▲ Kalshi
Ahead of the US midterm elections on November 3 local time, the amount traded related to the elections in prediction markets has reached approximately $1.9 billion (approx. 2.5 trillion won).
According to calculations by the U.S. daily The Washington Post (WP) based on figures as of 8 p.m. the previous night, the total amount traded on major prediction markets such as Kalshi and Polymarket regarding the outcome of these midterm elections reached $1.9 billion.
Of this total, $1.3 billion was traded on Kalshi, with the remainder traded on Polymarket.
There were over 7,000 betting topics, ranging from the content of specific candidates' campaign speeches to the balance of power in the federal Congress.
This shows that massive amounts of capital are flowing into election-related trades about four years after prediction markets truly entered the mainstream.
During the 2024 presidential election, more than $3.6 billion (approx. 4.8 trillion won) in trades was made on Polymarket alone over whether then-President Donald Trump and then-Democratic candidate Kamala Harris would win.
WP analyzed that the phenomenon of placing financial bets on the specific processes and outcomes of elections, which form the bedrock of democracy, demonstrates how deeply prediction markets have embedded themselves in American society.
However, because trading platforms are diverse and users' identities are anonymized, it is impossible to know precisely who or how many people have bet on the elections.
Consequently, concerns over insider trading and conflicts of interest have been raised.
This year, Kalshi banned transactions such as a North Carolina House candidate betting directly on their own district, and media reports emerged that campaign consultants were placing bets on elections they were involved in.
In response, some lawmakers have introduced legislation to ban election-, terror-, and war-related trades on prediction markets, signaling moves toward stricter regulation.
(Photo: Yonhap News)
※ Please note: This article was translated by AI and may contain errors.
Video News
Video News
Video News
Video News
Video News