經濟物理學導論 : 金融中的關聯性和複雜性

《經濟物理學導論 : 金融中的關聯性和複雜性》是2016年世界圖書出版公司出版的著作，作者是Rosario、N.Mantegna、H.Eugene、Stanley。

基本介紹

• 書名：《經濟物理學導論 : 金融中的關聯性和複雜性》
• 作者：Rosario、N.Mantegna、H.Eugene、Stanley
• 出版社：世界圖書出版公司
• 出版時間：2016年01月01日
• ISBN：9787519200176 

內容簡介

《經濟物理學導論 金融中的關聯性和複雜性（英文版）》關注金融體系描述中所用的經濟物理學概念。特別地，作者闡明了機率論、臨界現象及充分發展紊流中的尺度概念。將這些概念套用到金融時間序列中能很好地洞察市場行為。作者還描述了幾個隨機模型，展示了經驗數據中體現出來的統計特性。

《經濟物理學導論 金融中的關聯性和複雜性（英文版）》讀者對象：經濟學和物理學領域的本科生及科研工作者，金融學領域的專家等。

目錄

Preface

1 Introduction

1．1 Motivation

1．2 Pioneering approaches

1．3 The chaos approach

1．4 The present focus

2 Efficient market hypothesis

2．1 Concepts， paradigms， and variables

2．2 Arbitrage

2．3 Efficient market hypothesis

2．4 Algorithmic complexity theory

2．5 Amount ofinformation in a financial time series

2．6 Idealized systems in physics and finance

3 Random walk

3．1 One-dimensional discrete case

3．2 The continuous limit

3．3 Central limit theorem

3．4 The speed of convergence

3．4．1 Berry-Esseen Theorem 1

3．4．2 Berry-Esseen Theorem 2

3．5 Basin of attraction

4 Levy stochastic processes and limit theorems

4．1 Stable distributions

4．2 Scaling and self-similarity

4．3 Limit theorem for stable distributions

4．4 Power-law distributions

4．4．1 The St Petersburg paradox

4．4．2 Power laws in finite systems

4．5 Price change statistics

4．6 Infinitely divisible random processes

4．6．1 Stable processes

4．6．2 Poisson process

4．6．3 Gamma distributed random variables

4．6．4 Uniformly distributed random variables

4．7 Summary

5 Scales in financial data

5．1 Price scales in financial markets

5．2 Time scales in financial markets

5．3 Summary

6 Stationarity and time correlation

6．1 Stationary stochastic processes

6．2 Correlation

6．3 Short-range correlated random processes

6．4 Long-range correlated random processes

6．5 Short-range compared with long-range correlated noise

7 Time correlation in financial time series

7．1 Autocorrelation function and spectral density

7．2 Higher-order correlations： The volatility

7．3 Stationarity of price changes

7．4 Summary

8 Stochastic models of price dynamics

8．1 Levy stable non-Gaussian model

8．2 Student's t-distribution

8．3 Mixture of Gaussian distributions

8．4 Truncated Levy fiight

9 Scaling and its breakdown

9．1 Empirical analysis of the S&P 500 index

9．2 Comparison with the TLF distribution

9．3 Statistical properties of rare events

10 ARCH and GARCH processes

10．1 ARCH processes

10．2 GARCH processes

10．3 Statistical properties of ARCH/GARCH processes

10．4 The GARCH（1，1） and empirical observatins

10．5 Summary

11 Financial markets and turbulence

11．1 Turbulence

11．2 Parallel analysis of price dynamics and fiuld velocity

11．3 Scaling in turbulence and in financial markets

11．4 Discussion

12 Correlation and anticorrelation between stocks

12．1 Simultaneous dynamics of pairs of stocks

12．1．1 Dow-Jones Industrial Average portfolio

12．1．2 S&P 500 portfolio

12．2 Statistical properties of correlation matrices

12．3 Discussion

13 Taxonomy of a stock portfolio

13．1 Distance between stocks

13．2 Ultrametric spaces

13．3 Subdominant ultrametric space of a portfolio of stocks

13．4 Summary

14 Options in idealized markets

14．1 Forward contracts

14．2 Futures

14．3 Options

14．4 Speculating and hedging

14．4．1 Speculation： An example

14．4．2 Hedging： A form ofinsurance

14．4．3 Hedging： The concept of a riskless portfolio

14．5 Option pricing in idealized markets

14．6 The Black & Scholes formula

14．7 The complex structure of financial markets

14．8 Another option-pricing approach

14．9 Discussion

15 Options in real markets

15．1 Discontinuous stock returns

15．2 Volatility in real markets

15．2．1 Historical volatility

15．2．2 Implied volatility

15．3 Hedging in real markets

15．4 Extension of the Black & Scholes model

15．5 Summary

Appendix A： Notation guide

Appendix B： Martingales

References

Index