Workday's 60% Trading Volume Surge Pushes It to 121st in Market Activity Despite Slight Stock Drop

On September 5, 2025, Workday (WDAY) traded with a volume of $0.82 billion, a 60.08% increase from the previous day, ranking it 121st in market activity. Despite the surge in trading volume, the stock closed marginally lower by 0.02%.

Institutional investors have significantly increased their stakes in Workday during the first quarter. Alyeska Investment Group L.P. boosted its position by 235.3%, holding shares valued at $87.03 million. Other major players, including Advent International and Generation Investment Management, also expanded their holdings, with Advent’s stake rising by 407.8%. Collectively, hedge funds and institutional investors now control 89.81% of the company’s shares.

Workday reported strong second-quarter earnings, with EPS of $2.21, exceeding estimates of $2.09. Revenue grew 12.6% year-over-year to $2.35 billion. However, the stock faced downward pressure after management issued cautious Q3 guidance, which fell short of expectations. The company also announced the acquisition of AI firm Paradox to enhance its talent acquisition solutions, a move analysts view as strategic but insufficient to offset broader market concerns.

Insider activity added to the stock’s volatility. Major shareholder David Duffield sold 72,551 shares, reducing his ownership by 41.33%, while CEO Carl Eschenbach offloaded 6,250 shares, cutting his stake by 80.94%. The combined sales by insiders in the last quarter totaled 325,880 shares, valued at $78.45 million.

Analyst sentiment remains mixed. Zacks Research raised its FY2026 EPS forecast to $3.57 per share, reflecting confidence in Workday’s growth trajectory. However, several firms trimmed price targets, with KeyCorp reducing its estimate to $285 and Bernstein to $304. The stock currently holds an average rating of “Moderate Buy” with a consensus target price of $286.81.

It sounds like you want to simulate a daily-rebalanced, 1-day-holding portfolio that: 1. Every trading day from 2022-01-01 onward 2. Ranks the entire U.S. equity universe by that day’s dollar trading volume 3. Buys the top 500 names in equal weight at the close (or the next day’s open, depending on your execution assumption) 4. Sells them one trading day later 5. Tracks the cumulative portfolio return and basic risk metrics. Within our current back-testing tool set, each “strategy_backtest” run is designed for a single-ticker position file, not for a large daily-changing multi-ticker basket. To build your requested portfolio study we would need to: • Pull daily volume and close prices for the whole U.S. stock universe for 2022-01-01 → present. • Re-rank the universe each day and create a 500-ticker basket. • Calculate the equal-weighted portfolio return from close-to-close (or open-to-close, depending on execution). That workflow sits outside the scope of the one-ticker backtest engine we have available in this chat (it would require a custom multi-asset back-testing environment). Two practical options: A. Narrow the scope to a single security or ETF (e.g., SPY) and back-test “buy on high-volume days” as an event study. B. Let me outline the full data-processing steps (with Python/pseudocode) so you can run the portfolio back-test offline. Could you confirm which path you’d like to take—or clarify any adjustments to the spec (e.g., use the S&P 500 universe, test a particular ETF proxy, change holding period, etc.)?