Econometric Modelling of Stock Market Intraday ActivitySpringer Science & Business Media, 31. 8. 2001 - Počet stran: 177 Over the past 25 years, applied econometrics has undergone tremen dous changes, with active developments in fields of research such as time series, labor econometrics, financial econometrics and simulation based methods. Time series analysis has been an active field of research since the seminal work by Box and Jenkins (1976), who introduced a gen eral framework in which time series can be analyzed. In the world of financial econometrics and the application of time series techniques, the ARCH model of Engle (1982) has shifted the focus from the modelling of the process in itself to the modelling of the volatility of the process. In less than 15 years, it has become one of the most successful fields of 1 applied econometric research with hundreds of published papers. As an alternative to the ARCH modelling of the volatility, Taylor (1986) intro duced the stochastic volatility model, whose features are quite similar to the ARCH specification but which involves an unobserved or latent component for the volatility. While being more difficult to estimate than usual GARCH models, stochastic volatility models have found numerous applications in the modelling of volatility and more particularly in the econometric part of option pricing formulas. Although modelling volatil ity is one of the best known examples of applied financial econometrics, other topics (factor models, present value relationships, term structure 2 models) were also successfully tackled. |
Obsah
MARKET MICROSTRUCTURE TRADING MECHANISMS AND EXCHANGES | 1 |
2 Price Setting in financial markets | 2 |
23 Characteristics of trading mechanisms | 6 |
24 Market liquidity | 7 |
3 Exchanges | 11 |
32 The NASDAQ | 15 |
33 The Foreign Exchange market | 17 |
34 The Paris Bourse | 18 |
33 Estimation | 81 |
34 Diagnostics | 83 |
4 Illustration on NYSE data | 91 |
Probability distributions | 97 |
EMPIRICAL RESULTS AND EXTENSIONS | 107 |
2 Market microstructure effects | 108 |
22 Empirical application | 109 |
3 A joint model of durations and price change indicators | 111 |
4 Market microstructure | 21 |
42 Empirical research | 24 |
NYSE TAQ DATABASE AND FINANCIAL DURATIONS | 35 |
2 The TAQ database | 36 |
22 The quote database | 37 |
23 Best bidask quotes | 38 |
24 Direction of a trade | 40 |
27 Bidask bounce | 41 |
4 Durations | 44 |
41 Price durations | 45 |
42 Volume durations | 47 |
a descriptive analysis | 48 |
51 Trades and quotes | 49 |
52 Intraday seasonality | 50 |
53 Timeofday adjusted durations | 52 |
INTRADAY DURATION MODELS | 65 |
3 Econometric models | 69 |
31 ACD models | 70 |
32 Logarithmic ACD models | 76 |
31 The model | 113 |
32 Empirical application | 116 |
33 Forecasting and trading rules | 118 |
APPENDIX 4A | 122 |
INTRADAY VOLATILITY AND VALUEATRISK | 125 |
2 A review of arch models | 126 |
22 The ARCH model | 128 |
23 extensions | 130 |
3 ARCH models for intraday data | 132 |
31 Time transformations and intraday seasonality | 133 |
32 GARCH and EGARCH models | 141 |
33 Volume and number of trades | 144 |
4 Intraday Valueatrisk | 147 |
42 VaR models for intraday data | 149 |
43 Empirical application | 152 |
About the Authors | 173 |
175 | |
Další vydání - Zobrazit všechny
Econometric Modelling of Stock Market Intraday Activity Luc Bauwens,Pierre Giot Náhled není k dispozici. - 2013 |
Econometric Modelling of Stock Market Intraday Activity Luc Bauwens,Pierre Giot Náhled není k dispozici. - 2010 |
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Oblíbené pasáže
Strana 161 - Morana. C. (1999). Computing value at risk with high frequency data.
Odkazy na tuto knihu
Value at Risk-Quantifizierung unter Verwendung von Hochfrequenzdaten ... Mark Neukomm Omezený náhled - 2013 |