Publications by Henry Joyce
Apply 6
# Load packages # Core library(tidyverse) library(tidyquant) Goal Visualize expected returns and risk to make it easier to compare the performance of multiple assets and portfolios. Choose your stocks. from 2012-12-31 to 2017-12-31 1 Import stock prices # Choose stocks symbols <- c("AAPL", "GOOG", "TSLA") # Using tq_get() ---- prices <- tq_get...
908 sym R (3707 sym/16 pcs) 2 img
Apply 8
# Load packages # Core library(tidyverse) library(tidyquant) Goal Visualize and examine changes in the underlying trend in the downside risk of your portfolio in terms of kurtosis. Choose your stocks. from 2012-12-31 to present 1 Import stock prices # Choose stocks symbols <- c("AAPL", "GOOG", "TSLA") # Using tq_get() ---- prices <- tq_get(x =...
754 sym R (2781 sym/9 pcs) 1 img
Code Along 8
library(tidyverse) library(tidyquant) Goal Measure portfolio risk using kurtosis. It describes the fatness of the tails in probability distributions. In other words, it measures whether a distribution has more or less returns in its tails than the normal distribution. It matters to investors because a distribution with excess kurtosis (kurtosis > ...
809 sym R (3796 sym/16 pcs) 3 img
Apply 7
# Load packages # Core library(tidyverse) library(tidyquant) Goal Visualize and examine changes in the underlying trend in the downside risk of your portfolio in terms of kurtosis. Choose your stocks. from 2012-12-31 to present 1 Import stock prices # Choose stocks symbols <- c("AAPL", "GOOG", "TSLA") # Using tq_get() ---- prices <- tq_get(x =...
776 sym R (2779 sym/9 pcs) 1 img
Apply 7
# Load packages # Core library(tidyverse) library(tidyquant) Goal Visualize and compare skewness of your portfolio and its assets. Choose your stocks. from 2012-12-31 to 2017-12-31 1 Import stock prices # Choose stocks symbols <- c("AAPL", "GOOG", "TSLA") # Using tq_get() ---- prices <- tq_get(x = symbols, get = "stock.prices"...
757 sym R (3819 sym/12 pcs) 3 img
Week 8 Chapter 7 Code Along
library(tidyverse) library(tidyquant) Goal Measure portfolio risk using skewness. Skewness is the extent to which returns are asymmetric around the mean. It is important because a positively skewed distribution means large positive returns are more likely while a negatively skewed distribution implies large negative returns are more likely. five s...
608 sym R (3958 sym/17 pcs) 3 img
Updated Apply 5
# Load packages # Core library(tidyverse) library(tidyquant) Goal Collect individual returns into a portfolio by assigning a weight to each stock Choose your stocks. three stocks: “AAPL”, “GOOG”, “TSLA” from 2012-12-31 to 2017-12-31 1 Import stock prices # Choose stocks symbols <- c("AAPL", "GOOG", "TSLA") # Using tq_get() ---- pri...
536 sym R (2446 sym/9 pcs) 2 img
Apply 6
# Load packages # Core library(tidyverse) library(tidyquant) Goal Visualize expected returns and risk to make it easier to compare the performance of multiple assets and portfolios. Choose your stocks. from 2012-12-31 to 2017-12-31 1 Import stock prices # Choose stocks symbols <- c("AAPL", "GOOG", "TSLA") # Using tq_get() ---- prices <- tq_get...
933 sym R (3707 sym/16 pcs) 2 img
Week 7 Code Along 6
# Load packages # Core library(tidyverse) library(tidyquant) Goal Collect individual returns into a portfolio by assigning a weight to each stock five stocks: “SPY”, “EFA”, “IJS”, “EEM”, “AGG” from 2012-12-31 to 2017-12-31 1 Import stock prices # Choose stocks symbols <- c("SPY", "EFA", "IJS", "EEM", "AGG") # Using tq_get()...
342 sym R (6261 sym/17 pcs) 6 img
Apply 5
# Load packages # Core library(tidyverse) library(tidyquant) Goal Collect individual returns into a portfolio by assigning a weight to each stock Choose your stocks. three stocks: “AAPL”, “GOOG”, “TSLA” from 2012-12-31 to 2017-12-31 1 Import stock prices # Choose stocks symbols <- c("AAPL", "GOOG", "TSLA") # Using tq_get() ---- pri...
559 sym R (2446 sym/9 pcs) 2 img