FINA 6337 — Computational Methods in Finance
3 semester hoursGraduateLectureusually offered: falltypical days: TBostonTraditional
Studies various computational methods in finance. Analyzes market data and build trading strategies. Uses interpolation, solver, and optimization methods to calibrate discount curve and volatility surfaces to market prices. Analyzes market data and applies dimension-reduction techniques such as principal component analysis (PCA). Applies time-series analysis and PCA to implement and back test trading strategies.
Offering history
| Term | Sections | Enrolled | Capacity | Full | Open seats/section |
|---|---|---|---|---|---|
| Summer B 2023 | 1 | 16 | 35 | 46% | 19.0 |
| Fall 2023 | 1 | 40 | 40 | 100% | 0.0 |
| Spring 2024 | 1 | 17 | 40 | 43% | 23.0 |
| Summer A 2024 | 1 | 15 | 40 | 38% | 25.0 |
| Fall 2024 | 1 | 22 | 40 | 55% | 18.0 |
| Summer A 2025 | 1 | 9 | 40 | 23% | 31.0 |
| Fall 2025 | 1 | 18 | 30 | 60% | 12.0 |
Snapshots from scheduled scrapes — not live seat availability. "Full" can exceed 100% when sections over-enroll.
Meeting times
Share of recent sections by weekday: M 12% · T 59% · W 12% · Th 47% · F 42%
Common patterns: TF (42% of sections), R (29% of sections), TR (18% of sections), MW (12% of sections) — in patterns, R means Thursday
Professors
Fall
- Sunayan Acharya (73% of students) · reviews
- Milivoje Davidovic (28% of students) · reviews
Spring
- Sunayan Acharya (100% of students) · reviews
Summer A
- Sunayan Acharya (100% of students) · reviews
Summer B
- Sunayan Acharya (100% of students) · reviews
Percentages are each professor's average share of the season's enrolled students in recent terms.
Links
Official catalog (FINA course descriptions) · Student reviews on RateMyHusky · All FINA courses · Plan it at numap.app
More
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"retired": true,
"retiredSince": "2026-09-03"
}