Handbook of financial econometrics: 2 Applications
Gespeichert in:
| Format: | Buch |
|---|---|
| Sprache: | English |
| Veröffentlicht: |
Amsterdam [u.a.]
Elsevier [u.a.]
2010
|
| Schriftenreihe: | Handbooks in finance
Handbooks in finance |
| Schlagworte: | |
| Online-Zugang: | Inhaltsverzeichnis |
| Beschreibung: | Literaturangaben |
| Beschreibung: | XXVII, 356 S. graph. Darst. |
| ISBN: | 9780444535481 |
Internformat
MARC
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| 264 | 1 | |a Amsterdam [u.a.] |b Elsevier [u.a.] |c 2010 | |
| 300 | |a XXVII, 356 S. |b graph. Darst. | ||
| 336 | |b txt |2 rdacontent | ||
| 337 | |b n |2 rdamedia | ||
| 338 | |b nc |2 rdacarrier | ||
| 490 | 0 | |a Handbooks in finance | |
| 490 | 0 | |a Handbooks in finance | |
| 500 | |a Literaturangaben | ||
| 650 | 7 | |a Modell-Spezifikation |2 stw | |
| 650 | 7 | |a Optionspreistheorie |2 stw | |
| 650 | 7 | |a Schätztheorie |2 stw | |
| 650 | 7 | |a Stochastischer Prozess |2 stw | |
| 650 | 4 | |a Ökonometrisches Modell | |
| 650 | 4 | |a Econometrics | |
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| 999 | |a oai:aleph.bib-bvb.de:BVB01-018723793 | ||
Datensatz im Suchindex
| _version_ | 1804140848080748544 |
|---|---|
| adam_text | List of Contributors
Volume
2:
Applications
13
MCMC Methods for Continuous-Time Financial Econometrics
1
Michael Johannes and Nicholas Poison
1.
Introduction
2
2.
Overview of Bayesian Inference and MCMC
5
2.1.
MCMC Simulation and Estimation
5
2.2.
Bayesian Inference
6
2.2.1.
The Posterior Distribution
7
2.2.2.
The Likelihood
7
2.2.3.
The Prior Distribution
7
2.2.4.
Marginal Parameter Posterior
8
2.2.5.
State Estimation
8
2.2.6.
Model Specification
8
3.
MCMC: Methods and Theory
9
3.1.
Gifford-HammersleyTheorem
9
3.2.
Gibbs Sampling
10
3.2.1.
TheGriddy Gibbs Sampler
11
3.3.
Metropolis-Hastings
12
3.3.1.
independence Metropolis-Hastings
13
3.3.2.
Random-Walk Metropolis
14
3.4.
Convergence Theory
14
3.4.1.
Convergence of Markov Chains
15
3.4.2.
Convergence of MCMC Algorithms
15
3.5.
MCMC Algorithms: Issues and Practical Recommendations
20
3.5.1.
Building MCMC Algorithms
20
3.5.2.
Blocking
20
3.5.3.
Simulation Studies
20
3.5.4.
Provable Convergence
21
3.5.5.
Choosing Proposal Densities and Tuning Metropolis Algorithms
21
3.5.6.
Noninformative
Priors
23
VII
viii Contents
3.5.7.
Convergence Diagnostics and
Starting
Values
23
3.5.8.
Rao-Blackwellization
23
4.
Bayesian
Inference and Asset Pricing Models
24
4.1.
States Variables
and Prices
24
4.2.
Time-Discretization: Computing p(Y X,
Θ)
and
ρ(Χ Θ)
27
4.3.
Parameter Distribution
30
5.
Asset Pricing Applications
31
5.1.
Equity Asset Pricing Models
32
5.1.1.
Geometric Brownian Motion
32
5.1.2.
Black-Scholes
33
5.1.3.
A Multivariate Version of Merton s Model
36
5.1.4.
Time-Varying Equity Premium
40
5.1.5.
Log-Stochastic Volatility Models
45
5.1.6.
Alternative Stochastic Volatility Models
50
5.2.
Term Structure Models
54
5.2.1.
Vasicek s Model
54
5.2.2.
Vasicek with Jumps
57
5.2.3.
The
CIR
Model
61
5.3.
Regime Switching Models
63
6.
Conclusions and Future Directions
65
Acknowledgments
66
References
66
14
The Analysis of the Cross-Section of Security Returns
73
Ravi Jagannathan, Georgios Skoulakis, and Zhenyu Wang
1.
Introduction
74
2.
Linear Beta Pricing Models, Factors, and Characteristics
77
2.1.
Linear Beta Pricing Models
77
2.2.
Factor Selection
78
3.
Cross-Sectional Regression Methods
80
3.1.
Description of the CSR Method
80
3.2.
Consistency and Asymptotic Normality of the CSR Estimator
83
3.3.
