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.
Key Features
- 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
1. Introduction
2. Financial Markets
2.1 Market price formation
2.2 Returns and dividends
2.2.1 Simple and compounded returns
2.2.2 Dividend effects
2.3 Market Efficiency
2.3.1 Arbitrage
2.3.2 Efficient market hypothesis
2.3.2.1 The idea
2.3.2.2 The critique
2.4 Pathways for further reading
2.5 Exercises
3. Probability distributions
3.1 Basic definitions
3.2 Some important distributions
3.3 Stable distributions and scale invariance
3.4 References for further reading
3.5 Exercises
4. 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
4.6 References for further reading
4.7 Exercises
5. Time series analysis
5.1 Autoregressive and moving average models
5.2 Trends and seasonality
5.3 Conditional heteroskedascisity
5.4 Multivariate time series
5.5 References for further reading and econometric software
5.6 Exercises
6. Fractals
6.1 Basic definitions
6.2 Multifractals
6.3 References for further reading
6.4 Exercises
7. 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
7.8 Exercises
8. 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
8.5 Exercises
9. Option Pricing
9.1 Financial derivatives
9.2 General properties of options
9.3 Binomial trees
9.4 Black-Scholes theory
9.5 References for further reading
9.6 Appendix. The invariant of the arbitrage-free portfolio
9.7 Exercises
10. Portfolio management
10.1 Portfolio selection
10.2 Capital asset pricing model
10.3 Arbitrage pricing theory
10.4 Arbitrage trading strategies
10.5 References for further reading
10.6 Exercises
11. Market risk measurement
11.1 Risk measures
11.2 Calculating risk
11.3 References for further reading
11.4 Exercises
12. Agent-based modeling of financial markets
12.1 Introduction
12.2 Adaptive equilibrium models
12.3 Non-equilibrium price models
12.4 Modeling of observable variables
12.5 References for further reading
12.6 Exercises
Neftci, AN INTRODUCTION TO THE MATHEMATICS OF FINANCIAL DERIVATIVES, 2E (2000, 69.95 (USD) 44.99 (GBP), ISBN: 0125153929)