Publications by Daniel Lee
Apply it 13
# Load packages # Core library(tidyverse) library(tidyquant) # Source function source("../00_scripts/simulate_accumulation.R") 1 Import stock prices Revise the code below. Replace symbols with your stocks. Replace the from and the to arguments to date from 2012-12-31 to present. symbols <- c("GOOGL", "PG", "WMT", "ABT", "VZ") prices <-...
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R Markdown library(tidyverse) ## ── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ── ## ✔ dplyr 1.1.4 ✔ readr 2.1.5 ## ✔ forcats 1.0.0 ✔ stringr 1.5.1 ## ✔ ggplot2 3.5.1 ✔ tibble 3.2.1 ## ✔ lubridate 1.9.3 ✔ tidyr ...
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# Load packages # Core library(tidyverse) library(tidyquant) # time series library(timetk) Goal Simulate future portfolio returns five stocks: “SPY”, “EFA”, “IJS”, “EEM”, “AGG” market: “SPY” from 2012-12-31 to 2017-12-31 1 Import stock prices symbols <- c("SPY", "EFA", "IJS", "EEM", "AGG") prices <- tq_get(x = ...
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# Load packages # Core library(tidyverse) library(tidyquant) Goal Examine how each asset contributes to portfolio standard deviation. This is to ensure that our risk is not concentrated in any one asset. 1 Import stock prices Choose your stocks from 2012-12-31 to present. symbols <- c("JPM", "NVDA", "LLY", "AMZN") prices <- tq_get(x = symbol...
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Document
# Load packages # Core library(tidyverse) library(tidyquant) library(readr) # Time series library(lubridate) library(tibbletime) # modeling library(broom) Goal Examine how each asset contributes to portfolio standard deviation. This is to ensure that our risk is not concentrated in any one asset. five stocks: “SPY”, “EFA”, �...
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Document
# Load packages # Core library(tidyverse) library(tidyquant) library(readr) # Time series library(lubridate) library(tibbletime) # modeling library(broom) Goal Examine how each asset contributes to portfolio standard deviation. This is to ensure that our risk is not concentrated in any one asset. five stocks: “H”, “GOOGL”, �...
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# Load packages # Core library(tidyverse) library(tidyquant) # time series library(timetk) Goal Simulate future portfolio returns five stocks: “SPY”, “EFA”, “IJS”, “EEM”, “AGG” market: “SPY” from 2012-12-31 to 2017-12-31 1 Import stock prices symbols <- c("SPY", "EFA", "IJS", "EEM", "AGG") prices <- tq_get(x = symbol...
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# Load packages # Core library(tidyverse) library(tidyquant) # time series library(timetk) Goal Simulate future portfolio returns five stocks: “SPY”, “EFA”, “IJS”, “EEM”, “AGG” market: “SPY” from 2012-12-31 to 2017-12-31 1 Import stock prices symbols <- c("SPY", "EFA", "IJS", "EEM", "AGG") prices <- tq_get(x = ...
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Apply 12 DA
Import your data data("mtcars") mtcars <- as_tibble(mtcars) skimr::skim(mtcars) Data summary Name mtcars Number of rows 32 Number of columns 11 _______________________ Column type frequency: numeric 11 ________________________ Group variables None Variable type: numeric skim_variable n_missing complete_rate mean sd p0 p25 p50 p75 p100 hi...
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