Essays on statistical arbitrage:
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| Main Author: | |
|---|---|
| Format: | Thesis Book |
| Language: | German |
| Published: |
[Erlangen]
2016
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| Subjects: | |
| Online Access: | Inhaltsverzeichnis |
| Physical Description: | xi, 250 Seiten Diagramme |
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Record in the Search Index
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| adam_text | Titel: Essays on statistical arbitrage
Autor: Krauß, Christopher
Jahr: 2016
Contents
Abstract iv
Abstract (deutsche Fassung) v
Acknowledgements vi
1 Introduction 1
2 Statistical Arbitrage Pairs Trading Strategies: Review and Outlook 9
2.1 Introduction...................................11
2.2 Distance approach...............................14
2.2.1 The baseline approach - Gatev, Goetzmann and Rouwenhorst ... 14
2.2.2 Expanding on the GGR sample....................16
2.2.3 From SSD to Pearson correlation and quasi-multivariate pairs
trading .................................17
2.2.4 Explaining pairs trading profitability.................19
2.2.5 Further out-of-sample testing of GGR s strategy..........21
2.3 Cointegration approach ............................22
2.3.1 Univariate pairs trading........................22
2.3.1.1 Development of a theoretical framework..........22
2.3.1.2 A large-scale empirical application.............22
2.3.1.3 A deep-dive on the development of optimal trading thresh-
olds..............................23
2.3.1.4 A review of further empirical applications.........24
2.3.2 Multivariate cointegration approach.................28
2.3.2.1 Passive index tracking and enhanced indexation strategies 28
2.3.2.2 Active statistical arbitrage strategies............28
2.3.3 Adjacent developments ........................29
2.4 Time series approach..............................30
2.4.1 Modeling the spread in state space..................30
2.4.2 Applications of the Ornstein-Uhlenbeck process...........33
2.4.3 Further concepts from time series analysis..............34
2.5 Stochastic control approach..........................35
2.5.1 Modeling asset pricing dynamics with the Omstein-Uhlcnbcck pro-
cess..............................35
2.5.2 Modeling asset pricing dynamics with error correction models . . . 36
2.6 Other approaches................................37
2.6.1 Machine learning and combined forecasts approach.........37
2.6.2 Copula approach............................39
2.6.3 Principal components analysis approach...............42
2.7 Pairs trading in the light of market frictions.................43
2.8 Conclusion ..................................46
2.8.1 Distance approach...........................46
2.8.2 Cointegration approach........................47
2.8.3 Times series approach.........................47
2.8.4 Stochastic control approach......................48
2.8.5 Other approaches............................48
2.8.6 Pairs trading in the light of market frictions.............49
3 On the power and size properties of cointegration tests in the light of
high-frequency stylized facts 67
3.1 Introduction...................................69
3.2 Data sample and its stylized facts.......................71
3.3 Methodology..................................75
3.3.1 Simulation of stock prices.......................76
3.3.2 Simulation of cointegration processes.................77
3.3.2.1 Autoregressive model....................77
3.3.2.2 Generalized autoregressive conditional heteroscedasticity
model.............................78
3.3.2.3 Multiple regime smooth transition autoregressive model . 78
3.3.2.4 Multiple regime smooth transition autoregressive model
with reversible jumps....................79
3.3.2.5 Multiple regime smooth transition autoregressive model
with nonreversible jumps..................80
3.3.2.6 Parameter choices common to all Monte Carlo variants . 81
3.3.3 The cointegration relation.......................81
3.3.4 Analysis of power and size properties.................82
3.3.4.1 Cointegration tests......................82
3.3.4.2 Definition of size and power.................82
3.3.4.3 Setup of Monte Carlo simulations............. 83
3.4 Results................................................87
3.4.1 Results Type 1 through Type III...................87
3.4.2 Results Type IV............................90
3.4.3 Results Type V.............................92
3.4.4 Results Type VI.......................... 94
3.5 Economic interpretation........... ................96
3.6 Conclusion ..........................98
4 Pairs trading with partial cointegration 109
4.1 Introduction..........................111
4.2 Partial cointegration............113
4.2.1 Representation.............................113
4.2.2 Estimation of a partial cointegration model.............116
4.2.3 Consistency of estimation routine...................117
4.2.4 Power and size properties of the likelihood ratio test........120
4.3 Study design: Comparing partial cointegration with cointegration in the
context of pairs trading ............................121
4.3.1 Data...................................121
4.3.2 The backtesting framework......................122
4.3.2.1 Building blocks........................122
4.3.2.2 Formation period ......................123
4.3.2.3 Trading period........................125
4.3.3 Trading on simulated data.......................128
4.4 Results......................................129
