代做mathematical modeling, pricing and trading strategies代写Python编程

A. Course description

The course objective is to introduce students to mathematical modeling, pricing and trading strategies for credit instruments.

The course will cover:

- corporate and sovereign bonds

- credit default swaps (CDS) and credit default indices (CDX),

- fixed income ETFs,

- collateralized debt obligations (CDOs),

- mortgage and municipal bonds.

Real market data examples will be used for pricing and risk management.

The students will have the opportunity to discuss various trading strategies with market practitioners, for a better insight into the "daily activity" of credit trading desks.

B. Prerequisites

Undergraduate-level calculus, linear algebra, and probability. Familiarity with fixed income financial instruments, in particular US Treasuries, SOFR swaps/futures. Intermediate programming knowledge in Python. Some familiarity with Bloomberg terminals would be a plus.

C. Grading

50% homework

40% final exam

10% participation

D. Final Exam

The final exam will take place on Tuesday May 27 2025 in the same location as the class - MS 112.

The exam will start at 12:30pm and finish at 3:15pm, for a total of 2h 45 mins.

It will cover programming as well as conceptual & math questions.

E. Course outline

Session 1 (Cash Instruments)

Quick introduction to history of credit markets

What is credit default risk?

Overview of cash credit instruments: corporate bonds and loans

Market segments / role of credit rating agencies

Fixed vs floating rate coupons, contractual cashflows, seniority ranks, credit events

Coupon accrual, “dirty” vs. “clean” prices, settlement dates

Quoting conventions: prices, yields and spreads to benchmarks / “YAS screen” in Bloomberg

Embedded optionality in callable bonds: computation of workout dates

Valuation and risk management: DV01, duration, carry, curve rolldown, convexity, jump-to-default

Trading details: OTC vs. electronic venues, average volumes, TRACE reporting facility

Session 2 (Derivative/Synthetic Instruments)

Sovereign bonds

Corporate bond indices and credit ETFs (LQD, HYG, EMB)

Financed floating rate bonds

Overview of synthetic instruments: credit default swaps, CDX IG/HY credit indexes

CDS as a portfolio hedge against issuer credit defaults

CDX as macro trading product

Role of ISDA committee: determining default event, recovery rate auctions

Quoting conventions: price upfronts, quoted spreads, par spreads, index rolls

ISDA standard pricing model / “CDSW screen” in Bloomberg

Session 3 (Pricing and Risk Analytics)

QuantLib as pricing and risk analytics library

Overview of Python example notebooks

Understanding pricing for:

- generic (fixed & floating rate) cashflows

- risk-free government bonds

- IR swaps (SOFR)

- SOFR and Fed Funds futures

- risky corporate bonds

- fixed income ETFs

Risk-free curve calibration (bootstrapping) using:

- US cash (on-the-run) treasuries

- SOFR swaps/futures

- Fed Fund futures

- cash Bunds (EUR curve)

Risk management: duration, convexity and bucketed IR risks

Session 4 (The Hazard Rate Model)

Pricing generic credit instruments using the hazard rate model

Bootstrapping survival probability and hazard rate curves

Issuer credit curve shapes and the connection to the credit cycle

CDS pricing in the hazard rate model

ISDA CDS standard pricing model

CDX IG/HY valuation and risks

Risky bond pricing in the hazard rate model

Derivation of price sensitivites: IR01, CS01, REC01, JTD

Yield/spread vs. hazard rate models

Session 5 (Curve Shape Models)

Historical PCA analysis of bond yield curves

Parametric yield curves: Nelson-Siegel model and extensions

Smooth credit curve models

Issuer curve calibration in hazard rate space

Interpreting model results: edges and alpha signals

Quantitative trading in credit markets

Managing risks: credit spread, interest rates, “jump-to-default”, funding

Portfolio construction and trade execution

Strategy backtesting

Trading strategy examples

Session 6 (Trading Insights with Market Practitioners)

David Hermann, senior portfolio manager

Dan Wang, senior quantitative researcher

Insights into daily activity of a credit trading desk

Overview of various credit instruments and trading strategies

Fundamental vs Quantitative approach to trading

Q&A session on recent events in US investment grade credit markets

Session 7 (Structural Credit Models)

Structural approach to credit default risk

Structural credit models: the Merton model

Fair value of equity

Fair value of risky bonds

Leverage effect and equity volatility smiles

Capital structure strategies

Session 8 (Correlated Defaults and CDOs)

Correlated Defaults in the Merton model

Modeling credit losses in pools of risky instruments

Loss distributions for general (non-homogeneous) pools

Collateralized Debt Obligations

CDO tranches and structural subordination waterfalls

Synthetic CDO Pricing / CDX IG Index tranches

Base Correlation model and CDO quoting conventions

CDOs in the 2008 financial crisis

Session 9 (Mortgage and Municipal Bonds)

Mortgage Backed Securities (MBS)

Origination, pooling, securitization, issuance, and trading

Pricing and risk management

Role of GSEs and government agencies

Impact of credit rating agencies

Collateralized Mortgage Obligations (CMOs)

Mortgage Backed Securities in the 2008 financial crisis

Municipal bonds: specs, pricing, credit risk and tax benefits

Building smooth credit curve models for municipal bonds

Investing in municipal bonds via ETFs



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