1.1 Data
The Multi-Asset Strategy developed by EPFR is based on the percentage flow into asset classes. In this section, the reader will gain an understanding of the aggregations which can be used to create a signal as well as the methodology behind daily percentage flow calculations.
1.1.1 Aggregations
The first step is defining a subset of data to capture in calculating our signal.
For this strategy we can include equity, fixed-income, or both types of funds. Although, we will limit ourselves to actively managed funds when compiling the raw equity data.
Equity and fixed-income (i.e. Multi-Asset) funds, which report their daily flows, are only a subset of those that report their fund flows to EPFR. The figure below shows EPFR’s daily coverage for each of these universes over time compared to our total monthly and daily coverage.
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AUM ($BB) Funds reporting Daily-flow reporters used in:
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|---|---|---|---|---|---|
| Monthly Flows | Daily Flows | Multi Asset | 7-Region Equity | Fixed Income | |
| 2007 | 9,467 | 4,332 | 2,497 | 1,196 | 1,301 |
| 2008 | 10,071 | 5,361 | 3,399 | 1,190 | 2,209 |
| 2009 | 10,488 | 6,142 | 4,317 | 927 | 3,389 |
| 2010 | 12,538 | 7,114 | 4,570 | 1,093 | 3,477 |
| 2011 | 15,269 | 8,931 | 5,319 | 1,453 | 3,866 |
| 2012 | 16,977 | 9,645 | 5,725 | 1,605 | 4,120 |
| 2013 | 20,095 | 12,142 | 7,030 | 2,134 | 4,896 |
| 2014 | 23,740 | 14,584 | 8,189 | 2,549 | 5,640 |
| 2015 | 25,321 | 15,767 | 8,496 | 2,715 | 5,781 |
| 2016 | 26,284 | 16,467 | 8,683 | 2,606 | 6,078 |
| 2017 | 30,076 | 19,240 | 9,598 | 2,917 | 6,681 |
| 2018 | 33,397 | 21,523 | 10,283 | 3,224 | 7,059 |
| 2019 | 35,570 | 22,777 | 10,953 | 3,224 | 7,729 |
| 2020 | 39,799 | 26,843 | 13,339 | 3,387 | 9,952 |
| 2021 | 50,476 | 33,766 | 15,165 | 4,507 | 10,658 |
| 2022 | 45,930 | 31,410 | 14,372 | 3,884 | 10,488 |
| * Updated at the end of July each year | |||||
Users looking for more specific detail can customize this aggregation even further using EPFR’s fund-level or share class-level granularity. Some good examples would be to consider only active, passive, ETFs or mutual funds, or only institutional or retail share class flows and assets. Users can leverage these tags to different degrees in creating aggregated signals to backtest. Further detail about this is available in the section EPFR Data & Filters.
This can be achieved using fund-level flow files or by reaching out to EPFR’s Quant Team for customized aggregations.
1.1.2 Daily Percentage Flow
To begin calculating the daily percentage flow, we start with our subset of Multi-Asset funds. To calculate the total dollar flow into an asset class, we will sum the flows into the funds investing in that asset class.
\[\text{Total Flow}_{a,t} = \sum^{N}_{i=m} \text{Flow}_{i,a,t}\] Where:
- \(\text{Total Flow}\) = the total dollar flow into an asset class \(a\), across all funds in our universe \(i\), for day \(t\)
We will want to normalize this figure. So, we repeat the process across the same fund’s Assets held under Management (AuM), to get the total AuM held in an asset class.
\[\text{Total AuM}_{a,t} = \sum^{N}_{i=m} \text{AuM}_{i,a,t}\] Where:
- \(\text{Total AuM}\) = the total assets held in an asset class \(a\), across all funds in our universe \(i\), for day \(t\)
Finally, to get the daily percentage flow for an asset class, we divide the total dollar flow by the total AuM held in an asset class.
\[\text{Percentage Flow}_{a,t} = 100 \times \frac{\text{Total Flow}_{a,t}}{{\text{Total AuM}_{a,t}}}\] Where:
- \(\text{Percentage Flow}\) = the scaled flow as a percentage into an asset class \(a\), across all funds in our universe \(i\), for day \(t\)
We repeat this across all different asset classes for the entire history.
