Methods for Grouping Equity Funds by Exposure and Similarity
Article Quant Q&A · Author: NickF
Summary
The document considers ways to classify and compare an equity fund universe. Suggested approaches include estimating fund exposures through regressions against style or sector indices, using tracking error or benchmark regression to identify funds that closely follow an index, and applying principal component analysis or factor analysis to summarize shared variation and distinguish funds. An expectation-maximization algorithm is mentioned as a possible topic for model construction.
It also presents an existing commercial fund taxonomy as a baseline, organized by categories such as asset class, country, region, sector, size, style, and investment method. These proposals offer several starting points for grouping funds, but the document provides no empirical comparison, clustering procedure, or validation of the resulting classifications. The taxonomy’s listed categories may also reflect a particular provider and product universe, so they are not established as universal labels.
Key ideas
- Regressions on style and sector indices can estimate a fund’s exposures.
- Benchmark regression and tracking error can help identify funds that closely follow an index.
- Principal component or factor analysis can summarize common structure across fund returns.
- Existing taxonomies offer baseline classifications by region, sector, size, style, and method.
- The document suggests approaches but does not evaluate their results or validate groupings.
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Full text
# Clever ways of "summarising" the equity fund universe # Clever ways of "summarising" the equity fund universe I am trying to get some advice or direction (brainstorm) as to the best way to summarise/cluster/etc. the equity fund universe (which for my purposes consists of about 150 funds). Some of my ideas at current: -I have access to a Value and Growth Index so could perhaps try segregate funds into value/momentum/growth groups by looking at their betas to these indices. Could also do the same to estimate the funds' exposures to certain sectors: Large Cap, Mid Cap, Small Cap; Resources, Financials, Industrials; etc. -regression on index to see which funds are closet benchmark trackers (or look at tracking error) -maybe PCA on the equity fund universe to see which funds are more dissimilar to universe... I am really just looking for several ways of analysing the funds and try to get some groupings or measures of similarity between the funds. Any pointers of what to read up on or suggestions would be appreciated PS: I would be using R for this work so if there are any R-specific libraries to look at then please notify ## Answer by David Addison (score 1) https://quant.stackexchange.com/a/38085 Capital IQ has an existing classifications by asset class, country, family, method, region, sector, size, and style. These definitely are not clever classifications, but form the baseline for fund taxonomy. - AssetClass `Alternative ALTERN Commodities COMMOD Currencies CURR Equity EQUITY Fixed Income FIXINC Mixed Assets MIXASST ` ``` Alternative ALTERN Commodities COMMOD Currencies CURR Equity EQUITY Fixed Income FIXINC Mixed Assets MIXASST ``` - country follows ISO standards - Family `BLDRS BLDRS Claymore CLAYMORE Currency Shares (Rydex) CURRENCY Direxion DIREXION Exchange Traded Notes ETNS First Trust FTRUST FocusShares FOCUS HealthShares HEALTHSH HOLDRS HOLDRS iShares ISHARES Macro Shares MACROSH Market Vectors MVECTORS Miscellaneous MISCL NETS (Northern Trust) NETS PowerShares POWERSH ProShares PROSH Realty Funds REALTY RevenueShares REVSH Rydex RYDEX SPA SPA SPDR SPDR TDX Independence TDX United States Trust USTRUST Vanguard VANGUARD Wisdom Tree WISDOM ` ``` BLDRS BLDRS Claymore CLAYMORE Currency Shares (Rydex) CURRENCY Direxion DIREXION Exchange Traded Notes ETNS First Trust FTRUST FocusShares FOCUS HealthShares HEALTHSH HOLDRS HOLDRS iShares ISHARES Macro Shares MACROSH Market Vectors MVECTORS Miscellaneous MISCL NETS (Northern Trust) NETS PowerShares POWERSH ProShares PROSH Realty Funds REALTY RevenueShares REVSH Rydex RYDEX SPA SPA SPDR SPDR TDX Independence TDX United States Trust USTRUST Vanguard VANGUARD Wisdom Tree WISDOM ``` - Method > `Hedged HEDGED Leveraged Long LEVLONG Leveraged Short LEVSHORT Quant Model QUANT Special Weights SPWEIGHTS Standard Long STANLONG Standard Short STANSHORT ` ``` Hedged HEDGED Leveraged Long LEVLONG Leveraged Short LEVSHORT Quant Model QUANT Special Weights SPWEIGHTS Standard Long STANLONG Standard Short STANSHORT ``` - Region > `Asia ASIA BRIC-Chindia BRIC Developed DEVELOP Emerging EMERG Europe EUROPE Global GLOBAL Global Ex US GLOBALXUS Latin America LATIN MidEast-Africa MIDEAST North America NAMERICA Pacific Ex Japan PACIFIC ` ``` Asia ASIA BRIC-Chindia BRIC Developed DEVELOP Emerging EMERG Europe EUROPE Global GLOBAL Global Ex US GLOBALXUS Latin America LATIN MidEast-Africa MIDEAST North America NAMERICA Pacific Ex Japan PACIFIC ``` - Sector > `Agriculture AGRIC Alternate Energy ALTENERGY Consumer CONSUMER Energy ENERGY Financial FINANCIAL General GENSECT Healthcare HEALTHCAR Housing HOUSING Industrials INDUST Infrastructure INFRASTR Materials MATERIALS Municipal fixed inc MUNIS Precious Metals PRECIOUS Real Estate REALEST Resources (General) RESOURC Services SERVICES Social SOCIAL Special Theme SPECIAL Taxable Fixed Inc TXFIXINC Technology TECHNOL Telecomm TELECOMM Timber TIMBER Transportation TRANSPORT Utilities UTILITIES Water WATER ` ``` Agriculture AGRIC Alternate Energy ALTENERGY Consumer CONSUMER Energy ENERGY Financial FINANCIAL General GENSECT Healthcare HEALTHCAR Housing HOUSING Industrials INDUST Infrastructure INFRASTR Materials MATERIALS Municipal fixed inc MUNIS Precious Metals PRECIOUS Real Estate REALEST Resources (General) RESOURC Services SERVICES Social SOCIAL Special Theme SPECIAL Taxable Fixed Inc TXFIXINC Technology TECHNOL Telecomm TELECOMM Timber TIMBER Transportation TRANSPORT Utilities UTILITIES Water WATER ``` - Size > `General GENSIZE Large-Mega ETF_LARGECAP Mid ETF_MIDCAP Small-Micro ETF_SMALLCAP ` ``` General GENSIZE Large-Mega ETF_LARGECAP Mid ETF_MIDCAP Small-Micro ETF_SMALLCAP ``` - Style > `Equity Income EQINCOME General GENSTYLE General Fixed Inc GENFIXINC Growth GROWTH High Yield Fixed Inc HIGHYLD Intermediate Fixed Inc INTFIXINC Long Fixed Inc LTFIXINC Short Fixed Inc STFIXINC Value VALUE ` ``` Equity Income EQINCOME General GENSTYLE General Fixed Inc GENFIXINC Growth GROWTH High Yield Fixed Inc HIGHYLD Intermediate Fixed Inc INTFIXINC Long Fixed Inc LTFIXINC Short Fixed Inc STFIXINC Value VALUE ``` ## Answer by owner (score 0) https://quant.stackexchange.com/a/21793 for model construction purposes, I would suggest factor analysis or PCA. Have a look at EM algorithm
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