This is the kind of question where you start strong and then slowly realize how much ground it actually covers.
Structure your answer as a logical flow from instruments to analytics to risk to strategies, emphasizing how each concept builds on the previous one. Use concrete examples and connect the concepts to practical trading applications, showing both breadth and depth. Tailor the technical depth to a software engineering audience by highlighting data structures, algorithms, and system design considerations where relevant.
Pro tip: Demonstrate that you understand the 'why' behind each concept—e.g., why duration matters for hedging, why convexity is a second-order effect—and mention how these concepts are implemented in trading systems (e.g., yield curve construction, real-time risk calculations). This shows you can bridge finance and software engineering.
Start by categorizing fixed-income instruments (government bonds, corporate bonds, municipals, agency MBS, etc.) and explain how their cash flows are structured (coupons, principal repayment, prepayment optionality).
Define yield (YTM, current yield), duration (Macaulay, modified), convexity, credit spreads, and the yield curve. Explain how they are calculated and what they measure.
Identify major risks: interest rate risk, credit risk, liquidity risk, inflation risk, and prepayment risk. Explain how each risk is measured and managed.
Describe real trading strategies such as duration hedging, curve steepeners/flatteners, credit spread arbitrage, and relative value trades. Specify the market conditions (e.g., steepening yield curve, widening spreads) that make each strategy profitable.
Tie the concepts to software engineering by discussing how trading systems implement these analytics (e.g., real-time curve bootstrapping, risk engines, order management) and the technical challenges involved.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.