1.1.3 Aggregate Flow File
Users may create flow percentages for their desired equity and/or fixed-income asset class aggregations and granularity using the methodology described in the previous section.
Users also have the option to use the Multi-Asset Strategy files EPFR provides, which are updated daily at 5:00 PM EST with a T+1 day lag, and are available in the user’s EPFR FTP connection under the Strategies folder. There are two different types of Multi-Asset Strategy files for fixed-income and (active) equity funds, which both contain aggregate percentage flow data. Below is the list of asset classes in each file:
- 7 Global Equity Regions:
- Asia ex Japan
- Europe ex UK
- Japan
- Latin America
- Pacific ex Japan
- United Kingdom
- United States
- 10 Fixed Income:
- Global Emerging Markets
- Western Europe Bond
- High Yield Bond
- Floating Rate Funds
- USA Treasuries - Intermediate
- USA Treasuries - Long
- USA Treasuries - Short
- Cash
- USA Muni’s
- Global Fixed Income
For this demonstration, we will be using the files MultiAsset-Rgn-daily.csv and MultiAsset-FI-daily.csv, which can be downloaded from the user’s FTP under the folder Strategies/daily and can be stored in the users local folder EPFR/daily.
Below shows a snippet of what these files contain:
Strategies/daily/MultiAsset-Rgn-daily.csv
| AsiaXJP | EurXGB | Japan | LatAm | PacXJP | UK | USA | |
|---|---|---|---|---|---|---|---|
| 20221201 | 0.007832 | -0.049717 | 0.025896 | -0.119699 | 0.047104 | 0.046167 | -0.002579 |
| 20221202 | -0.005935 | 0.045037 | 0.044813 | -0.120665 | -0.089292 | -0.005365 | -0.011253 |
| 20221205 | 0.103487 | -0.028151 | -0.130054 | 0.032016 | -0.036000 | -0.139015 | -0.090282 |
| 20221206 | -0.033235 | -0.034462 | -0.062251 | 0.008487 | -0.014146 | -0.005865 | -0.099294 |
| 20221207 | 0.139546 | 0.033230 | -0.064353 | 0.092872 | -0.010595 | -0.040282 | -0.084254 |
| 20221208 | 0.061229 | -0.058623 | -0.011848 | 0.052552 | -0.050941 | -0.052541 | -0.111574 |
Strategies/daily/MultiAsset-FI-daily.csv
| GLOBEM | WESEUR | HYIELD | FLOATS | USTRIN | USTRLT | USTRST | CASH | USMUNI | GLOFIX | |
|---|---|---|---|---|---|---|---|---|---|---|
| 20221201 | 0.051787 | 0.033868 | 0.289366 | 0.184143 | 0.096795 | 2.799822 | -0.680302 | 0.366766 | 0.063576 | -0.113089 |
| 20221202 | 0.070311 | -0.003194 | 0.033532 | -0.142670 | 0.126346 | -0.007633 | -0.033858 | 0.251873 | 0.016175 | -0.010894 |
| 20221205 | 0.197142 | 0.010749 | -0.230443 | -0.038015 | -0.606976 | -0.028715 | -0.273733 | 0.203955 | 0.011237 | 0.042224 |
| 20221206 | 0.058314 | 0.063199 | -0.167975 | -0.174142 | 0.240116 | -0.036163 | -0.385658 | 0.159930 | 0.045748 | 0.012920 |
| 20221207 | 0.004829 | 0.015731 | -0.046363 | -0.253774 | -0.014336 | 0.044745 | -0.077747 | -0.080626 | 0.009204 | 0.013182 |
| 20221208 | 0.079906 | -0.062840 | -0.144903 | -0.335260 | 0.083566 | 0.163354 | 0.306039 | 0.445716 | -0.003462 | 0.068364 |
note: all strategy files represent indicator as a % figure, i.e. 0.1 is 0.1%
For convenience, save the paths to the flow files you choose to use as flow.file.rgn and flow.file.FI respectively. Example shown below:
flow.file.rgn <- "C:\\EPFR\\daily\\MultiAsset-Rgn-daily.csv"
flow.file.FI <- "C:\\EPFR\\daily\\MultiAsset-FI-daily.csv"1.1.4 Return File
The return file for this strategy should contain daily fixed-income and passive-equity returns for the respective asset classes contained in the flow file, over the period of time the user wants to backtest.
