Analysis of latent information events on financial markets: an application of the discrete mixture ACD framework
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| Format: | Abschlussarbeit Buch |
| Sprache: | English |
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2006
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| Online-Zugang: | Inhaltsverzeichnis |
| Beschreibung: | IX, 271 S. Ill., graph. Darst. |
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| 245 | 1 | 0 | |a Analysis of latent information events on financial markets |b an application of the discrete mixture ACD framework |c vorgelegt von: Sandra Vuletić |
| 264 | 1 | |c 2006 | |
| 300 | |a IX, 271 S. |b Ill., graph. Darst. | ||
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Datensatz im Suchindex
| _version_ | 1804135781654069248 |
|---|---|
| adam_text | Table of Contents
List of Tables vii
List of Figures ix
Introduction 1
I Conceptual Part 9
1 Financial Trade Processes 11
1.1 Ancilla 11
1.2 The Trading Game 12
1.3 Institutional Details of the New York Stock Exchange 14
1.4 Recent Developments 16
1.4.1 Theoretical Paradigms 16
1.4.1.1 Inventory Models 17
1.4.1.2 Information Models 18
1.4.2 Methodological Cornerstones 21
1.5 The Genesis of a New Framework 22
II Econometric Part 27
2 Econometric Modelling of Financial Processes 29
2.1 Ancilla 29
2.2 Survival Analysis 31
2.2.1 The Censoring Problem 31
2.2.2 Functions of Primary Interest 32
2.2.3 Elementary Statistical Functions 34
2.2.4 Duration Distributions 37
2.2.4.1 The Common Assortment 37
2.2.4.2 Mixture Models 40
2.2.4.3 The Comprehensive Family 42
2.3 Time Series Analysis 50
2.3.1 Stochastic Processes 50
iii
2.3.2 Stationary Processes 51
2.3.3 Renewal Processes 53
2.3.4 Markov Processes and Martingales 54
2.4 Regime Switching Models in Econometrics 58
3 The Art of ACD Modelling 63
3.1 Ancilla 63
3.2 The General ACD Approach 64
3.2.1 Complex of Assumptions 64
3.2.2 Fundamental Implications 65
3.3 Customary Specifications 69
3.3.1 Conditional Duration Densities 70
3.3.2 Functional Forms of the Conditional Duration Mean 71
3.4 Importance of the Logarithmic ACD Model 75
3.5 The Innovative Discrete Mixture ACD Framework 82
3.5.1 The Static Mixture ACD Model 82
3.5.2 The Markov Switching ACD Model 87
3.5.3 The Interface 91
3.6 Estimation of Discrete Mixture ACD Models 93
4 Specification Tests 97
4.1 Ancilla 97
4.2 Density Evaluation 99
4.3 Nonparametric Specification Tests 100
4.4 Determination of the Number of Regimes 104
4.5 Testing Parameter Restrictions 106
III Empirical Part 109
5 Operationalization of the Discrete Mixture ACD Framework 111
5.1 Ancilla Ill
5.2 Structure of Information Based Trading 112
5.3 Important Considerations 116
5.4 Regulators 117
6 Empirical Analysis of Latent Information Events on Financial Markets 123
6.1 Ancilla 123
6.2 The Data Set 124
6.3 The Stylized Fact of Seasonality in Duration Data 125
6.3.1 Sources of Seasonality 125
6.3.2 Methodological Consideration 126
iv
6.3.3 Analysis of Seasonality 128
6.4 Statistical Description of Duration Data 138
6.5 Necessity of Preliminary Setups 141
6.6 Model Specifications 145
6.7 Results of Model Estimation 153
6.7.1 In sample Analysis 153
6.7.1.1 Ordinary ACD Models 153
6.7.1.2 Discrete Mixture ACD Models 159
6.7.2 Theoretical Interpretation 185
6.7.2.1 Central Positions 185
6.7.2.2 Tailor Made Trade Models 193
6.7.3 Forecast Accuracy 204
Conclusion and Outlook 209
Bibliography 213
A Mathematical Review 231
A.I Matrix Algebra 231
A.2 Mathematical Analysis 231
A3 Definitions and Theorems 235
B Appendix 237
B.I Duration Distributions 237
B.I.I Log Distributions 237
B.1.2 Laguerre Polynomial Distributions 238
B.1.3 Infinite Mixtures of Duration Distributions 239
B.I.3.1 Exponential Mixtures 239
B.l.3.2 Weibull Mixtures 240
B.1.4 The Comprehensive Family 240
B.l.4.1 Construction 240
B.l.4.2 The Limiting Case 241
B.2 The Markov Process 243
B.2.1 Multistep Transition Probabilities 243
B.2.2 Steady State Distribution 244
B.2.3 Classification of States 244
B.2.4 Expected Return Time 246
B.2.5 Expected Duration 247
B.3 ACD Modelling 248
B.3.1 Residual Duration Expectancy 248
v
B.3.2 Unconditional Duration Moments 249
B.3.2.1 The Case of a Linear Mean Function 249
