Goal

Visualize and examine changes in the underlying trend in the downside risk of your portfolio in terms of kurtosis.

Choose your stocks.

I chose the stocks NVDA, AMD, INTC, AVGO and TSM. These stocks all have to do with computer technology.

from 2012-12-31 to present

1 Import stock prices

2 Convert prices to returns

3 Assign a weight to each asset

## [1] "AMD"  "AVGO" "INTC" "NVDA" "TSM"
## [1] 0.25 0.25 0.20 0.20 0.10
## # A tibble: 5 × 2
##   symbols weights
##   <chr>     <dbl>
## 1 AMD        0.25
## 2 AVGO       0.25
## 3 INTC       0.2 
## 4 NVDA       0.2 
## 5 TSM        0.1

4 Build a portfolio

## # A tibble: 155 × 2
##    date        returns
##    <date>        <dbl>
##  1 2013-01-31  0.0580 
##  2 2013-02-28 -0.0108 
##  3 2013-03-28  0.0251 
##  4 2013-04-30  0.0390 
##  5 2013-05-31  0.142  
##  6 2013-06-28 -0.00420
##  7 2013-07-31 -0.0312 
##  8 2013-08-30 -0.0307 
##  9 2013-09-30  0.0892 
## 10 2013-10-31 -0.00316
## # ℹ 145 more rows

5 Calculate Skewness

## # A tibble: 1 × 1
##   Kurtosis
##      <dbl>
## 1    0.641

6 Plot

Distribution of portfolio returns

Expected Return vs Risk

Rolling kurtosis

Has the downside risk of your portfolio increased or decreased over time? Explain using the plot you created. You may also refer to the skewness of the returns distribution you plotted in the previous assignment.

It has decreased. You can see that during 2019-2020 the rolling kurtosis skyrocketed itself and ended up losing it over time. The plot I created explains a lot because in 2020 a lot of businesses were effected and over time lost value. The skewness of the return distribution was 0.641 which suggests it has a slightly higher chance of an occasional positive return.