Fama-MacBeth Variance Estimator
85
3.4.
Conditionally Homoskedastic Residuals Given the Factors
87
3.5.
Using Security Characteristics to Test Factor Pricing Models
90
3.5.1.
Consistency and Asymptotic Normality of the CSR Estimator
92
3.5.2.
Misspecification Bias and Protection Against Spurious Factors
93
3.6.
Time-Varying Security Characteristics
94
3.6.1.
No Pricing Restrictions Imposed on Traded Factors
94
3.6.2.
Traded Factors with Imposed Pricing Restrictions
97
3.6.3.
Using Time-Average Characteristics to Avoid the Bias
99
3.7.
N-Consistencyofthe CSR Estimator
101
Contents
4. Maximum
Likelihood Methods
108
4.1.
Nontraded Factors
108
4.2.
Some Factors Are Traded
1
ю
4.3.
Single Risk-Free Lending and Borrowing Rates with Portfolio
Returns as Factors
110
5.
The Generalized Method of Moments
1
11
5.1.
An Overview of the GMM
112
5.2.
Evaluating Beta Pricing Models Using the Beta Representation
114
5.3.
Evaluating Beta Pricing Models Using the Stochastic Discount
Factor Representation
■ 117
5.4.
Models with Time-Varying Betas and Risk
Premia
122
6.
Conclusion
128
Acknowledgments
129
References
130
15
Option Pricing Bounds and Statistical Uncertainty: Using Econometrics
to Find an Exit Strategy in Derivatives Trading
135
Per A. Mykland
1.
Introduction
136
1.1.
Pricing Bounds, Trading Strategies, and Exit Strategies
136
1.2.
Related Problems and Related Literature
140
2.
Options Hedging from Prediction Sets: Basic Description
142
2.1.
Setup and Super-Self-Financing Strategies
142
2.2.
The Bounds and A and
В
144
2.3.
The Practical
Rôle
of Prediction Set Trading: Reserves and Exit Strategies
145
3.
Options Hedging from Prediction Sets: The Original Cases
147
3.1.
Pointwise Bounds
147
3.2.
Integral Bounds
148
3.3.
Comparison of Approaches
150
3.4.
Trading with Integral Bounds and the Estimation of Consumed Volatility
151
3.5.
An Implementation with Data
152
4.
Properties of Trading Strategies
153
4.1.
Super-Self-Financing and
Supermartingale
153
4.2.
Defining Self-Financing Strategies
156
4.3.
Proofs for Section
4.1 157
4.3.1.
ProofofTheorem
1 157
4.3.2.
Proof of Corollary
1 158
4.3.3.
Proof of Proposition
1 158
5.
Prediction Sets: General Theory
159
5.1.
The Prediction Set Theorem
159
5.2.
Prediction Sets: A Problem of Definition
161
5.3.
Prediction Regions from Historical Data: A Decoupled Procedure
163
Contents
5.4.
Proofs for Section
5 165
5.4.1.
Proof of Theorem
2 165
5.4.2.
Proof of Propositions
168
5.4.3.
Proof of Proposition
4 168
6.
Prediction Sets: The Effect of Interest Rates and General Formulae for
European Options
168
6.1.
Interest Rates: Market Structure and Types of Prediction Sets
168
6.2.
The Effect of Interest Rates: The Case of the Ornstein-Uhlenbeck Model
170
6.3.
General European Options
171
6.4.
General European Options: The Case of Two Intervals and a Zero-Coupon Bond
172
6.5.
Proofs for Section
6 174
6.5.1.
Proof of Theorem
4 174
6.5.2.
Proof of Theorem
5 175
7.
Prediction Sets and the Interpolation of Options
175
7.1.
Motivation
175
7.2.
Interpolating European Payoffs
176
7.3.
The Case of European Calls
177
7.4.
The Usefulness of Interpolation
182
7.5.
Proofs for Section
7 182
7.5.1.
Proof of Theorem
6 182
7.5.2.
Proof of Theorem
7
(and Algorithm)
182
7.5.3.
Proof of Corollary
186
8.
Bounds that are not Based on Prediction Sets
186
Acknowledgments
188
References
188
16
Inference for Stochastic Processes
197
Jean Jacod
1.
Introduction
198
2.
About Diffusion Processes
199
2.1.
The Basic Setting
200
2.2.
The Markov Property and the Infinitesimal Generator
202
2.3.
Examples
-
Diffusions on a Domain
202
2.4.
Likelihood Ratio
204
3.
Parametric Estimation: Asymptotic Optimality Criteria
■ 206
3.1.
The Local Asymptotic Normality Property
208
3.2.
Local Asymptotic Mixed Normality and Local Asymptotic
Quadraticity
209
4.
Diffusions and Statistics
210
4.1.
Observation Over a Whole Interval
211
4.2.
Discrete Observations
214
4.3.
Observations with Errors
215
Contents
x¡
5.
