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On October 1, 2025,
(V) rose 1.89% to close its session with a trading volume of $2.86 billion, ranking 31st among U.S. stocks by liquidity. The move followed a strategic shift in global payment processing regulations, which analysts suggest could expand the company's market share in cross-border transactions.Regulatory updates in key markets including the European Union and Southeast Asia introduced new compliance frameworks that align with Visa's existing infrastructure. This alignment reduces operational friction for merchants adopting digital payment solutions, potentially accelerating adoption rates in regions with growing e-commerce sectors.
Market participants noted that Visa's recent earnings report highlighted a 12% year-over-year increase in cross-border transaction volumes, driven by improved interchange fee structures in Asia-Pacific markets. The company's Q3 guidance also emphasized cost optimization initiatives, which analysts project could yield $450 million in annualized savings by 2026.
To set up this back-test properly I need to pin down a few practical details: 1. Universe • Do you mean “all U.S. listed common stocks” (NYSE + NASDAQ + AMEX) or a narrower list (e.g., S&P 1500 constituents, Russell 3000, etc.)? • ADRs, ETFs, and preferred shares: include or exclude? 2. Weighting & rebalancing • After selecting the 500 highest-volume names each day, should the position be equally weighted (1/500 each) or volume-weighted? • Any cash left un-invested or do we use full notional every day? 3. Friction • Commission/slippage assumptions (if any). • Do we allow partial fills or assume all trades execute at the close? 4. Benchmark / output preference • Any specific benchmark for relative performance (e.g., SPY)? • Key metrics you’d like besides cumulative return and max drawdown (e.g., Sharpe, turnover, etc.). Once I have this, I can generate the data-retrieval plan and run the back-test.

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