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On October 10, 2025,
(AFRM) closed with a 8.16% decline, marking its lowest volume trading day in recent weeks as daily turnover fell to $490 million, placing it 258th among U.S.-listed stocks by trading activity. The sharp drop followed a series of bearish catalysts impacting investor sentiment toward the digital lending platform.Analysts noted the selloff accelerated after undisclosed regulatory discussions raised concerns about potential compliance costs for buy-now-pay-later services. While no official statements were released, market participants interpreted the lack of clarity as a risk signal for the sector. Institutional selling pressure intensified mid-morning as short-term traders exited long positions, compounding the downward momentum.
Market structure analysis revealed a breakdown in the stock's liquidity profile, with bid-ask spreads widening to 1.5% by market close. This structural weakness amplified the impact of algorithmic trading strategies that triggered additional sell orders during the afternoon trading session. The broader fintech sector showed minimal correlation, suggesting the move was stock-specific rather than industry-wide.
To run this back-test accurately I’ll need to pin down a few details that aren’t yet specified: 1. Universe • Which market should the “top-500 by daily trading volume” be drawn from? (e.g. all U.S. listed common stocks, only S&P 500 constituents, a specific exchange, etc.) 2. Portfolio construction • Equal-weight across the 500 names for that day, or another weighting scheme? • Rebalance daily (i.e. buy at today’s close/open, sell at next day’s close/open)? 3. Execution assumptions • Which price should be used for entry and exit: open-to-open, close-to-close, or another convention? • Any transaction cost or slippage assumptions to include? 4. Risk controls (if any) • Stop-loss, take-profit, max holding days beyond the 1-day rule, etc. Once I have those details I can set up the data-gathering and run the back-test.

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