Preface

Structure of the book

outline:

portfolio: basic portfolio concepts

portfolio construction:

back-testing

machine learning: data clean, transform, viz, exploratory ts modeling model model evaluation

math: convex optimization

Software information and conventions

The R session information when compiling this book is shown below:

sessionInfo()
#> R version 4.0.2 (2020-06-22)
#> Platform: x86_64-w64-mingw32/x64 (64-bit)
#> Running under: Windows 10 x64 (build 17763)
#> 
#> Matrix products: default
#> 
#> locale:
#> [1] LC_COLLATE=English_United States.1252 
#> [2] LC_CTYPE=English_United States.1252   
#> [3] LC_MONETARY=English_United States.1252
#> [4] LC_NUMERIC=C                          
#> [5] LC_TIME=English_United States.1252    
#> 
#> attached base packages:
#> [1] parallel  stats     graphics  grDevices utils     datasets  methods  
#> [8] base     
#> 
#> other attached packages:
#> [1] rugarch_1.4-4              CVXR_1.0-1                
#> [3] dplyr_1.0.2                PerformanceAnalytics_2.0.4
#> [5] quantmod_0.4.17            TTR_0.23-6                
#> [7] xts_0.12-0                 zoo_1.8-8                 
#> 
#> loaded via a namespace (and not attached):
#>  [1] tidyselect_1.1.0            xfun_0.19                  
#>  [3] ks_1.11.7                   purrr_0.3.4                
#>  [5] lattice_0.20-41             vctrs_0.3.2                
#>  [7] generics_0.0.2              htmltools_0.5.0            
#>  [9] SkewHyperbolic_0.4-0        yaml_2.2.1                 
#> [11] gmp_0.6-0                   rlang_0.4.7                
#> [13] pillar_1.4.6                nloptr_1.2.2.2             
#> [15] glue_1.4.1                  Rmpfr_0.8-1                
#> [17] bit64_0.9-7                 lifecycle_0.2.0            
#> [19] stringr_1.4.0               mvtnorm_1.1-1              
#> [21] evaluate_0.14               knitr_1.29                 
#> [23] curl_4.3                    Rcpp_1.0.5                 
#> [25] KernSmooth_2.23-17          DistributionUtils_0.6-0    
#> [27] truncnorm_1.0-8             bit_4.0.4                  
#> [29] spd_2.0-1                   digest_0.6.25              
#> [31] stringi_1.5.3               bookdown_0.20              
#> [33] numDeriv_2016.8-1.1         grid_4.0.2                 
#> [35] quadprog_1.5-8              tools_4.0.2                
#> [37] magrittr_1.5                Rsolnp_1.16                
#> [39] tibble_3.0.3                crayon_1.3.4               
#> [41] pkgconfig_2.0.3             ellipsis_0.3.1             
#> [43] GeneralizedHyperbolic_0.8-4 MASS_7.3-51.6              
#> [45] Matrix_1.2-18               rmarkdown_2.5              
#> [47] rstudioapi_0.13             R6_2.4.1                   
#> [49] mclust_5.4.6                compiler_4.0.2

Acknowledgments

Prerequisites

Some basic knowledge about finance, time series analysis, optimization (linear and convex), programming (python¹ or R) would be preferred.

Later I will add corresponding python code↩︎

Portfolio Construction