BS and MV - Extention.Rmd

---
title: "<img src='https://raw.githubusercontent.com/scibrokes/betting-strategy-and-model-validation/master/figure/SmartOdds.png' width='840'>"
subtitle: "[<span style='color:blue'>Betting Strategy and Model Validation II (Extention)</span>](https://github.com/scibrokes/betting-strategy-and-model-validation)"
author: "[<span style='color:blue'>®γσ, Lian Hu</span>](https://englianhu.github.io/) <img src='https://raw.githubusercontent.com/scibrokes/betting-strategy-and-model-validation/master/www/ENG.jpg' width='24'> <img src='https://raw.githubusercontent.com/scibrokes/betting-strategy-and-model-validation/master/www/RYO.jpg?raw=true' width='24'>白戸則道®"
date: "`r Sys.Date()`"
output:
  tufte::tufte_html:
    toc: yes
    toc_depth: 4
    self_contained: no
  tufte::tufte_book:
    citation_package: natbib
    latex_engine: xelatex
  tufte::tufte_handout:
    citation_package: natbib
    latex_engine: xelatex
link-citations: yes
---

```{r setup}
#'@ rm(list = ls(all = TRUE))

suppressPackageStartupMessages(library('BBmisc'))
pkgs <- c('knitr', 'kableExtra', 'tint', 'devtools', 'lubridate', 'data.table', 'quantmod', 'plyr', 'stringr', 'magrittr', 'dplyr', 'tidyverse', 'htmltools', 'highcharter', 'googleVis', 'formattable', 'DT', 'fst')
 
funs <- c('plotChart2.R')

suppressAll(lib(pkgs))
l_ply(paste0('./function/', funs), source)

## Set option to below if you want to plot an independent webpage with graph 
#'@ op <- options(gvis.plot.tag=NULL)
op <- options(gvis.plot.tag = 'chart')
options(gvis.plot.tag = 'chart', warn = -1)

rm(pkgs)
```

# 1. Introduction

  By refer to *Ryo Eng Lian Hu (2017)*^[reference paper 1], I tried to model few Kelly funds for financial trading. Today I am zooming on the Kellys fund.

# 2. Data

  Firstly, we need to load a large size data.
  
  - [Fast data loading from files to R](http://appsilondatascience.com/blog/rstats/2017/04/11/fast-data-load.html)
  - [`fst`: Fast serialization of R data frames](http://blog.revolutionanalytics.com/2017/02/fst-fast-serialization-of-r-data-frames.html)
  - [fstpackage.github.io *Lightning Fast Serialization of Data Frames for R*](http://www.fstpackage.org/)

```{r read-data}
## http://appsilondatascience.com/blog/rstats/2017/04/11/fast-data-load.html
## http://blog.revolutionanalytics.com/2017/02/fst-fast-serialization-of-r-data-frames.html
#'@ BR <- readRDS('./data/BR.rds')
#'@ BRSum <- fread('./data/BRSum.csv')

## https://stackoverflow.com/questions/16300344/how-to-flatten-a-list-of-lists-in-r?answertab=votes#tab-top
#'@ BRM <- do.call(c, unlist(BR$KM, recursive = FALSE))
Date <- readRDS('./data/K1.rds')$data$Date
#'@ BRM1 <- llply(BRM, function(x) x[-c(1:5)])
#'@ BRM1 <- bind_cols(BRM1)
#'@ saveRDS(BRM1, './data/BRM1.rds')
BRM1 <- try(readRDS('./data/BRM1.rds'), silent = TRUE)

#'@ rm(BR, BRM)
```

```{r arrange-data}
## build data frame
BRM.Hi <- tryCatch(data.table(Date, Hi(BRM1)), error = function(e) Hi(BRM1))
BRM.Lo <- tryCatch(data.table(Date, Lo(BRM1)), error = function(e) Lo(BRM1))
BRM.Cl <- tryCatch(data.table(Date, Cl(BRM1)), error = function(e) Cl(BRM1))

BR.Hi <- fread('./data/BRSum.Hi.csv')
BR.Lo <- fread('./data/BRSum.Lo.csv')
BR.Cl <- fread('./data/BRSum.Cl.csv')

```

# 3. Model Comparison

  Here we plot a graph for high volume data points.

  - [Question: R Plotting Line Graph With Large Dataset](https://www.biostars.org/p/47288/)
  - [More efficient plot functions in R when millions of points are present?](https://stats.stackexchange.com/questions/7348/more-efficient-plot-functions-in-r-when-millions-of-points-are-present?answertab=votes#tab-top)
  - [Visualizing Big Data with R](https://beta.rstudioconnect.com/jmcphers/datavis-talk/datavis.html)

```{r graph-Hi}
#'@ plotChart2(Hi(BRM1), chart.type = 'Hi')
#'@ hchart(BRM.Hi, 'line')

## https://cran.r-project.org/web/packages/googleVis/vignettes/googleVis_examples.html
Line <- gvisLineChart(Hi(BRM1))
plot(Line)
```

```{r}
ggplot(data = BRM.Hi, aes()) + geom_line() + geom_point(size = 4, shape = 21, fill = 'white')
```

```{r graph-Lo}
Line <- gvisLineChart(Lo(BRM1))
plot(Line)
```

```{r graph-Cl}
Line <- gvisLineChart(Cl(BRM1))
plot(Line)
```


# 4. Conclusion


```{r stopPar, echo = FALSE}
## Set options back to original options
options(op)
options(warn = 0)
```

# 5. Appendix

## 5.1 Documenting File Creation 

  It's useful to record some information about how your file was created.

  - File creation date: 2017-10-16
  - File latest updated date: `r Sys.Date()`
  - `r R.version.string`
  - R version (short form): `r getRversion()`
  - [<span style='color:blue'>**rmarkdown** package</span>](https://github.com/rstudio/rmarkdown) version: `r packageVersion('rmarkdown')`
  - [<span style='color:blue'>**tufte** package</span>](https://github.com/rstudio/tufte) version: `r packageVersion('tufte')`
  - File version: 1.0.1
  - Author Profile: [<span style='color:blue'>®γσ, Eng Lian Hu</span>](https://beta.rstudioconnect.com/englianhu/ryo-eng/)
  - GitHub: [<span style='color:blue'>Source Code</span>](https://github.com/englianhu/binary.com-interview-question)
  - Additional session information
  
```{r info, echo = FALSE, warning = FALSE, results = 'asis'}
suppressMessages(require('dplyr', quietly = TRUE))
suppressMessages(require('formattable', quietly = TRUE))

lubridate::now()
sys1 <- devtools::session_info()$platform %>% unlist %>% data.frame(Category = names(.), session_info = .)
rownames(sys1) <- NULL
sys1 %>% formattable %>% as.htmlwidget

data.frame(Sys.info()) %>% mutate(Category = rownames(.)) %>% .[2:1] %>% rename(Category = Category, Sys.info =  Sys.info..) %>% formattable %>% as.htmlwidget

rm(sys1)
```

## 5.2 Reference

  01. [<span style='color:blue'>Betting Strategy and Model Validation - Part II</span>](https://englianhu.github.io/2017/10/Betting_Strategy_and_Model_Validation_-_Part_02/)

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