Quick overview

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Canary the XRP ETF (XRPC) saw a decline in trading volume on day two, extending XRP’s losing streak to six sessions on Sunday.

 

The broader cryptocurrency market plummeted this week due to fading expectations of a December Fed rate cut. With net outflows of $1.11 billion during the reporting week ending November 14, the BTC-spot ETF reflected the market sentiment.

XRP experienced a dramatic reversal despite the upcoming launch of 21Shares, Bitwise, CoinShares, and Franklin Templeton XRP-spot ETFs in the following week.

XRP made a strong impression with $245 million in net inflows and $59 million in trading volume on its first day of trading, but by Friday, volumes dropped to $26 million, impacting demand for XRP on Saturday, November 15. Outflows from BTC-spot ETFs and the broader sell-off in the crypto market likely affected institutional demand.

However, with the introduction of Bitwise and Franklin Templeton’s XRP-spot ETFs, demand for XRP could increase significantly in the upcoming week.

The Bitwise XRP ETF is scheduled to go live on November 19 or 20. With no BlackRock (BLK) iShares XRP Trust, analysts believe Franklin Templeton and Bitwise will dominate the XRP-spot ETF market. Strong inflows could potentially reverse recent losses.

Although robust ETF inflows are promising, they do not guarantee price appreciation, despite optimistic forecasts. Ethereum-based ETFs experienced net outflows for just one month between November 2024 and October 2025, despite generating approximately $14.7 billion in total net inflows during that period. Due to supply-side factors and broader market pressures, Ethereum did not sustain a price increase despite these large inflows. This illustrates that significant inflows alone might not be enough to drive consistent price gains.

Overall, a scenario of $600 million in monthly inflows is plausible and has precedents in other crypto ETF markets, but its direct effect on XRP’s price would depend on various external factors. ETF demand is just one among many variables influencing long-term price trends, and actual outcomes may differ significantly from model predictions.