categoryWeights
Compute average and periodic category weights
Description
[
computes the average and periodic category weights for the portfolio and the benchmark as
well as the corresponding active weights. AverageCategoryWeights
,PeriodicCategoryWeights
] = categoryWeights(brinsonAttributionObj
)
Examples
Compute Category Weights Using brinsonAttribution
Object
This example shows how to create a brinsonAttribution
object and then use categoryWeights
to compute average and periodic category (sector) weights.
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
Create brinsonAttribution
Object
Use brinsonAttribution
to create the brinsonAttribution
object.
BrinsonPAobj = brinsonAttribution(AssetTable)
BrinsonPAobj = brinsonAttribution with properties: 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 Weights
Use categoryWeights
to compute the average and periodic category weights for the portfolio and the benchmark, as well as, the corresponding active weights.
[AverageCategoryWeights,PeriodicCategoryWeights] = categoryWeights(BrinsonPAobj)
AverageCategoryWeights=2×4 table
Category AveragePortfolioWeight AverageBenchmarkWeight AverageActiveWeight
______________________ ______________________ ______________________ ___________________
Consumer Discretionary 0.33333 0.5 -0.16667
Consumer Staples 0.66667 0.5 0.16667
PeriodicCategoryWeights=6×5 table
Period Category PortfolioWeight BenchmarkWeight ActiveWeight
______ ______________________ _______________ _______________ ____________
1 Consumer Discretionary 0.33333 0.5 -0.16667
1 Consumer Staples 0.66667 0.5 0.16667
2 Consumer Discretionary 0.33333 0.5 -0.16667
2 Consumer Staples 0.66667 0.5 0.16667
3 Consumer Discretionary 0.33333 0.5 -0.16667
3 Consumer Staples 0.66667 0.5 0.16667
Input Arguments
brinsonAttributionObj
— Brinson attribution model
object
Brinson attribution model, specified as a brinsonAttribution
object.
Data Types: object
Output Arguments
AverageCategoryWeights
— Category weights averaged over all periods
table
Category weights averaged over all periods, returned as a table with the following columns:
Category
— Asset categoryAveragePortfolioWeight
— Average portfolio weightsAverageBenchmarkWeight
— Average benchmark weightsAverageActiveWeight
— Average active weights
PeriodicCategoryWeights
— Category weights for each period
table
Category weights 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 categoryPortfolioWeight
— Portfolio weightsBenchmarkWeight
— Benchmark weightsActiveWeight
— Active weights
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 R2022b
Apri esempio
Si dispone di una versione modificata di questo esempio. Desideri aprire questo esempio con le tue modifiche?
Comando MATLAB
Hai fatto clic su un collegamento che corrisponde a questo comando MATLAB:
Esegui il comando inserendolo nella finestra di comando MATLAB. I browser web non supportano i comandi MATLAB.
Select a Web Site
Choose a web site to get translated content where available and see local events and offers. Based on your location, we recommend that you select: .
You can also select a web site from the following list:
How to Get Best Site Performance
Select the China site (in Chinese or English) for best site performance. Other MathWorks country sites are not optimized for visits from your location.
Americas
- América Latina (Español)
- Canada (English)
- United States (English)
Europe
- Belgium (English)
- Denmark (English)
- Deutschland (Deutsch)
- España (Español)
- Finland (English)
- France (Français)
- Ireland (English)
- Italia (Italiano)
- Luxembourg (English)
- Netherlands (English)
- Norway (English)
- Österreich (Deutsch)
- Portugal (English)
- Sweden (English)
- Switzerland
- United Kingdom (English)