List of Tables
II.1 Principles and representative online portfolio selection algorithms 19
5.1 Motivating example to show the mean reversion trading idea 32
6.1 Pattern matching-based approaches: sample selection and portfolio
optimization 38
9.1 Motivating example to compare BCRP and PAMR 62
10.1 Summary of mean reversion statistics on real markets 73
10.2 A running example of CWMR-Stdev on the Cover’s game 80
10.3 Summary of time complexity analysis 81
11.1 Summaryofexistingoptimization formulations and their underlying
predictions 85
11.2 Illustration of the mean reversion strategies on toy markets 87
12.1 Summary of the six datasets from real markets 98
12.2 Summary of the performance metrics used in the evaluations 101
13.1 Cumulative wealth achieved by various trading strategies on the
six datasets and their reversed datasets 104
13.2 Statistical t-test of the proposed algorithms on the six datasets 107
13.3 Cumulative wealth achieved by various strategies on the six datasets
without and with margin loans (MLs) 121
13.4 Computational time cost (in seconds) on the six real datasets 122
13.5 Some descriptive statistics on the NYSE (O) dataset 123
13.6 Top five (average) allocation weights of some strategies on
NYSE (O) 126
A.1 All implemented strategies in the toolbox 146
A.2 All included datasets in the toolbox 147
A.3 Controlling variables 155
A.4 Vector of the analyzed results 156
C.1 Some descriptive statistics on the NYSE (N) dataset 188
C.2 Some descriptive statistics on the SP500 dataset 189
C.3 Some descriptive statistics on the MSCI dataset 190
C.4 Some descriptive statistics on the DJIA dataset 191
C.5 The top five (average) allocation weights of the proposed strategies
on five datasets 192
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