Week 14: Code along 12
CHAPTER 10 Component Contribution to Standard Deviation
Luke Moriarty
2022-11-15
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 memory on covariance with this video. Click this link Refresh your memory on matrix multiplication. Click this link
## AGG EEM EFA IJS SPY
## 2013-01-31 -0.0062314818 -0.0029356001 0.0366064100 0.052133090 4.992277e-02
## 2013-02-28 0.0058916378 -0.0231050073 -0.0129695690 0.016175342 1.267805e-02
## 2013-03-28 0.0009846231 -0.0102347632 0.0129695690 0.040258193 3.726795e-02
## 2013-04-30 0.0096398633 0.0120846592 0.0489676215 0.001222127 1.903029e-02
## 2013-05-31 -0.0202145584 -0.0494834017 -0.0306555928 0.041976501 2.333572e-02
## 2013-06-28 -0.0157782285 -0.0547285981 -0.0271445305 -0.001403001 -1.343443e-02
## 2013-07-31 0.0026876047 0.0131599274 0.0518603108 0.063541433 5.038593e-02
## 2013-08-30 -0.0082981768 -0.0257056421 -0.0197460608 -0.034743194 -3.045145e-02
## 2013-09-30 0.0111448200 0.0695889588 0.0753386824 0.063873520 3.115625e-02
## 2013-10-31 0.0082909175 0.0408612923 0.0320813207 0.034234077 4.526639e-02
## 2013-11-29 -0.0025098158 -0.0025943098 0.0054497637 0.041661326 2.920690e-02
## 2013-12-31 -0.0055827482 -0.0040743570 0.0215279276 0.012891799 2.559616e-02
## 2014-01-31 0.0152914929 -0.0903226763 -0.0534133570 -0.035775399 -3.588445e-02
## 2014-02-28 0.0037564572 0.0332206147 0.0595054100 0.045257762 4.451014e-02
## 2014-03-31 -0.0014804940 0.0380217630 -0.0046028114 0.013315309 8.261399e-03
## 2014-04-30 0.0081828727 0.0077727927 0.0165294223 -0.023184432 6.927258e-03
## 2014-05-30 0.0117211716 0.0290913076 0.0158285209 0.006205204 2.294117e-02
## 2014-06-30 -0.0005753667 0.0237337140 0.0091652618 0.037718656 2.043493e-02
## 2014-07-31 -0.0025121550 0.0135556888 -0.0263794989 -0.052009590 -1.352898e-02
## 2014-08-29 0.0114307148 0.0279046076 0.0018000838 0.043658115 3.870524e-02
## 2014-09-30 -0.0061669743 -0.0808566622 -0.0395983796 -0.061260315 -1.389236e-02
## 2014-10-31 0.0105840781 0.0140961089 -0.0026548517 0.068874721 2.327752e-02
## 2014-11-28 0.0065488021 -0.0155407440 0.0006252476 0.004773965 2.710141e-02
## 2014-12-31 0.0014752498 -0.0404423528 -0.0407468179 0.025295749 -2.539736e-03
## 2015-01-30 0.0203148056 -0.0068955117 0.0062266214 -0.054628196 -3.007728e-02
## 2015-02-27 -0.0089883941 0.0431359574 0.0614505880 0.056914381 5.468249e-02
## 2015-03-31 0.0037406253 -0.0150863608 -0.0143887132 0.010156846 -1.583076e-02
## 2015-04-30 -0.0032329599 0.0662815238 0.0358165791 -0.018417952 9.785875e-03
## 2015-05-29 -0.0043835346 -0.0419113842 0.0019527114 0.007510015 1.277425e-02
## 2015-06-30 -0.0108258784 -0.0297464117 -0.0316790005 0.004171511 -2.052124e-02
## 2015-07-31 0.0085848704 -0.0651780822 0.0201144184 -0.027375498 2.233776e-02
## 2015-08-31 -0.0033639692 -0.0925123972 -0.0771523474 -0.047268348 -6.288655e-02
## 2015-09-30 0.0080816230 -0.0318249587 -0.0451948496 -0.038464751 -2.584726e-02
## 2015-10-30 0.0006857283 0.0618081421 0.0640259951 0.063589600 8.163491e-02
## 2015-11-30 -0.0038982580 -0.0255601981 -0.0075560638 0.024415351 3.649114e-03
## 2015-12-31 -0.0019189923 -0.0389471341 -0.0235947978 -0.052157248 -1.743385e-02
## 2016-01-29 0.0123298344 -0.0516366963 -0.0567579689 -0.060306908 -5.106896e-02
## 2016-02-29 0.0088318577 -0.0082116920 -0.0339138341 0.020605475 -8.261510e-04
## 2016-03-31 0.0087086840 0.1218791055 0.0637455795 0.089910220 6.510043e-02
## 2016-04-29 0.0025460278 0.0040793093 0.0219750201 0.021044475 3.932909e-03
## 