Analysis of Fixed Income Securities

Analysis of Fixed Income Securities covers fixed income securities and derivatives, asset-backed/mortgage-backed securities, pricing and portfolio strategies, and term structure models.

offering recorded3 credits
Recorded instructors · Spring 2027 Ivan Shaliastovich

Summary

1 / 3

Recent recorded grades — Spring 2025: 3.31 GPA, 53.8% A/AB (n=26 letter grades); Fall 2025: 3.67 GPA, 82.6% A/AB (n=23 letter grades); Spring 2026: 3.57 GPA, 71.4% A/AB (n=7 letter grades).

What you’ll be able to do

  • Utilize and be comfortable with the mathematics of fixed income markets.

  • Utilize appropriate tools and techniques, including various measures of duration and convexity, to make decisions about trading and hedging portfolios of fixed income securities.

  • Explain the structure and uses of fixed income derivative instruments, including options, forwards, and swaps.

Source: UW Guide

Grade history

↗
average GPA
letter grades
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AB
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All recorded terms · compare terms & instructors

Prerequisites

Course map

(FINANCE 700 and GEN BUS 704) or declared in graduate Business Exchange program

FINANCE 740

This is a best-effort interpretation; check the catalog requirements above.

Prerequisite text tree

Professors

Spring 2027

Recent recorded grades — Spring 2024: 3.75 GPA, 78.6% A/AB (n=14 letter grades); Spring 2025: 3.31 GPA, 53.8% A/AB (n=26 letter grades); Spring 2026: 3.57 GPA, 71.4% A/AB (n=7 letter grades). Includes jointly taught sections.

Historical instructors & teaching patterns

IVAN SHALIASTOVICH is recorded teaching in Spring 2017, Spring 2018, Spring 2019, Spring 2020, Spring 2022, Spring 2024, Spring 2025, Spring 2026. Recorded history may be incomplete and does not establish a future schedule.

Recorded history may be incomplete and does not establish a future schedule.

Calendar & sections

Spring 2027

Schedule loads here as you scroll.

SectionModeEnrolled / capacityWaitlist
LEC 001Classroom Instruction0 / 100

Times are Central. Select a meeting for details; export includes recorded dates for the selected sections. Enrollment reflects scan time.

Meeting source records

Student experience

the class

Recent recorded grades — Spring 2025: 3.31 GPA, 53.8% A/AB (n=26 letter grades); Fall 2025: 3.67 GPA, 82.6% A/AB (n=23 letter grades); Spring 2026: 3.57 GPA, 71.4% A/AB (n=7 letter grades).

difficulty & workload

No workload feedback recorded.

Topics

  • Fixed income securities and derivatives
  • Asset-backed and mortgage-backed securities
  • Pricing and portfolio strategies
  • Term structure models and analytical tools

Skills

  • Mathematics of fixed income markets
  • Trading and hedging portfolios using duration and convexity
  • Structure and uses of fixed income derivatives

Grades

Latest available · Spring 2026— not enough history to project Spring 2027.

average GPA
A / AB grades
letter grades
Instructor

Grade distribution · % of letter grades

A
AB
B
BC
C
D
F

Grades over time

Through Spring 2026

More grade details Grade mix, volume & source data

Not enough comparable courses for Spring 2027 in UW–Madison.

Sources & history

UW–Madison

Catalog & offerings

Descriptions, prerequisites, and recorded course offerings.

Catalog observation history

Observations at scan time; dates do not imply when a catalog change took effect.

Selected offering source records
FINANCE 740 · Spring 2027

Analysis of Fixed Income Securities

Recorded 2026-10-14
Raw records
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    "course_id": "FINANCE 740",
    "course_uid": "course_41cf0022a0de496bf7e82138",
    "term_id": "1274",
    "source_course_id": "003063",
    "source_subject_id": "233",
    "title": "Analysis of Fixed Income Securities",
    "credits_min": 3,
    "credits_max": 3,
    "typically_offered": "Occasionally"
  }
]
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Student reviews

Original comments behind the course and instructor summaries.

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Madgrades

Grade history

Recorded grade distributions by term, section, and instructor.

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Model outputs & technical records
Qwen/Qwen3.8-27B
LLM outputs across runs
Full model traces

Recorded model configuration, reasoning, and tool conversations.

Model & dataset provenance
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