How do we compute industry exposures for ETFs using factor models?
In the list of industry factors, we detailed how the different industry factors can be grouped together into the 11 industries of the GICS taxonomy. We can also use this information to get an accurate assessment of the exposures of an ETF or mutual fund to various industries.
For an ETF, which can be constructed out of possibly 100s of individual securities, we can determine the exposure of the ETF to all industries within the GICS classification by simply summing up the industry exposures of the underlying securities.
Mathematically, if we denote the industry exposure of the i-th security within an ETF by β and the weight of that security within the ETF is w, then the contribution of that security to the ETF's exposure to that industry is simply βw The total exposure of the ETF to that industry is then the sum of the contributions of all the individual securities within the ETF. This is given by the following expression.

Here the sum runs over all the assets. This equation gives us the exposure of the ETF to the industry. We can also use this to determine the exposure of the ETF to the different sectors within the GICS classification. We simply sum up the exposures of the ETF to the industries within each sector to get the exposure of the ETF to that sector.
Let us take a simple example. We will create an artificial ETF with a few individual equities, with the following weights.
| Asset Name | Asset Ticker | Weight (in ETF) |
| Amazon | AMZN | 20% |
| Berkshire Hathaway | BRKB | 20% |
| Exxon Mobil | XOM | 20% |
| JP Morgan Chase | JPM | 20% |
| NVIDIA | NVDA | 20% |
We can then use the MSCI MAC model to determine the industry exposures of each of these individual equities. For each of the assets above, we provide the exposures, according to the MSCI MAC model, to the various industries within the GICS classification.
| Asset | Industry Name | Exposure Value |
| Amazon | Consumer Discretionary | 0.5 |
| Information Technology | 0.5 | |
| Berkshire Hathaway | Industrials | 0.409 |
| Financials | 0.496 | |
| Utilities | 0.095 | |
| Exxon Mobil | Energy | 0.91 |
| Materials | 0.09 | |
| JP Morgan Chase | Financials | 1.0 |
| Nvidia | Information Technology | 1.0 |
Note: that here a single equity can have exposure to multiple industries. For example, Amazon has exposure to both the Consumer Discretionary and Information Technology industries. However, the sum of these exposures still sums to 1.
Given these exposures, we can then compute the total exposure to each industry by summing up the individual exposures of the assets weighted by the weight of the asset in the ETF. We thus get the following industry/sector exposure breakdown for our example ETF.
| Industry Name | Weighted Exposure |
| Consumer Discretionary | 0.1 |
| Energy | 0.182 |
| Financials | 0.299 |
| Industrials | 0.082 |
| Information Technology | 0.3 |
| Materials | 0.018 |
| Utilities | 0.019 |
| 1.0 |
Note: The example above relied upon the availability of exposures for each of the individual assets within an ETF. However, there are two models available: the look-through model and the Fund model (see here for more details on distinctions between the two models). For ETFs, the results from the look-through model match with those from the fund model. However, differences might be present for Mutual funds.
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