professionals with diverse backgrounds across fixed income sales and trading, portfolio management, data science and machine learning, software engineering, and combat tested military leadership. We are service oriented and driven to make a positive impact.
Please reach out if you or your organization share our interest, or want to play a part in moving the financial industry forward.
info@Pre-Rec.com
980 6th Ave
New York, NY 10018