Tradeweb Markets Posts 10.9% YoY Increase in Q1 ADV

The online fixed income trading platform Tradeweb Markets has released its financial metrics for the first quarter in 2022 ended March 31, showing a 13.9% yearly increase with its quarterly revenues at $311.5 million for the period.

Fazzaco Live Webinar on 12th May: Vladimir Moshkov on How to Start a Crypto Exchange from Scratch

According to the press release, for the quarter, the average daily volume (ADV) reached $1.2 trillion, an increase of 10.9% compared to prior year period, with record ADV in U.S. and European government bonds.

Moreover, Tradeweb witnessed $97.4 million in net income, while its adjusted net income was $115.1 million for the first quarter of the current year, increases of 19.5% and 13.3% respectively from prior year period.

Tradeweb achieved 51.6% adjusted EBITDA margin or $160.6 million adjusted EBITDA for the quarter, compared to 52.0% or $142.1 million respectively for prior year period.

Lee Olesky, Chairman and CEO, Tradeweb Markets, said:"Tradeweb surpassed $300 million in quarterly revenue for the first time in our history, showcasing the diversity of our business with strong contributions from rates, credit and equities. Increased rates volatility in the first quarter of 2022 contributed to record volumes in U.S. Treasuries, European government bonds and swaps. Credit delivered a record revenue quarter driven by broad-based product growth and strong corporate bond client engagement across RFQ, Tradeweb AllTrade, and Portfolio Trading – which saw a ~60% YoY increase in the number of firms using the tool."

"In February, our board announced succession plans for the company; I was honored to be appointed Chairman, and I am tremendously excited that my longtime partner Billy Hult will succeed me as CEO on January 1, 2023. Tradeweb has an outstanding leadership team and we believe we are well positioned for the future."

Earlier this month, Tradeweb announced the launch of Tradeweb Ai-Price for municipal bonds, which will use machine learning and proprietary data science to calculate daily prices for municipal bonds.