【书名】 Analysis of Financial Time Series
【作者】 RUEY S. TSAY
【出版社】A Wiley-Interscience Publication
【版本】英文
【出版日期】2002
【文件格式】PDF
【文件大小】4.21mb
【页数】448页
【ISBN出版号】
【资料类别】计量经济学
【市面定价】
【扫描版还是影印版】清晰扫描版
【是否缺页】完整
【关键词】Time Series；Financial；Financial Econometrics
【内容简介】
【目录】
Preface xi
1. Financial Time Series and Their Characteristics 1
1.1 Asset Returns, 2
1.2 Distributional Properties of Returns, 6
1.3 Processes Considered, 17
2. Linear Time Series Analysis and Its Applications 22
2.1 Stationarity, 23
2.2 Correlation and Autocorrelation Function, 23
2.3 White Noise and Linear Time Series, 26
2.4 Simple Autoregressive Models, 28
2.5 Simple Moving-Average Models, 42
2.6 Simple ARMA Models, 48
2.7 Unit-Root Nonstationarity, 56
2.8 Seasonal Models, 61
2.9 Regression Models with Time Series Errors, 66
2.10 Long-Memory Models, 72
Appendix A. Some SCA Commands, 74
3. Conditional Heteroscedastic Models 79
3.1 Characteristics of Volatility, 80
3.2 Structure of a Model, 81
3.3 The ARCH Model, 82
3.4 The GARCH Model, 93
3.5 The Integrated GARCH Model, 100
3.6 The GARCH-M Model, 101
3.7 The Exponential GARCH Model, 102
3.8 The CHARMA Model, 107
3.9 Random Coefficient Autoregressive Models, 109
3.10 The Stochastic Volatility Model, 110
3.11 The Long-Memory Stochastic Volatility Model, 110
3.12 An Alternative Approach, 112
3.13 Application, 114
3.14 Kurtosis of GARCH Models, 118
Appendix A. Some RATS Programs for Estimating Volatility
Models, 120
4. Nonlinear Models and Their Applications 126
4.1 Nonlinear Models, 128
4.2 Nonlinearity Tests, 152
4.3 Modeling, 161
4.4 Forecasting, 161
4.5 Application, 164
Appendix A. Some RATS Programs for Nonlinear Volatility
Models, 168
Appendix B. S-Plus Commands for Neural Network, 169
5. High-Frequency Data Analysis and Market Microstructure 175
5.1 Nonsynchronous Trading, 176
5.2 Bid-Ask Spread, 179
5.3 Empirical Characteristics of Transactions Data, 181
5.4 Models for Price Changes, 187
5.5 Duration Models, 194
5.6 Nonlinear Duration Models, 206
5.7 Bivariate Models for Price Change and Duration, 207
Appendix A. Review of Some Probability Distributions, 212
Appendix B. Hazard Function, 215
Appendix C. Some RATS Programs for Duration Models, 216
6. Continuous-Time Models and Their Applications 221
6.1 Options, 222
6.2 Some Continuous-Time Stochastic Processes, 222
6.3 Ito’s Lemma, 226
6.6 Black–Scholes Pricing Formulas, 234
6.7 An Extension of Ito’s Lemma, 240
6.8 Stochastic Integral, 242
6.9 Jump Diffusion Models, 244
6.10 Estimation of Continuous-Time Models, 251
Appendix A. Integration of Black–Scholes Formula, 251
Appendix B. Approximation to Standard Normal Probability, 253
7. Extreme Values, Quantile Estimation, and Value at Risk 256
7.1 Value at Risk, 256
7.2 RiskMetrics, 259
7.3 An Econometric Approach to VaR Calculation, 262
7.4 Quantile Estimation, 267
7.5 Extreme Value Theory, 270
7.6 An Extreme Value Approach to VaR, 279
7.7 A New Approach Based on the Extreme Value Theory, 284
8. Multivariate Time Series Analysis and Its Applications 299
8.1 Weak Stationarity and Cross-Correlation Matrixes, 300
8.2 Vector Autoregressive Models, 309
8.3 Vector Moving-Average Models, 318
8.4 Vector ARMA Models, 322
8.5 Unit-Root Nonstationarity and Co-Integration, 328
8.6 Threshold Co-Integration and Arbitrage, 332
8.7 Principal Component Analysis, 335
8.8 Factor Analysis, 341
Appendix A. Review of Vectors and Matrixes, 348
Appendix B. Multivariate Normal Distributions, 353
9. Multivariate Volatility Models and Their Applications 357
9.1 Reparameterization, 358
9.2 GARCH Models for Bivariate Returns, 363
9.3 Higher Dimensional Volatility Models, 376
9.4 Factor-Volatility Models, 383
9.5 Application, 385
9.6 Multivariate t Distribution, 387
Appendix A. Some Remarks on Estimation, 388
10. Markov Chain Monte Carlo Methods with Applications 395
10.1 Markov Chain Simulation, 396
10.2 Gibbs Sampling, 397
10.3 Bayesian Inference, 399
10.4 Alternative Algorithms, 403
10.5 Linear Regression with Time-Series Errors, 406
10.6 Missing Values and Outliers, 410
10.7 Stochastic Volatility Models, 418
10.8 Markov Switching Models, 429
10.9 Forecasting, 438
10.10 Other Applications, 441
Index 445
【原创书评】
在此我不太想说书中的内容，毕竟中文版已经出版，且目录列的很详细了！只是强调一点，这本书无论在使用性和可阅读性上都是很好的！（中英版本我都已经看过了，非常不错）
说点题外话，就本帖，我想说两个观点：一、在金融研究领域计量经济学非常重要，而重中之重就是时间序列。原因很简单，因为在金融市场中存在着大量的连续、平滑的数据，在股票市场这种数据可以精确到秒。那么关于这个学科的研究，就需要我们掌握如何处理这些数据的技能；二、英语阅读技能很重要。我看到前面有很多朋友跟帖说“有中文的没有？”，“中文的已经出版了”等等，我想告诉这些朋友，翻译的毕竟不是原来的，有些部分肯定会有偏差的。另外，我国的经济领域研究还没有达到世界领先水平，这需要我们首先会学的是借鉴，借鉴国外优秀的研究成果。而那些成果应该都是英文写成的吧！！所以希望大家重视英文阅读能力。就这些，谢谢！
[此贴子已经被作者于2008-1-3 23:02:29编辑过]
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