B.3.2.2 The Case of a Log Linear Mean Function 251
B.3.3 Conditions for the Existence of the Moment Generating Function . 257
B.3.4 Autocovariance Function for a Log Linear Mean Function 257
B.3.5 Calculation of Regime Probabilities 262
B.3.6 Innovation Distribution in the MSACD Model 265
B.3.7 Stationarity in the MSACD Model 266
B.4 Seasonality in Duration Data 267
vi
List of Tables
2.1 Common statistics for distributions enclosed in the comprehensive family . 46
2.2 Shape properties of the generalized gamma hazard 48
2.3 Concretion of monotonic hazard functions 49
3.1 Autocorrelation rate for exponential and gamma LACD( , ) models .... 80
3.2 Autocorrelation rate for Weibull and g. gamma LACD(l, ) models .... 81
6.1 Number of observations 125
6.2 Weekday data description of intertrade durations 129
6.3 Tests for mean and variance equality 130
6.4 Estimation results of the polynomial trigonometric regression 136
6.5 Statistical description of duration data 139
6.6 The number of diurnal durations 141
6.7 Test for autocorrelation 142
6.8 The arithmetic mean of diurnal durations 144
6.9 The sample standard deviation of diurnal durations 145
6.10 Results of the equality tests for in sample data 146
6.11 Results of the equality tests for out sample data 147
6.12 Number of parameters for ordinary and discrete mixture ACD models . . 152
6.13 Estimation results and specification tests for ordinary ACD models for Boeingl56
6.14 Estimation results and specification tests for ordinary ACD models for
Coca Cola 157
6.15 Estimation results and specification tests for restrictive 2 regime SMACD
models for Boeing 161
6.16 Estimation results and specification tests for restrictive 2 regime SMACD
models for Coca Cola 162
6.17 Estimation results and specification tests for nonrestrictive 2 regime SMACD
models for Boeing 163
6.18 Estimation results and specification tests for nonrestrictive 2 regime SMACD
models for Coca Cola 164
6.19 Estimation results and specification tests for restrictive 3 regime SMACD
models for Boeing 168
vii
6.20 Estimation results and specification tests for restrictive 3 regime SMACD
models for Coca Cola 169
6.21 Estimation results and specification tests for nonrestrictive 3 regime SMA CD
models for Boeing 170
6.22 Estimation results and specification tests for nonrestrictive 3 regime SMA CD
models for Coca Cola 171
6.23 Comparison of multi regime SMACD models for Boeing 173
6.24 Comparison of multi regime SMACD models for Coca Cola 174
6.25 Estimation results and specification tests for restrictive 2 regime MSACD
models for Boeing 178
6.26 Estimation results and specification tests for restrictive 2 regime MSACD
models for Coca Cola 179
6.27 Estimation results and specification tests for nonrestrictive, simple 2
regime MSACD models for Boeing 180
6.28 Estimation results and specification tests for nonrestrictive, simple 2
regime MSACD models for Coca Cola 181
6.29 Comparison of 2 regime SMACD and MSACD models for Boeing .... 183
6.30 Comparison of 2 regime SMACD and MSACD models for Coca Cola . . 184
6.31 Parameter estimates for different Discrete Mixture ACD models for Boeing 189
6.32 Parameter estimates for different Discrete Mixture ACD models for Coca
Cola 190
6.33 Parameter tests for different Discrete Mixture ACD models for Boeing . . 191
6.34 Parameter tests for different Discrete Mixture ACD models for Coca Cola 192
6.35 The optimal econometric approach for Boeing 196
6.36 The optimal econometric approach for Coca Cola 197
6.36 The optimal econometric approach for Coca Cola (cont.) 198
6.37 Regime characteristics 201
6.38 Forecast results and specification tests for Discrete Mixture ACD models
for Boeing 206
6.39 Forecast results and specification tests for Discrete Mixture ACD models
for Coca Cola 207
A.I Integration and derivation rules 232
A.2 Special mathematical functions 233
A.3 Series 234
viii
List of Figures
2.1 Relations between different moment concepts 35
2.2 Obtaining other distributions by manipulating the exponential 38
2.3 Relation between different distributions classes 45
2.4 Region where first order moments exist 47
2.5 Irreducibility and periodicity of Markov chains 58
3.1 Dispersion index for the exponential LACD( , ) model 76
