Uber Shares Soar 3.62% on Cost-Cutting and Expansion $2.27B Volume Ranks 36th in Market Activity

Uber shares closed 3.62% higher on October 6, 2025, with a trading volume of $2.27 billion—up 121.68% from the previous day and ranking 36th in market activity. The stock’s surge followed a strategic update highlighting cost-cutting measures and expansion plans in high-growth markets. The company announced a 12% reduction in corporate workforce and a shift to third-party logistics partners in select regions to improve operational efficiency. Additionally, Uber reiterated its commitment to increasing driver compensation by 5% in North America and Europe by year-end, balancing cost discipline with workforce retention goals.

Analysts noted the stock’s performance aligned with positive investor sentiment toward tech sector resilience amid broader market volatility. The company’s focus on margin optimization, including a 15% reduction in marketing spend through AI-driven customer acquisition, was cited as a key driver. Regulatory developments also played a role, as Uber secured a favorable ruling in a key European antitrust case, reducing uncertainty in its international operations. The stock’s strong volume suggests renewed institutional interest, though short-term momentum remains sensitive to macroeconomic indicators.

I understand the spirit of the strategy, but I’d like to confirm a couple of implementation details before running the back-test, because the current toolset is designed to test one ticker (or one synthetic series) at a time: 1. Daily “top-500‐by-volume” is a cross-sectional portfolio that changes every day. • Our back-testing engine can evaluate a single time-series (one ticker or one synthetic index). • To test the full portfolio precisely, we would first need to build a synthetic index that tracks the equal-weight return of those 500 stocks each day, then feed that index into the engine. 2. Two practical approaches: A) Build the synthetic index (requires pulling daily volume & price data for the entire tradable universe, ~3+ years, and aggregating). B) Simplify/approximate—for example, test the idea on a subset (e.g., the S&P 500 constituents) or on a single high-liquidity ETF as a proxy. Would you like me to proceed with the full synthetic-index approach (more data, longer run-time), or use a simplified proxy method?