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Home > Business and Economics > Finance and accounting > Finance and the finance industry > Financial Mathematics and Interest Theory in Actuarial Science With Python: Dense Theory, Targeted Questions, and Full Python Walkthroughs for Rates, Curves, and Risk
Financial Mathematics and Interest Theory in Actuarial Science With Python: Dense Theory, Targeted Questions, and Full Python Walkthroughs for Rates, Curves, and Risk

Financial Mathematics and Interest Theory in Actuarial Science With Python: Dense Theory, Targeted Questions, and Full Python Walkthroughs for Rates, Curves, and Risk


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About the Book

Power through the mathematics of interest and term structure the actuarial way-without fluff. This dense, 33-chapter, problem-driven textbook turns theory into practice and practice into mastery, chapter by chapter. Every topic moves from rigorous derivation to exam-style multiple choice questions to fully worked Python code demonstrations you can run today. What you'll be able to do Value any deterministic cash flow-level, deferred, graduated, or continuous-with exact timing and compounding. Build and stress-test amortization schedules; compute IRR, horizon yields, and realized returns under reinvestment assumptions. Compute duration, convexity, key-rate exposures, and construct hedges or cash-flow matches that actually immunize. Bootstrap and fit yield curves (OIS vs. forwarding), handle negative rates, and reconcile quotes across instruments. Price and analyze bonds, FRNs, FRAs, futures, swaps, and options on rates; find CTD and hedge with duration-based ratios. Model inflation-linked and defaultable cash flows; connect CDS spreads, hazards, and recovery to risky PVs. Work with short-rate (Vasicek/CIR/Hull-White), HJM, and market models; compute PV random variables and sensitivities under stochastic interest. Apply valuation bases for insurance liabilities, use commutation functions efficiently, and implement robust numerical methods. Who this is for Actuarial students and professionals who want a tight, exam-ready and practice-ready reference. Fixed-income and treasury practitioners seeking a principled, code-backed approach to rates and curve construction. Quant-minded learners who prefer proofs, problem sets, and reproducible Python implementations over hand-waving. Inside each chapter Concise theory with worked examples Multiple choice questions with full explanations Complete Python code demonstrations: valuation routines, curve bootstraps, hedging calculators, rate tree builders, Monte Carlo engines, and more Topics you'll cover end-to-end Accumulation/discount, annuities, gradients, and continuous cash flows Amortization, sinking funds, refinancing, and capital budgeting Bond pricing, yield conventions, price-yield dynamics, and realized returns Duration/convexity, immunization, key-rate hedging, and dispersion control Term structure: discount factors, spot/forward rates, bootstrapping, and parametric/spline fits Short-term instruments and day-count conventions Inflation, credit risk, CDS-bond relations, expected loss and spreads Forwards, futures, swaps, CTD, and basis risk Embedded options, OAS, mortgages, prepayments, and negative convexity Stochastic discounting, short-rate and forward-rate models, LIBOR Market Model Liability valuation bases, commutation functions, and numerical implementation Ready to turn mastery into momentum? Start now. Work the theory. Prove it on questions. Lock it in with code. Build career-making fluency in interest theory and financial mathematics today.


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Product Details
  • ISBN-13: 9798263941994
  • Publisher: Independently Published
  • Publisher Imprint: Independently Published
  • Height: 279 mm
  • No of Pages: 320
  • Spine Width: 17 mm
  • Weight: 797 gr
  • ISBN-10: 8263941997
  • Publisher Date: 05 Sep 2025
  • Binding: Paperback
  • Language: English
  • Returnable: N
  • Sub Title: Dense Theory, Targeted Questions, and Full Python Walkthroughs for Rates, Curves, and Risk
  • Width: 216 mm


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Financial Mathematics and Interest Theory in Actuarial Science With Python: Dense Theory, Targeted Questions, and Full Python Walkthroughs for Rates, Curves, and Risk
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