3.2 Typical autocorrelation patterns in LACD( , ) models 78
3.3 Rate of autocorrelation in LACD(1,1) models 79
3.4 The interface between the SMACD and MSACD model 92
5.1 Structure of the trading process 113
5.2 Components of continuous mixture distributions 119
6.1 Cross validation function (CV) for Boeing 133
6.2 Cross validation function (CV) for Coca Cola 134
6.3 Estimated intraday seasonality pattern 135
6.4 Estimated seasonality pattern and interval means 137
6.5 Autocorrelation function for durations 140
6.6 Scatter plots of durations 143
6.7 Specifications of the Discrete Mixture ACD framework 150
6.8 The distributional deficiency in the ordinary ACD model 158
6.9 The distributional adaption in the two regime SMACD model 166
6.10 The distributional adaption in the three regime SMACD model 176
6.11 Visualization of the regime specific trading velocities 199
6.12 Log ratios of the smoothed regime probabilities 202
ix
|
| adam_txt |
Table of Contents
List of Tables vii
List of Figures ix
Introduction 1
I Conceptual Part 9
1 Financial Trade Processes 11
1.1 Ancilla 11
1.2 The Trading Game 12
1.3 Institutional Details of the New York Stock Exchange 14
1.4 Recent Developments 16
1.4.1 Theoretical Paradigms 16
1.4.1.1 Inventory Models 17
1.4.1.2 Information Models 18
1.4.2 Methodological Cornerstones 21
1.5 The Genesis of a New Framework 22
II Econometric Part 27
2 Econometric Modelling of Financial Processes 29
2.1 Ancilla 29
2.2 Survival Analysis 31
2.2.1 The Censoring Problem 31
2.2.2 Functions of Primary Interest 32
2.2.3 Elementary Statistical Functions 34
2.2.4 Duration Distributions 37
2.2.4.1 The Common Assortment 37
2.2.4.2 Mixture Models 40
2.2.4.3 The Comprehensive Family 42
2.3 Time Series Analysis 50
2.3.1 Stochastic Processes 50
iii
2.3.2 Stationary Processes 51
2.3.3 Renewal Processes 53
2.3.4 Markov Processes and Martingales 54
2.4 Regime Switching Models in Econometrics 58
3 The Art of ACD Modelling 63
3.1 Ancilla 63
3.2 The General ACD Approach 64
3.2.1 Complex of Assumptions 64
3.2.2 Fundamental Implications 65
3.3 Customary Specifications 69
3.3.1 Conditional Duration Densities 70
3.3.2 Functional Forms of the Conditional Duration Mean 71
3.4 Importance of the Logarithmic ACD Model 75
3.5 The Innovative Discrete Mixture ACD Framework 82
3.5.1 The Static Mixture ACD Model 82
3.5.2 The Markov Switching ACD Model 87
3.5.3 The Interface 91
3.6 Estimation of Discrete Mixture ACD Models 93
4 Specification Tests 97
4.1 Ancilla 97
4.2 Density Evaluation 99
4.3 Nonparametric Specification Tests 100
4.4 Determination of the Number of Regimes 104
4.5 Testing Parameter Restrictions 106
III Empirical Part 109
5 Operationalization of the Discrete Mixture ACD Framework 111
5.1 Ancilla Ill
5.2 Structure of Information Based Trading 112
5.3 Important Considerations 116
5.4 Regulators 117
6 Empirical Analysis of Latent Information Events on Financial Markets 123
6.1 Ancilla 123
6.2 The Data Set 124
6.3 The Stylized Fact of Seasonality in Duration Data 125
6.3.1 Sources of Seasonality 125
6.3.2 Methodological Consideration 126
iv
6.3.3 Analysis of Seasonality 128
6.4 Statistical Description of Duration Data 138
6.5 Necessity of Preliminary Setups 141
6.6 Model Specifications 145
6.7 Results of Model Estimation 153
6.7.1 In sample Analysis 153
6.7.1.1 Ordinary ACD Models 153
6.7.1.2 Discrete Mixture ACD Models 159
6.7.2 Theoretical Interpretation 185
6.7.2.1 Central Positions 185
6.7.2.2 Tailor Made Trade Models 193
6.7.3 Forecast Accuracy 204
Conclusion and Outlook 209
Bibliography 213
A Mathematical Review 231
A.I Matrix Algebra 231
A.2 Mathematical Analysis 231
A3 Definitions and Theorems 235
B Appendix 237
B.I Duration Distributions 237
B.I.I Log Distributions 237
B.1.2 Laguerre Polynomial Distributions 238
B.1.3 Infinite Mixtures of Duration Distributions 239
B.I.3.1 Exponential Mixtures 239
B.l.3.2 Weibull Mixtures 240
B.1.4 The Comprehensive Family 240
B.l.4.1 Construction 240
B.l.4.2 The Limiting Case 241
B.2 The Markov Process 243
B.2.1 Multistep Transition Probabilities 243
B.2.2 Steady State Distribution 244
B.2.3 Classification of States 244
B.2.4 Expected Return Time 246
B.2.5 Expected Duration 247
B.3 ACD Modelling 248
B.3.1 Residual Duration Expectancy 248
