## # A tibble: 22,677 x 8
## # Groups: symbol [3]
## symbol date open high low close volume adjusted
## <chr> <date> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 MSFT 1989-11-07 0.538 0.572 0.536 0.562 131542400 0.363
## 2 MSFT 1989-11-08 0.570 0.587 0.569 0.578 106486400 0.373
## 3 MSFT 1989-11-09 0.583 0.587 0.573 0.582 111526400 0.375
## 4 MSFT 1989-11-10 0.583 0.590 0.582 0.587 59168000 0.379
## 5 MSFT 1989-11-13 0.587 0.613 0.582 0.612 178905600 0.395
## 6 MSFT 1989-11-14 0.616 0.620 0.597 0.601 95241600 0.388
## 7 MSFT 1989-11-15 0.602 0.620 0.599 0.615 94492800 0.397
## 8 MSFT 1989-11-16 0.618 0.620 0.599 0.608 68054400 0.392
## 9 MSFT 1989-11-17 0.609 0.613 0.602 0.603 31651200 0.389
## 10 MSFT 1989-11-20 0.602 0.602 0.587 0.601 56937600 0.388
## # … with 22,667 more rows
## # A tibble: 93 x 3
## # Groups: symbol [3]
## symbol date yearly.returns
## <chr> <date> <dbl>
## 1 MSFT 1989-12-29 0.0741
## 2 MSFT 1990-12-31 0.730
## 3 MSFT 1991-12-31 1.22
## 4 MSFT 1992-12-31 0.151
## 5 MSFT 1993-12-31 -0.0556
## 6 MSFT 1994-12-30 0.516
## 7 MSFT 1995-12-29 0.436
## 8 MSFT 1996-12-31 0.883
## 9 MSFT 1997-12-31 0.564
## 10 MSFT 1998-12-31 1.15
## # … with 83 more rows
## # A tibble: 3 x 2
## symbol returns_avg
## <chr> <dbl>
## 1 ^IXIC 0.134
## 2 MSFT 0.284
## 3 WMT 0.159
Microsoft has the highest expected yearly return of about 28% whereas NASDAQ’s expected return is 13% and Walmart’s expected return is 16%.
## # A tibble: 3 x 2
## # Groups: symbol [3]
## symbol sd.1
## <chr> <dbl>
## 1 MSFT 0.408
## 2 ^IXIC 0.277
## 3 WMT 0.326
In terms of standard deviation, Microsoft is the riskiest with the highest sd of 0.41, NASDAQ being the least risky with the lowest sd of 0.28, and Walmart in the middle in terms of riskiness at 0.33.
## # A tibble: 3 x 2
## # Groups: symbol [3]
## symbol skewness.1
## <chr> <dbl>
## 1 MSFT 0.228
## 2 ^IXIC 0.181
## 3 WMT 1.36
## # A tibble: 3 x 2
## # Groups: symbol [3]
## symbol kurtosis.1
## <chr> <dbl>
## 1 MSFT 0.249
## 2 ^IXIC 0.362
## 3 WMT 1.35
Standard deviation as a measure when considering downside risk, underestimates it. For skewness, all stocks are positive, indicating that they all have extreme positive returns more likely than extreme negative returns. Walmart has a much higher skewness than the others being more on the positive side. In terms of kurtosis, Walmart has the fattest tail and Microsoft has the smallest tail, meaning Microsoft is less risky. Standard deviation wasn’t the best measurement of risk is this case.
Hint: This is not to be confused with HistoricalVaR you calculated in class. Look for the right code, using tq_performance_fun_options().
## [,1] [,2] [,3]
## symbol "MSFT" "^IXIC" "WMT"
## VaR "-0.5991879" "-0.4842999" "-0.1414682"
Microsoft has the greatest downside risk in terms of VaR because it has the largest loss one could expect within the 99% confidence of -0.599 compared to NASDAQ’s -0.48 amd Walmart’s -0.14.
Hint: Make your argument based on the three calculated Sharpe Ratios.
## # A tibble: 3 x 4
## # Groups: symbol [3]
## symbol `ESSharpe(Rf=2%,p=99… `StdDevSharpe(Rf=2%,p=… `VaRSharpe(Rf=2%,p=…
## <chr> <dbl> <dbl> <dbl>
## 1 MSFT 0.373 0.646 0.440
## 2 ^IXIC 0.196 0.410 0.235
## 3 WMT 0.139 0.428 0.985
I would choose Microsoft because it has higher sharpe ratios for the majority, a higher ES sharpe and SD sharpe than the other two stocks. Walmart only has a higher VaR sharpe.
Hint: Use message, echo and results in the chunk options. Refer to the RMarkdown Reference Guide.