1. Get stock price at project kickoff date
| Task | Owner | Start Date | Due Date | Hours |
| Website Redesign | Sarah Chen | 2026-01-15 | 2026-03-31 | 120 |
| API Integration | Marcus Johnson | 2026-02-01 | 2026-04-15 | 85 |
=GOOGLEFINANCE("TICKER:MSFT","price",DATE(2026,1,15))
Result: 425.3
GOOGLEFINANCE retrieves the MSFT closing price on the project start date (2026-01-15). The price attribute returns a single numeric value. This is useful for recording company valuation at project initiation or milestone dates.
2. Fetch daily trading volume for project period
| Task | Owner | Start Date | Due Date | Hours |
| Website Redesign | Sarah Chen | 2026-01-15 | 2026-03-31 | 120 |
| Testing & QA | Elena Rodriguez | 2026-03-01 | 2026-04-30 | 95 |
=GOOGLEFINANCE("TICKER:GOOG","tradevolume",DATE(2026,1,15),DATE(2026,3,31),"DAILY")
Result: Daily volumes: [[2026-01-15, 54320000], [2026-01-16, 48950000], [2026-01-17, 52180000], ...]
By specifying the project's start and end dates with DAILY interval, this returns a complete array of trading volumes. The data can reveal market patterns during project execution and correlate activity with team milestones.
3. Use spreadsheet dates for historical price trends
| Task | Owner | Start Date | Due Date | Hours |
| Mobile App Dev | Marcus Johnson | 2026-02-01 | 2026-04-15 | 85 |
| Security Audit | Sarah Chen | 2026-03-10 | 2026-05-20 | 60 |
=GOOGLEFINANCE("TICKER:AAPL","price",B2,C2,"WEEKLY")
Result: Weekly prices: [[2026-02-02, 192.50], [2026-02-09, 194.20], [2026-02-16, 191.80], ...]
This formula references cells B2 and C2 from the timesheet (start and end dates) to dynamically fetch weekly AAPL prices spanning the project. WEEKLY aggregation reduces the dataset size, making trends easier to spot across multi-week projects.