2016-05-31 0.0001351525 -0.0376286004 -0.0008559986 0.004396950 1.686877e-02
## 2016-06-30 0.0191672466 0.0445825600 -0.0244912633 0.008292171 3.469931e-03
## 2016-07-29 0.0054295935 0.0524420916 0.0390001498 0.049348431 3.582200e-02
## 2016-08-31 -0.0021561783 0.0087986612 0.0053269294 0.011260918 1.196811e-03
## 2016-09-30 0.0005157805 0.0248726013 0.0132790775 0.008614878 5.794373e-05
## 2016-10-31 -0.0082054546 -0.0083121396 -0.0224038355 -0.038134959 -1.748906e-02
## 2016-11-30 -0.0259897169 -0.0451620178 -0.0179744018 0.125246540 3.617600e-02
## 2016-12-30 0.0025380577 -0.0025298522 0.0267028177 0.031491678 2.006930e-02
## 2017-01-31 0.0021262175 0.0644314833 0.0323819966 -0.012143831 1.773617e-02
## 2017-02-28 0.0064381402 0.0172578364 0.0118364314 0.013428896 3.853926e-02
## 2017-03-31 -0.0005531281 0.0361890338 0.0318056710 -0.006532995 1.249270e-03
## 2017-04-28 0.0090297016 0.0168662927 0.0239521757 0.005107639 9.877229e-03
## 2017-05-31 0.0068472679 0.0280597909 0.0348102953 -0.022862482 1.401413e-02
## 2017-06-30 -0.0001829170 0.0092242165 0.0029559259 0.029151511 6.354867e-03
## 2017-07-31 0.0033339670 0.0565942026 0.0261878800 0.007481652 2.034573e-02
## 2017-08-31 0.0093699441 0.0232439210 -0.0004483592 -0.027564583 2.913498e-03
## 2017-09-29 -0.0057327004 -0.0004464642 0.0233429537 0.082321429 1.994907e-02
## 2017-10-31 0.0009780023 0.0322789003 0.0166533727 0.005915983 2.329081e-02
## 2017-11-30 -0.0014832734 -0.0038972165 0.0068703072 0.036913381 3.010802e-02
## 2017-12-29 0.0047396386 0.0369255154 0.0133982058 -0.003731191 1.205495e-02## AGG EEM EFA IJS SPY
## AGG 7.398467e-05 0.0001042108 4.178215e-05 -7.812103e-05 -9.031866e-06
## EEM 1.042108e-04 0.0017547120 1.039017e-03 6.437712e-04 6.795434e-04
## EFA 4.178215e-05 0.0010390167 1.064237e-03 6.490282e-04 6.975411e-04
## IJS -7.812103e-05 0.0006437712 6.490282e-04 1.565450e-03 8.290272e-04
## SPY -9.031866e-06 0.0006795434 6.975411e-04 8.290272e-04 7.408316e-04## [,1]
## [1,] 0.02347491## AGG EEM EFA IJS SPY
## [1,] 0.0003874127 0.009257147 0.005815631 0.005684461 0.002330253## [1] 0.02347491## # A tibble: 1 × 5
## AGG EEM EFA IJS SPY
## <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 0.017 0.394 0.248 0.242 0.099## # A tibble: 5 × 2
## asset contribution
## <chr> <dbl>
## 1 AGG 0.017
## 2 EEM 0.394
## 3 EFA 0.248
## 4 IJS 0.242
## 5 SPY 0.0994 Component Contribution with a Custom Function
## # A tibble: 1 × 5
## AGG EEM EFA IJS SPY
## <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 0.017 0.394 0.248 0.242 0.0995 Visualizing Component Contribution
6 Rolling Component Contribution
## # A tibble: 1 × 6
## date AGG EEM EFA IJS SPY
## <date> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 2015-01-30 0.039 0.372 0.256 0.245 0.088## # A tibble: 1 × 6
## date AGG EEM EFA IJS SPY
## <date> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 2015-02-27 0.036 0.374 0.249 0.252 0.089## # A tibble: 36 × 6
## date AGG EEM EFA IJS SPY
## <date> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 2015-01-30 0.039 0.372 0.256 0.245 0.088
## 2 2015-02-27 0.036 0.374 0.249 0.252 0.089
## 3 2015-03-31 0.027 0.37 0.255 0.255 0.092
## 4 2015-04-30 0.027 0.372 0.256 0.252 0.093
## 5 2015-05-29 0.024 0.385 0.254 0.246 0.092
## 6 2015-06-30 0.018 0.383 0.248 0.257 0.094
## 7 2015-07-31 0.014 0.375 0.253 0.261 0.097
## 8 2015-08-31 0.013 0.404 0.237 0.257 0.09
## 9 2015-09-30 0.012 0.407 0.248 0.238 0.094
## 10 2015-10-30 0.003 0.405 0.244 0.243 0.105
## # ℹ 26 more rows