v
B.3.2 Unconditional Duration Moments 249
B.3.2.1 The Case of a Linear Mean Function 249
B.3.2.2 The Case of a Log Linear Mean Function 251
B.3.3 Conditions for the Existence of the Moment Generating Function . 257
B.3.4 Autocovariance Function for a Log Linear Mean Function 257
B.3.5 Calculation of Regime Probabilities 262
B.3.6 Innovation Distribution in the MSACD Model 265
B.3.7 Stationarity in the MSACD Model 266
B.4 Seasonality in Duration Data 267
vi
List of Tables
2.1 Common statistics for distributions enclosed in the comprehensive family . 46
2.2 Shape properties of the generalized gamma hazard 48
2.3 Concretion of monotonic hazard functions 49
3.1 Autocorrelation rate for exponential and gamma LACD(\,\) models . 80
3.2 Autocorrelation rate for Weibull and g. gamma LACD(l,\) models . 81
6.1 Number of observations 125
6.2 Weekday data description of intertrade durations 129
6.3 Tests for mean and variance equality 130
6.4 Estimation results of the polynomial trigonometric regression 136
6.5 Statistical description of duration data 139
6.6 The number of diurnal durations 141
6.7 Test for autocorrelation 142
6.8 The arithmetic mean of diurnal durations 144
6.9 The sample standard deviation of diurnal durations 145
6.10 Results of the equality tests for in sample data 146
6.11 Results of the equality tests for out sample data 147
6.12 Number of parameters for ordinary and discrete mixture ACD models . . 152
6.13 Estimation results and specification tests for ordinary ACD models for Boeingl56
6.14 Estimation results and specification tests for ordinary ACD models for
Coca Cola 157
6.15 Estimation results and specification tests for restrictive 2 regime SMACD
models for Boeing 161
6.16 Estimation results and specification tests for restrictive 2 regime SMACD
models for Coca Cola 162
6.17 Estimation results and specification tests for nonrestrictive 2 regime SMACD
models for Boeing 163
6.18 Estimation results and specification tests for nonrestrictive 2 regime SMACD
models for Coca Cola 164
6.19 Estimation results and specification tests for restrictive 3 regime SMACD
models for Boeing 168
vii
6.20 Estimation results and specification tests for restrictive 3 regime SMACD
models for Coca Cola 169
6.21 Estimation results and specification tests for nonrestrictive 3 regime SMA CD
models for Boeing 170
6.22 Estimation results and specification tests for nonrestrictive 3 regime SMA CD
models for Coca Cola 171
6.23 Comparison of multi regime SMACD models for Boeing 173
6.24 Comparison of multi regime SMACD models for Coca Cola 174
6.25 Estimation results and specification tests for restrictive 2 regime MSACD
models for Boeing 178
6.26 Estimation results and specification tests for restrictive 2 regime MSACD
models for Coca Cola 179
6.27 Estimation results and specification tests for nonrestrictive, simple 2
regime MSACD models for Boeing 180
6.28 Estimation results and specification tests for nonrestrictive, simple 2
regime MSACD models for Coca Cola 181
6.29 Comparison of 2 regime SMACD and MSACD models for Boeing . 183
6.30 Comparison of 2 regime SMACD and MSACD models for Coca Cola . . 184
6.31 Parameter estimates for different Discrete Mixture ACD models for Boeing 189
6.32 Parameter estimates for different Discrete Mixture ACD models for Coca
Cola 190
6.33 Parameter tests for different Discrete Mixture ACD models for Boeing . . 191
6.34 Parameter tests for different Discrete Mixture ACD models for Coca Cola 192
6.35 The optimal econometric approach for Boeing 196
6.36 The optimal econometric approach for Coca Cola 197
6.36 The optimal econometric approach for Coca Cola (cont.) 198
6.37 Regime characteristics 201
6.38 Forecast results and specification tests for Discrete Mixture ACD models
for Boeing 206
6.39 Forecast results and specification tests for Discrete Mixture ACD models
for Coca Cola 207
A.I Integration and derivation rules 232
A.2 Special mathematical functions 233
A.3 Series 234
viii
List of Figures
2.1 Relations between different moment concepts 35
2.2 Obtaining other distributions by manipulating the exponential 38
2.3 Relation between different distributions classes 45
2.4 Region where first order moments exist 47
2.5 Irreducibility and periodicity of Markov chains 58
