
Coinbase is working with Canadian regulators on an “Everything Exchange” strategy that would widen local offerings beyond crypto trading to include tokenized stocks, stocks, ETFs and prediction markets in one app.
Coinbase is pressing ahead with plans to broaden its Canadian business beyond cryptocurrency trading under its “Everything Exchange” strategy, which aims to combine crypto, stocks, ETFs and prediction markets on a single platform. Eric Richmond, CEO of Coinbase Canada, said the company is working with local regulators on the rollout but has not set a launch date for Canada. Richmond said Coinbase’s first chapter in Canada was establishing a regulated crypto exchange, while the next phase is to become a broader financial app built on blockchain infrastructure designed to make trading and transfers more seamless and available around the clock. Coinbase became the first international crypto exchange registered in Canada in April 2024, a milestone the company says has helped support its regulatory engagement in the country. A key part of that expansion is tokenized stocks for non-U.S. users, including Canadians, which Richmond said are planned for this month. Coinbase has said the products would represent real shares recorded on a blockchain rather than synthetic exposure, with holders retaining dividend rights. Richmond cast the model as a way to widen access to financial products that are often constrained by market hours, slow settlement and eligibility restrictions. The Canada push follows a broader build-out in the United States, where Coinbase opened stock and ETF trading to eligible users in February 2026 and launched prediction markets in January through Kalshi. Coinbase’s roadmap for the Everything Exchange includes nearly 10,000 stocks and ETFs on one platform. Richmond said the company is also waiting for Canada’s stablecoin framework to be completed, with the Bank of Canada expected to finalize implementing regulations in 2027, before it can list a Canadian dollar stablecoin and fully roll out the model locally.