mgei

# What is PCA?
# - PCA is a form of multi-dimensional scaling. 
# - It transforms the data into a lower dimensional space while keeping the maxiumum of information. 
# Book: Multi-Dimensional Diversification

# get data https://www.msci.com/end-of-day-data-search

library(tidyverse)
library(tidyquant)
library(readxl)

mgei

library(tidyquant)

ty10 <- tq_get("DGS10", get = "economic.data", from = as.Date("1950-01-01"))


mod_dur <- function(yield) {
  # out <- (1-(1/(1+0.5*yield/100)^(2*10)))/(yield/100)
  out <- (1-(1/(1+0.5*yield)^(2*10)))/(yield)
  
  return(out)

mgei

library(tidyverse)
library(jsonlite)

get_earnings <- function(symbol, av_key, get = "quarterly", cache_dir = "cache") {
  if (!(cache_dir %in% list.dirs(full.names = F, recursive = F))) {
    dir.create(cache_dir)
  }
  
  if (!(paste0(symbol, ".json") %in% list.files(cache_dir))) {
    print("downloading")

mgei

library(tidyverse)
library(tidyquant)
library(lubridate)

# get data from Yahoo ----
spx <- tq_get("^GSPC")

# calculate returns ----
ret_daily <- spx %>% 
  mutate(ret = adjusted/lag(adjusted)-1,

mgei

library(shiny)

ui <- fluidPage(
  fluidRow(
    column(width = 12,
           tabsetPanel(
             tabItem("main", "MENU"),
             tabItem("more", uiOutput("hello"))
           ))
  )

mgei

library(shiny)
library(shinyWidgets)
library(tidyverse)

# read persistent data or create a new file if it does not exist yet
if ("favs.csv" %in% list.files()) {
  favs <- read_file("favs.csv") %>% 
    strsplit(", ") %>% 
    .[[1]] %>% 
    as.numeric() %>% 

mgei

library(tidyverse)

library(ggplot2)

periods <- 10
trend <- 0
vola <- 0.1

leverage <- 2

mgei

library(shiny)
library(tidyverse)

# data <- readRDS("persistent_data/data.RDS")
data <- as_tibble(mtcars) %>% head()

ui <- fluidPage(
  tableOutput("mytable"),
  actionButton("go", "filter it"),
  actionButton("save", "save it")

mgei

What I've done thus far

Install QMKL

But before:

Install Py-videocore

Increase video memory!

mgei

library(tidyverse)

localurl <- function(document, path = ""){
  
  path     <- str_remove_all(path, "/$|^/")
  document <- str_remove_all(document, "/$|^/")
  
  path     <- file.path(path, document) %>% 
    str_remove_all("/$|^/")
  document <- last(str_split(path, pattern = "/", simplify = T))