Publications by Daniel Lee
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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 2 Convert prices to returns 3 Assign a weight to each asset ## [1] "AGG" "EEM" "EFA" "IJS" "SPY" ## [1] 0.25 0.25 0.20 0.20 0.10 ## # A tibbl...
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Week 12: Code Along 11
# Load packages # Core library(tidyverse) library(tidyquant) Functions Introductions When should you write a function df <- tibble::tibble( a = rnorm(10), b = rnorm(10), c = rnorm(10), d = rnorm(10) ) df$a <- (df$a - min(df$a, na.rm = TRUE)) / (max(df$a, na.rm = TRUE) - min(df$a, na.rm = TRUE)) df$b <- (df$b - min(df$b, na.rm = TRU...
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Functions When should you write a function? ## # A tibble: 10 × 4 ## a b c d ## <dbl> <dbl> <dbl> <dbl> ## 1 0.332 0.153 0.782 1 ## 2 0.765 0 0.473 0.519 ## 3 1 0.0651 0.498 0.448 ## 4 0 0.311 0.943 0.511 ## 5 0.809 0.573 0.373 0.168 ## 6 0.831 0.260 0 0.308 ## 7 0.516 0.143 1 0 #...
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Apply 11
Import your data data(flights) flights %>% skimr::skim() Data summary Name Piped data Number of rows 336776 Number of columns 19 _______________________ Column type frequency: character 4 numeric 14 POSIXct 1 ________________________ Group variables None Variable type: character skim_variable n_missing complete_rate min max empty n_...
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Import your data data(flights) flights %>% skimr::skim() Data summary Name Piped data Number of rows 336776 Number of columns 19 _______________________ Column type frequency: character 4 numeric 14 POSIXct 1 ________________________ Group variables None Variable type: character skim_variable n_missing complete_rate min max empty n_...
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Monte Carlo Simulation
# Load packages # Core library(tidyverse) library(tidyquant) # Import Excel files library(readxl) # 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"...
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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”, “IJS”, “EEM”, “AGG” from 2012-12-31 to 2017-12-31 1 Import stock prices 2 Convert prices to returns 3 Component Contribution Step-by-Step Refresh your memo...
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Best Practices 11
Write one key takeaway per chapter. Write at least 100 words for each chapter summary. Ch1 It’s Not Just about Forecasting In chapter one we learned the main ideologies of economics and how we as future managers should focus on making critical decisions that will impact our future businesses if we choose to build on them. We really dig into le...
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Code Along 12
# 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”, “IJS”, ...
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Document
# 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 symbols <- c("NFLX", "AMZN", "GOOG") prices <- tq_get(x = symbols, get = "stock.prices", ...
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