categoryReturns

Compute aggregate and periodic category returns

Since R2020b

Description

example

[AggregateCategoryReturns,PeriodicCategoryReturns] = categoryReturns(brinsonAttributionObj) computes the aggregate and periodic category (sector) returns for the portfolio and the benchmark.

Examples

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This example shows how to create a brinsonAttribution object and then use categoryReturns to compute the aggregate and periodic category returns for the portfolio and the benchmark.

Prepare Data

Create a table for the monthly prices for four assets.

GM =[17.82;22.68;19.37;20.28];
HD = [39.79;39.12;40.67;40.96];
KO = [38.98;39.44;40.00;40.20];
PG = [56.38;57.08;57.76;55.54];
MonthlyPrices  = table(GM,HD,KO,PG);

Use tick2ret to define the monthly returns.

MonthlyReturns = tick2ret(MonthlyPrices.Variables)';
[NumAssets,NumPeriods] = size(MonthlyReturns);

Define the periods.

Period = ones(NumAssets*NumPeriods,1);
for k = 1:NumPeriods
Period(k*NumAssets+1:end,1) = Period(k*NumAssets,1) + 1;
end

Define the categories for the four assets.

Name = repmat(string(MonthlyPrices.Properties.VariableNames(:)),NumPeriods,1);
Categories = repmat(categorical([ ...
"Consumer Discretionary"; ...
"Consumer Discretionary"; ...
"Consumer Staples"; ...
"Consumer Staples"]),NumPeriods,1);

Define benchmark and portfolio weights.

BenchmarkWeight = repmat(1./NumAssets.*ones(NumAssets, 1),NumPeriods,1);
PortfolioWeight = repmat([1;0;1;1]./3,NumPeriods,1);

Create AssetTable Input

Create AssetTable as the input for the brinsonAttribution object.

AssetTable = table(Period, Name, ...
MonthlyReturns(:), Categories, PortfolioWeight, BenchmarkWeight, ...
VariableNames=["Period","Name","Return","Category","PortfolioWeight","BenchmarkWeight"])
AssetTable=12×6 table
Period    Name     Return             Category           PortfolioWeight    BenchmarkWeight
______    ____    _________    ______________________    _______________    _______________

1       "GM"      0.27273    Consumer Discretionary        0.33333             0.25
1       "HD"    -0.016838    Consumer Discretionary              0             0.25
1       "KO"     0.011801    Consumer Staples              0.33333             0.25
1       "PG"     0.012416    Consumer Staples              0.33333             0.25
2       "GM"     -0.14594    Consumer Discretionary        0.33333             0.25
2       "HD"     0.039622    Consumer Discretionary              0             0.25
2       "KO"     0.014199    Consumer Staples              0.33333             0.25
2       "PG"     0.011913    Consumer Staples              0.33333             0.25
3       "GM"      0.04698    Consumer Discretionary        0.33333             0.25
3       "HD"    0.0071306    Consumer Discretionary              0             0.25
3       "KO"        0.005    Consumer Staples              0.33333             0.25
3       "PG"    -0.038435    Consumer Staples              0.33333             0.25

Use brinsonAttribution with the brinsonAttribution object to compute aggregate and periodic category returns.

BrinsonPAobj =

NumAssets: 4
NumPortfolioAssets: 3
NumBenchmarkAssets: 4
NumPeriods: 3
NumCategories: 2
AssetName: [4x1 string]
AssetReturn: [4x3 double]
AssetCategory: [4x3 categorical]
PortfolioAssetWeight: [4x3 double]
BenchmarkAssetWeight: [4x3 double]
PortfolioCategoryReturn: [2x3 double]
BenchmarkCategoryReturn: [2x3 double]
PortfolioCategoryWeight: [2x3 double]
BenchmarkCategoryWeight: [2x3 double]
PortfolioReturn: 0.0598
BenchmarkReturn: 0.0540
ActiveReturn: 0.0059

Compute Category Returns

Use categoryReturns with the brinsonAttribution object to compute aggregate and periodic category (sector) returns.

[AggregateCategoryReturns, PeriodicCategoryReturns] = categoryReturns(BrinsonPAobj)
AggregateCategoryReturns=2×3 table
Category           AggregatePortfolioReturn    AggregateBenchmarkReturn
______________________    ________________________    ________________________

Consumer Discretionary             0.13805                    0.096876
Consumer Staples                 0.0081816                   0.0081816

PeriodicCategoryReturns=6×4 table
Period           Category           PortfolioReturn    BenchmarkReturn
______    ______________________    _______________    _______________

1       Consumer Discretionary         0.27273            0.12794
1       Consumer Staples              0.012108           0.012108
2       Consumer Discretionary        -0.14594          -0.053161
2       Consumer Staples              0.013056           0.013056
3       Consumer Discretionary         0.04698           0.027055
3       Consumer Staples             -0.016717          -0.016717

Input Arguments

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Data Types: object

Output Arguments

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Category returns aggregated over all periods, returned as a table with the following columns:

• Category — Asset category

• AggregatePortfolioReturn — Aggregate portfolio returns

• AggregateBenchmarkReturn — Aggregate benchmark returns

Category returns for each period, returned as a table with the following columns:

• Period — Time period numbers (1 for the first period, 2 for the second period, and so on)

• Category — Asset category

• PortfolioReturn — Portfolio returns

• BenchmarkReturn — Benchmark returns

References

[1] Brinson, G. P. and Fachler, N. “Measuring Non-US Equity Portfolio Performance.” Journal of Portfolio Management. Spring 1985: 73–76.

[2] Brinson, G. P., Hood, L. R., and Beebower, G. L. “Determinants of Portfolio Performance.” Financial Analysts Journal. Vol. 42, No. 4, 1986: 39–44.

[3] Menchero, J. “Multiperiod Arithmetic Attribution.” Financial Analysts Journal. Vol. 60, No. 4, 2004: 76–91.

[4] Tuttle, D. L., Pinto, J. E., and McLeavey, D. W. Managing Investment Portfolios: A Dynamic Process. Third Edition. CFA Institute, 2007.

Version History

Introduced in R2020b