Quantitative Finance for Physicists

Contents

1. Introduction
2. Financial Markets
3. 1 Market price formation2.2 Returns and dividends 2.2.1 Simple and compounded returns 2.2.2 Dividend effects2.3 Market Efficiency 2.3.1 Arbitrage 2.3.2 Efficient market hypothesis 2.3.2.1 The idea 2.3.2.2 The critique
4. 4 Pathways for further reading
5. 5 Exercises
6. Probability distributions
7. 1 Basic definitions
8. 2 Some important distributions
9. 3 Stable distributions and scale invariance
10. 4 References for further reading
11. 5 Exercises
12. Stochastic processes 4.1 Markov process 4.2 Brownian motion 4.3 Stochastic differential equation. Ito’s lemma 4.4 Stochastic integral 4.5 Martingales
13. 6 References for further reading
14. 7 Exercises
15. Time series analysis 5.1 Autoregressive and moving average models
16. 2 Trends and seasonality
17. 3 Conditional heteroskedascisity
18. 4 Multivariate time series
19. 5 References for further reading and econometric software
20. 6 Exercises
21. Fractals
22. 1 Basic definitions
23. 2 Multifractals
24. 3 References for further reading
25. 4 Exercises
26. Nonlinear dynamical systems 7.1 Motivation 7.2 Discrete systems: Logistic map 7.3 Continuous systems 7.4 Lorenz model 7.5 Pathways to chaos 7.6 Measuring chaos 7.7 References for further reading
27. 8 Exercises
28. Scaling in financial time series 8.1 Introduction 8.2 Power laws in financial data 8.3 New developments 8.4 References for further reading
29. 5 Exercises
30. Option Pricing
31. 1 Financial derivatives
32. 2 General properties of options
33. 3 Binomial trees
34. 4 Black-Scholes theory
35. 5 References for further reading9.6 Appendix. The invariant of the arbitrage-free portfolio
36. 7 Exercises
37. Portfolio management 10.1 Portfolio selection
38. 2 Capital asset pricing model
39. 3 Arbitrage pricing theory 10.4 Arbitrage trading strategies
40. 5 References for further reading
41. 6 Exercises
42. Market risk measurement
43. 1 Risk measures
44. 2 Calculating risk 11.3 References for further reading
45. 4 Exercises
46. Agent-based modeling of financial markets 12.1 Introduction
47. 2 Adaptive equilibrium models
48. 3 Non-equilibrium price models
49. 4 Modeling of observable variables
50. 5 References for further reading
51. 6 Exercises

With more and more physicists and physics students exploring the possibility of utilizing their advanced math skills for a career in the finance industry, this much-needed book quickly introduces them to fundamental and advanced finance principles and methods.

Quantitative Finance for Physicists provides a short, straightforward introduction for those who already have a background in physics. Find out how fractals, scaling, chaos, and other physics concepts are useful in analyzing financial time series. Learn about key topics in quantitative finance such as option pricing, portfolio management, and risk measurement. This book provides the basic knowledge in finance required to enable readers with physics backgrounds to move successfully into the financial industry.

• Short, self-contained book for physicists to master basic concepts and quantitative methods of finance
• Growing field—many physicists are moving into finance positions because of the high-level math required
• Draws on the author's own experience as a physicist who moved into a financial analyst position

Physics students following a course on finance worldwide, students in econophysics and quantitative finance, physicists interested in moving into professional finance positions.