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Financial, macro and micro econometrics using R /
Financial, Macro and Micro Econometrics Using R, Volume 42, provides state-of-the-art information on important topics in econometrics, including multivariate GARCH, stochastic frontiers, fractional responses, specification testing and model selection, exogeneity testing, causal analysis and forecast...
| Clasificación: | Libro Electrónico |
|---|---|
| Otros Autores: | , |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Amsterdam, Netherlands :
North-Holland is an imprint of Elsevier,
[2020]
|
| Colección: | Handbook of statistics (Amsterdam, Netherlands) ;
v. 42. |
| Temas: | |
| Acceso en línea: | Texto completo |
MARC
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| 050 | 4 | |a HB139 |b .F56 2020 | |
| 082 | 0 | 4 | |a 330.01/5195 |2 23 |
| 245 | 0 | 0 | |a Financial, macro and micro econometrics using R / |c edited by Hrishikesh D. Vinod, C.R. Rao. |
| 264 | 1 | |a Amsterdam, Netherlands : |b North-Holland is an imprint of Elsevier, |c [2020] | |
| 300 | |a 1 online resource | ||
| 336 | |a text |b txt |2 rdacontent | ||
| 337 | |a computer |b c |2 rdamedia | ||
| 338 | |a online resource |b cr |2 rdacarrier | ||
| 490 | 1 | |a Handbook of statistics ; |v volume 42 | |
| 500 | |a Includes index. | ||
| 588 | 0 | |a Online resource; title from digital title page (viewed on February 12, 2020). | |
| 504 | |a Includes bibliographical references and index. | ||
| 505 | 0 | |a Front Cover -- Financial, Macro and Micro Econometrics Using R -- Copyright -- Contents -- Contributors -- Preface -- Part I: Finance -- Chapter 1: Financial econometrics and big data: A survey of volatility estimators and tests for the presence of jumps and ... -- 1. Introduction -- 2. Setup -- 3. Realized measures of integrated volatility -- 3.1. Realized volatility -- 3.2. Realized bipower variation -- 3.3. Tripower variation -- 3.4. Two-scale realized volatility -- 3.5. Multiscale realized volatility -- 3.6. Realized kernel -- 3.7. Truncated realized volatility | |
| 505 | 8 | |a 3.8. Modulated bipower variation -- 3.9. Threshold bipower variation -- 3.10. Subsampled realized kernel -- 3.11. MedRV and MinRV -- 4. Jump testing -- 4.1. Barndorff-Nielsen and Shephard test -- 4.2. Lee and Mykland test -- 4.3. Jiang and Oomen test -- 4.4. A�it-Sahalia and Jacod test -- 4.5. Podolskij and Ziggel (PZ) test -- 4.6. Corradi, Silvapulle, and Swanson test -- 5. Co-jump testing -- 5.1. BLT co-jump testing -- 5.2. JT co-jump testing -- 5.3. MG threshold co-jump test -- 5.4. GST co-exceedance rule -- 5.5. CKR co-jump testing -- 6. Empirical experiments -- 6.1. Data description | |
| 505 | 8 | |a 6.2. Methodology -- 6.3. Findings -- 7. Conclusion -- Appendix. R code -- References -- Chapter 2: Real time monitoring of asset markets: Bubbles and crises**This chapter draws on several of our earlier works ... -- 1. Introduction -- 2. The PSY Procedure -- 2.1. The Augmented Dickey-Fuller test -- 2.2. The Recursive Evolving Algorithm -- 3. The PSY Test for Bubble Identification -- 3.1. The Rationale -- 3.2. Consistency -- 4. The PSY Test for Crisis Identification -- 4.1. The Rationale -- 4.2. Consistency -- 5. A New Composite Bootstrap -- 6. Empirical Applications with R | |
| 505 | 8 | |a 6.1. Example 1: The S & P 500 Market -- 6.2. Example 2: Credit Risk in the European Sovereign Sector -- 7. Conclusion -- References -- Further reading -- Chapter 3: Component-wise AdaBoost algorithms for high-dimensional binary classification and class probability predicti -- 1. Introduction -- 2. AdaBoost -- 3. Extensions to AdaBoost algorithms -- 3.1. Real AdaBoost -- 3.2. LogitBoost -- 3.3. Gentle AdaBoost -- 4. Alternative classification methods -- 4.1. Deep Neural Network -- 4.2. Logistic regression with LASSO -- 4.3. Semiparametric single-index model -- 5. Monte Carlo -- 6. Applications | |
| 505 | 8 | |a 7. Conclusions -- Acknowledgments -- References -- Part II: Macro Econometrics -- Chapter 4: Mixed data sampling (MIDAS) regression models -- 1. Introduction -- 2. A stylized MIDAS regression model -- 2.1. A few examples of the constraint function h -- 2.2. Selection of h, d, and k -- 2.3. Statistical inference -- 3. Linear and quasi-linear MIDAS models (affine g) -- 3.1. Unconstrained MIDAS -- 3.2. MIDAS -- 3.3. MIDAS with nonparametric smoothing of weights -- 4. Nonlinear parametric MIDAS models -- 4.1. General considerations -- 4.2. Logistic smooth transition MIDAS (LSTR-MIDAS) | |
| 520 | 2 | |a Financial, Macro and Micro Econometrics Using R, Volume 42, provides state-of-the-art information on important topics in econometrics, including multivariate GARCH, stochastic frontiers, fractional responses, specification testing and model selection, exogeneity testing, causal analysis and forecasting, GMM models, asset bubbles and crises, corporate investments, classification, forecasting, nonstandard problems, cointegration, financial market jumps and co-jumps, among other topics. | |
| 650 | 0 | |a Econometrics. | |
| 650 | 0 | |a R (Computer program language) | |
| 650 | 6 | |a �Econom�etrie. |0 (CaQQLa)201-0025541 | |
| 650 | 6 | |a R (Langage de programmation) |0 (CaQQLa)201-0368319 | |
| 650 | 7 | |a Econometrics |2 fast |0 (OCoLC)fst00901574 | |
| 650 | 7 | |a R (Computer program language) |2 fast |0 (OCoLC)fst01086207 | |
| 700 | 1 | |a Vinod, Hrishikesh D., |d 1939- |e editor. | |
| 700 | 1 | |a Rao, C. Radhakrishna |q (Calyampudi Radhakrishna), |d 1920-2023, |e editor. | |
| 776 | 0 | 8 | |i Print version: |z 0128202505 |z 9780128202500 |w (OCoLC)1108555395 |
| 830 | 0 | |a Handbook of statistics (Amsterdam, Netherlands) ; |v v. 42. | |
| 856 | 4 | 0 | |u https://sciencedirect.uam.elogim.com/science/handbooks/01697161/42 |z Texto completo |