3.1 Dispersion index for the exponential LACD(\,\) model 76
3.2 Typical autocorrelation patterns in LACD(\,\) models 78
3.3 Rate of autocorrelation in LACD(1,1) models 79
3.4 The interface between the SMACD and MSACD model 92
5.1 Structure of the trading process 113
5.2 Components of continuous mixture distributions 119
6.1 Cross validation function (CV) for Boeing 133
6.2 Cross validation function (CV) for Coca Cola 134
6.3 Estimated intraday seasonality pattern 135
6.4 Estimated seasonality pattern and interval means 137
6.5 Autocorrelation function for durations 140
6.6 Scatter plots of durations 143
6.7 Specifications of the Discrete Mixture ACD framework 150
6.8 The distributional deficiency in the ordinary ACD model 158
6.9 The distributional adaption in the two regime SMACD model 166
6.10 The distributional adaption in the three regime SMACD model 176
6.11 Visualization of the regime specific trading velocities 199
6.12 Log ratios of the smoothed regime probabilities 202
ix |
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| author | Vuletić, Sandra 1974- |
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| dewey-ones | 332 - Financial economics |
| dewey-raw | 332.0151 |
| dewey-search | 332.0151 |
| dewey-sort | 3332.0151 |
| dewey-tens | 330 - Economics |
| discipline | Wirtschaftswissenschaften |
| discipline_str_mv | Wirtschaftswissenschaften |
| format | Thesis Book |
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| publishDateSort | 2006 |
| record_format | marc |
| spelling | Vuletić, Sandra 1974- Verfasser (DE-588)132035413 aut Analysis of latent information events on financial markets an application of the discrete mixture ACD framework vorgelegt von: Sandra Vuletić 2006 IX, 271 S. Ill., graph. Darst. txt rdacontent n rdamedia nc rdacarrier Frankfurt (Main), Univ., Diss., 2006 Autoregressives Modell (DE-588)4143717-2 gnd rswk-swf Kreditmarkt (DE-588)4073788-3 gnd rswk-swf (DE-588)4113937-9 Hochschulschrift gnd-content Kreditmarkt (DE-588)4073788-3 s Autoregressives Modell (DE-588)4143717-2 s DE-188 HBZ Datenaustausch application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=015057188&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Vuletić, Sandra 1974- Analysis of latent information events on financial markets an application of the discrete mixture ACD framework Autoregressives Modell (DE-588)4143717-2 gnd Kreditmarkt (DE-588)4073788-3 gnd |
| subject_GND | (DE-588)4143717-2 (DE-588)4073788-3 (DE-588)4113937-9 |
| title | Analysis of latent information events on financial markets an application of the discrete mixture ACD framework |
| title_auth | Analysis of latent information events on financial markets an application of the discrete mixture ACD framework |
| title_exact_search | Analysis of latent information events on financial markets an application of the discrete mixture ACD framework |
| title_exact_search_txtP | Analysis of latent information events on financial markets an application of the discrete mixture ACD framework |
| title_full | Analysis of latent information events on financial markets an application of the discrete mixture ACD framework vorgelegt von: Sandra Vuletić |
| title_fullStr | Analysis of latent information events on financial markets an application of the discrete mixture ACD framework vorgelegt von: Sandra Vuletić |
| title_full_unstemmed | Analysis of latent information events on financial markets an application of the discrete mixture ACD framework vorgelegt von: Sandra Vuletić |
| title_short | Analysis of latent information events on financial markets |
| title_sort | analysis of latent information events on financial markets an application of the discrete mixture acd framework |
| title_sub | an application of the discrete mixture ACD framework |
| topic | Autoregressives Modell (DE-588)4143717-2 gnd Kreditmarkt (DE-588)4073788-3 gnd |
| topic_facet | Autoregressives Modell Kreditmarkt Hochschulschrift |
| url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=015057188&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
| work_keys_str_mv | AT vuleticsandra analysisoflatentinformationeventsonfinancialmarketsanapplicationofthediscretemixtureacdframework |