4.4.1 Simulated data.............................129
4.4.2 Empirical data.............................132
4.4.2.1 Performance evaluation...................132
4.4.2.2 Sub-period analysis.....................137
4.5 Conclusions...................................138
4.6 AppendixA. Identifiability...........................141
4.7 AppendixB. Likelihood function........................142
4.8 AppendixC. Likelihood ratio test.......................145
5 Nonlinear dependence modeling with bivariate copulas: Statistical ar-
bitrage pairs trading on the S P 100 151
5.1 Introduction...................................153
5.2 Data and software...............................157
5.2.1 Data...................................157
5.2.2 Software.................................158
5.3 Methodology..................................158
5.3.1 Preliminaries..............................158
5.3.1.1 Copula concept........................158
5.3.1.2 Goodness-of-fit of copulas..................159
Cramer-von Mises test.....................159
Information criteria.......................161
5.3.2 Formation period............................162
5.3.2.1 Estimation period......................163
5.3.2.2 Pseudo-trading period....................164
Suitable pairs..........................166
Individualized exit rules....................166
5.3.3 Trading period.............................167
5.3.4 Return computation..........................167
5.4 Results......................................168
5.4.1 Return characteristics and trading statistics.............168
5.4.2 Value at risk..............................170
5.4.3 Annualized risk-return characteristics ................170
5.4.4 Drawdown measures..........................171
5.4.5 Subperiod analysis...........................172
5.4.6 Common risk factors..........................174
5.4.7 Market frictions ............................176
5.5 Conclusion ...................................177
6 Deep neural networks, gradient-boosted trees, random forests: Statis-
tical arbitrage on the S P 500 185
6.1 Introduction...................................187
6.2 Literature review................................189
6.3 Data and software...............................192
6.3.1 Data...................................192
6.3.2 Software.................................193
6.4 Methodology..................................193
6.4.1 Generation of training and trading sets ...............193
6.4.2 Feature generation...........................194
6.4.3 Model training.............................195
6.4.3.1 Deep neural networks....................195
6.4.3.2 Gradient-boosted trees ...................197
6.4.3.3 Random forests .......................198
6.4.3.4 Equal-weighted ensemble..................199
6.4.4 Forecasting, ranking, and trading...................200
6.5 Results......................................200
6.5.1 General results.............................200
6.5.2 Strategy performance .........................203
6.5.3 Sub-period analysis...........................207
6.5.4 Further analyses............................211
6.5.4.1 Variable importances ....................211
6.5.4.2 Industry breakdown.....................212
6.5.4.3 Robustness checks......................213
6.6 Conclusion ...................................215
7 Conclusion 223
Bibliography 227
|
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| spelling | Krauss, Christopher 1985- Verfasser (DE-588)1077582757 aut Essays on statistical arbitrage vorgelegt von Diplom-Wirtschaftsingenieur Univ. Christopher Krauß aus Nürnberg [Erlangen] 2016 xi, 250 Seiten Diagramme txt rdacontent n rdamedia nc rdacarrier Dissertation Universität Erlangen-Nürnberg 2016 Mit einem Abstract in deutscher Sprache Aktienmarkt (DE-588)4130931-5 gnd rswk-swf Zeitreihenanalyse (DE-588)4067486-1 gnd rswk-swf Kointegration (DE-588)4347470-6 gnd rswk-swf Arbitrage (DE-588)4002820-3 gnd rswk-swf (DE-588)4113937-9 Hochschulschrift gnd-content Aktienmarkt (DE-588)4130931-5 s Arbitrage (DE-588)4002820-3 s Kointegration (DE-588)4347470-6 s Zeitreihenanalyse (DE-588)4067486-1 s DE-604 HBZ Datenaustausch application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=029064821&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Krauss, Christopher 1985- Essays on statistical arbitrage Aktienmarkt (DE-588)4130931-5 gnd Zeitreihenanalyse (DE-588)4067486-1 gnd Kointegration (DE-588)4347470-6 gnd Arbitrage (DE-588)4002820-3 gnd |
| subject_GND | (DE-588)4130931-5 (DE-588)4067486-1 (DE-588)4347470-6 (DE-588)4002820-3 (DE-588)4113937-9 |
| title | Essays on statistical arbitrage |
| title_auth | Essays on statistical arbitrage |
| title_exact_search | Essays on statistical arbitrage |
| title_full | Essays on statistical arbitrage vorgelegt von Diplom-Wirtschaftsingenieur Univ. Christopher Krauß aus Nürnberg |
| title_fullStr | Essays on statistical arbitrage vorgelegt von Diplom-Wirtschaftsingenieur Univ. Christopher Krauß aus Nürnberg |
| title_full_unstemmed | Essays on statistical arbitrage vorgelegt von Diplom-Wirtschaftsingenieur Univ. Christopher Krauß aus Nürnberg |
| title_short | Essays on statistical arbitrage |
| title_sort | essays on statistical arbitrage |
| topic | Aktienmarkt (DE-588)4130931-5 gnd Zeitreihenanalyse (DE-588)4067486-1 gnd Kointegration (DE-588)4347470-6 gnd Arbitrage (DE-588)4002820-3 gnd |
| topic_facet | Aktienmarkt Zeitreihenanalyse Kointegration Arbitrage Hochschulschrift |
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