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Teach Your Students How to Become Successful Working QuantsQuantitative Finance: A Simulation-Based Introduction Using Excel provides an introduction to financial mathematics for students in applied mathematics, financial engineering, actuarial science, and business administration. The text not only enables students to practice with the basic techn

1. Preface
2. Author
3. Chapter 1 - Introduction
4. Chapter 2 - Intuition about Uncertainty and Risk
1. 2.1 CHAPTER SUMMARY
2. 2.2 Introduction
3. 2.3 Individual Attitudes toward Risk
4. 2.4 The St. Petersburg Paradox
5. 2.5 Looking Forward to Chapter 3
6. Exercises
5. Chapter 3 - The Classical Approach to Decision Making under Uncertainty
6. Chapter 4 - Valuing Investment Opportunities: The Discounted Cash Flow Method
1. 4.1 CHAPTER SUMMARY
2. 4.2 Discounted Cash Flow Method for Evaluating Investment Opportunities
3. 4.3 Conclusions
4. Exercises
7. Chapter 5 - Repaying Loans over Time
1. 5.1 CHAPTER SUMMARY
2. 5.2 Introduction
3. 5.3 Repaying a Loan over Time: Excel
4. 5.4 Repaying a Loan over Time: Mathematics
5. 5.5 First-Order Difference Equations
6. 5.6 Solving the Loan Repayment Difference Equation
7. 5.7 More Examples of Using Difference Equations to Find Loan Payments
8. 5.8 Writing the Difference Equation in Forward versus Backward Forms
9. 5.9 Bridges to the Future
10. Exercises
8. Chapter 6 - Bond Pricing with Default: Using Simulations
9. Chapter 7 - Bond Pricing with Default: Using Difference Equations
10. Chapter 8 - Difference Equations for Life Annuities
11. Chapter 9 - Tranching and Collateralized Debt Obligations
1. 9.1 CHAPTER SUMMARY
2. 9.2 Collateralized Debt Obligations
3. 9.3 Tranched Portfolios
4. 9.4 The Detailed Calculation
5. 9.5 Correlation of Two Identical Bonds
6. 9.6 Conclusion
7. Exercises
12. Chapter 10 - Bond CDOs: More than Two Bonds, Correlation, and Simulation
13. Chapter 11 - Fundamentals of Fixed Income Markets
1. 11.1 CHAPTER SUMMARY
2. 11.2 What Are Bonds?
3. 11.3 Getting Down to Quantitative Details
4. 11.4 Simplest Bond Pricing Equation
6. 11.6 Clean and Dirty Bond Prices
7. 11.7 Conclusion and Bridge to the Next Chapter
8. Exercises
14. Chapter 12 - Yield Curves and Bond Risk Measures
1. 12.1 CHAPTER SUMMARY
2. 12.2 Introduction
3. 12.3 Constructing Yield Curves from Bond Prices
4. 12.4 Bond Price Sensitivities to the Yield
5. Exercises
15. Chapter 13 - Forward Rates
16. Chapter 14 - Modeling Stock Prices
17. Chapter 15 - Mean Variance Portfolio Optimization
1. 15.1 CHAPTER SUMMARY
2. 15.2 Selecting Portfolios
3. 15.3 CAPM and Markowitz
4. Exercises
18. Chapter 16 - A Qualitative Introduction to Options
19. Chapter 17 - Value at Risk
20. Chapter 18 - Pricing Options Using Binomial Trees
21. Chapter 19 - Random Walks
22. Chapter 20 - Basic Stochastic Calculus
1. 20.1 CHAPTER SUMMARY
2. 20.2 Basics of Stochastic Calculus
3. 20.3 Stochastic Integration by Examples
1. 20.3.1 Review of the Left Endpoint Rule of Introductory Calculus
2. 20.3.2 Itô Integration
3. 20.3.3 Itô Isometry
4. 20.3.4 Introduction to Ordinary Differential Equations
5. 20.3.5 Solution of SDEs
4. 20.4 Conclusions and Bridge to Next Chapters
5. Exercises
23. Chapter 21 - Simulating Geometric Brownian Motion
24. Chapter 22 - Black Scholes PDE for Pricing Options in Continuous Time
25. Chapter 23 - Solving the Black Scholes PDE
26. Chapter 24 - Pricing Put Options Using Put Call Parity
27. Chapter 25 - Some Approximate Values of the Black Scholes Call Formula
28. Chapter 26 - Simulating Delta Hedging
29. Chapter 27 - Black Scholes with Dividends
30. Chapter 28 - American Options
31. Chapter 29 - Pricing the Perpetual American Put and Call
32. Chapter 30 - Options on Multiple Underlying Assets
33. Chapter 31 - Interest Rate Models
34. Chapter 32 - Incomplete Markets
1. 32.1 CHAPTER SUMMARY
2. 32.2 Introduction to Incomplete Markets
3. 32.3 Trying to Hedge Options on a Trinomial Tree
4. 32.4 Minimum Variance Hedging of a European Option with Default
5. 32.5 Binomial Tree Model with Default Risk
6. EXERCISE
35. Appendix 1: Probability Theory Basics
1. A1.1 Introduction
2. A1.2 Conditional probability
3. A1.3 Independence
4. A1.4 Factorials, “choose” notation, and Stirling’s formula
5. A1.5 Binomial random variables
6. A1.6 Mean and variance
7. A1.7 SOME USEFUL CONTINUOUS PDFs
8. A1.8 NEW RANDOM VARIABLES FROM OLD: LINEAR TRANSFORMATIONS
9. A1.9 JOINT DENSITIES
10. A1.10 Combining random variables
11. A1.11 Moment-generating functions
12. A1.12 Poisson distribution
13. A1.13 Relationship between the Poisson, binomial, and exponential RVs
14. A1.14 MGFs and THE NORMAL RANDOM VARIABLE