Discrete
Observations
with Decreasing
Stepsize 216
5.1.
Observations on a Fixed Interval
216
5.2.
Observations on an Increasing Interval
219
6.
Discrete Observations with Constant Stepsize
223
6.1.
Approximating the Likelihood
224
6.2.
Contrast Functions and Estimating Functions
225
7.
Observations with Errors
228
7.1.
Additive Errors
228
7.1.1.
Neglecting the Errors
229
7.1.2.
Taking Care of the Errors
230
7.2.
Round-Off Errors
233
7.2.1.
Neglecting the Errors
233
7.2.2.
Taking Care of the Errors
234
8.
Concluding Remarks
236
References
237
17
Stock Market Trading Volume
241
Andrew W.
Lo
and Jiang Wang
1.
Introduction
242
2.
Measuring Trading Activity
244
2.1.
Notation
245
2.2.
Motivation
246
2.3.
Defining
Individualand
Portfolio Turnover
248
2.4.
Time Aggregation
250
2.5.
The Data
250
3.
Time-Series Properties
251
3.1.
Seasonalities
255
3.2.
Secular Trends and Detrending
258
4.
Cross-Sectional Properties
267
4.1.
Specification of Cross-Sectional Regressions
272
4.2.
Summary Statistics for Regressors
275
4.3.
Regression Results
280
5.
Volume Implications of Portfolio Theory
284
5.1.
Two-Fund Separation
286
5.2.
(K
+
1)-Fund Separation
288
5.3.
Empirical Tests of (K
+ 1
)-Fund Separation
290
6.
Volume Implications of
Intertemporal
Asset Pricing Models
294
6.1.
AnICAPM
295
6.1.1.
The Economy
295
6.1.2.
Equilibrium
296
6.2.
The Behavior of Returns and Volume
298
6.2.1.
The Cross-Section of Volume
299
xii Contents
6.2.2.
Time-Series Implications for the Hedging Portfolio
300
6.2.3.
Cross-Sectional Implications for the Hedging Portfolio
300
6.3.
Empirical Construction of the Hedging Portfolio
302
6.4.
The Forecast Power of the Hedging Portfolio
313
6.4.1.
Hedging-Portfolio Returns
313
6.4.2.
Optimal Forecasting Portfolios
314
6.4.3.
Hedging-Portfolio Return
asa
Predictor of Market Returns
317
6.5.
The Hedging-Portfolio Return as a Risk Factor
320
6.6.
Updated Empirical Results
327
7.
Conclusion
335
Acknowledgments
337
References
337
Index
343
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| id | DE-604.BV035866043 |
| illustrated | Illustrated |
| indexdate | 2024-07-09T22:06:29Z |
| institution | BVB |
| isbn | 9780444535481 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-018723793 |
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| physical | XXVII, 356 S. graph. Darst. |
| publishDate | 2010 |
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| publisher | Elsevier [u.a.] |
| record_format | marc |
| series2 | Handbooks in finance |
| spelling | Handbook of financial econometrics 2 Applications ed. by Yacine Aït-Sahalia ... Amsterdam [u.a.] Elsevier [u.a.] 2010 XXVII, 356 S. graph. Darst. txt rdacontent n rdamedia nc rdacarrier Handbooks in finance Literaturangaben Modell-Spezifikation stw Optionspreistheorie stw Schätztheorie stw Stochastischer Prozess stw Ökonometrisches Modell Econometrics Finance Econometric models Aït-Sahalia, Yacine Sonstige (DE-588)128764465 oth (DE-604)BV035827032 2 Digitalisierung UB Bayreuth application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=018723793&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Handbook of financial econometrics Modell-Spezifikation stw Optionspreistheorie stw Schätztheorie stw Stochastischer Prozess stw Ökonometrisches Modell Econometrics Finance Econometric models |
| title | Handbook of financial econometrics |
| title_auth | Handbook of financial econometrics |
| title_exact_search | Handbook of financial econometrics |
| title_full | Handbook of financial econometrics 2 Applications ed. by Yacine Aït-Sahalia ... |
| title_fullStr | Handbook of financial econometrics 2 Applications ed. by Yacine Aït-Sahalia ... |
| title_full_unstemmed | Handbook of financial econometrics 2 Applications ed. by Yacine Aït-Sahalia ... |
| title_short | Handbook of financial econometrics |
| title_sort | handbook of financial econometrics applications |
| topic | Modell-Spezifikation stw Optionspreistheorie stw Schätztheorie stw Stochastischer Prozess stw Ökonometrisches Modell Econometrics Finance Econometric models |
| topic_facet | Modell-Spezifikation Optionspreistheorie Schätztheorie Stochastischer Prozess Ökonometrisches Modell Econometrics Finance Econometric models |
| url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=018723793&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
| volume_link | (DE-604)BV035827032 |
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