The user can choose to either use return data found with their own resources, or the files EPFR provides specifically for the Multi-Asset Strategy, which are available in the user’s EPFR FTP connection under the Returns folder (more information available in Returns Information). The return files that EPFR provides contain Fund Return data and can be used as a proxy to equity and fixed-income market returns. The user can recreate these files using EPFR’s daily flow data with the following equation:
\[\text{Fund Return}_{a,t} = 100 \times \frac{\sum^{N}_{i=m} \text{Portfolio Change}_{i,a,t}}{\sum^{N}_{i=m} \text{Assets Start}_{i,a,t}}\] Where:
- \(\text{Fund Return}\) = the percentage return of an asset class \(a\), across all funds in our universe \(i\), for day \(t\)
For this demonstration, we will be using the files PsuedoReturns-MultiAsset-Rgn-daily.csv and PsuedoReturns-MultiAsset-FI-daily.csv, which can be downloaded from the user’s FTP under the folder Returns/daily and can be stored in the user’s local folder EPFR/returns.
Below shows a snippet of what these files contain:
Returns/daily/PsuedoReturns-MultiAsset-Rgn-daily.csv
| AsiaXJP | EurXGB | Japan | LatAm | PacXJP | UK | USA | |
|---|---|---|---|---|---|---|---|
| 20221201 | 0.715411 | 0.500223 | 0.384052 | -0.568963 | 0.727795 | 0.193082 | -0.039694 |
| 20221202 | -0.313732 | 0.127613 | -0.799961 | -0.411561 | 0.077575 | -0.037108 | -0.045309 |
| 20221205 | 0.383543 | -0.330591 | -0.879353 | -1.300552 | -0.284246 | 0.086392 | -1.455498 |
| 20221206 | -0.858824 | -0.576183 | 0.021875 | -0.732394 | 0.001009 | -0.527493 | -1.862187 |
| 20221207 | -1.122508 | -0.524565 | -0.248970 | -0.574701 | -0.828990 | -0.463849 | -0.192359 |
| 20221208 | 1.007893 | -0.082585 | -0.365683 | -0.844728 | 0.028126 | -0.268758 | 0.673149 |
Returns/daily/PsuedoReturns-MultiAsset-FI-daily.csv
| GLOBEM | WESEUR | HYIELD | FLOATS | USTRIN | USTRLT | USTRST | CASH | USMUNI | GLOFIX | |
|---|---|---|---|---|---|---|---|---|---|---|
| 20221201 | 0.446122 | 0.224148 | 0.593589 | 0.036348 | 0.624382 | 2.254448 | 0.028171 | 0.000667 | 0.415195 | 0.356319 |
| 20221202 | 0.307907 | 0.171585 | 0.051091 | -0.002056 | 0.134954 | 0.123340 | -0.000624 | 0.001003 | 0.052663 | 0.218442 |
| 20221205 | 0.126604 | 0.035921 | -0.153365 | -0.027640 | -0.356850 | -0.209727 | -0.063772 | 0.001550 | 0.140540 | -0.032771 |
| 20221206 | -0.280337 | 0.160147 | -0.255263 | 0.003406 | 0.144371 | 0.780719 | 0.017401 | 0.000984 | 0.031446 | 0.062543 |
| 20221207 | 0.140055 | 0.058259 | -0.018378 | -0.065139 | 0.634225 | 1.535799 | 0.098879 | 0.000776 | 0.185798 | 0.184534 |
| 20221208 | 0.265156 | -0.024768 | 0.142264 | -0.005329 | -0.318677 | -0.241050 | -0.032810 | 0.000782 | 0.036168 | 0.062115 |
For convenience, save the paths to the return files you choose to use as ret.file.rgn and ret.file.FI respectively. Example shown below:
ret.file.rgn <- "C:\\EPFR\\returns\\PsuedoReturns-MultiAsset-Rgn-daily.csv"
ret.file.FI <- "C:\\EPFR\\returns\\PsuedoReturns-MultiAsset-FI-daily.csv"