The unique approach in 5 steps
Transcend your portfolio performance with BSD Investing's innovations:
1. Question the market information currently used for active/passive fund allocation.
2. Develop a unique method in 5 steps to allow fair comparisons between active and passive based on a proprietary fund selection process.
3. Introduce a state-of-the-art interactive tool based on innovative methods and unique active/passive fund allocation recommendations to enhance portfolio performance.
BSD Investing approach in 5 steps
Step 1 Identify the right set of funds/benchmarks
Step 2 Find comparable funds
Step 3 Access our refined data for a reliable comparison
Step 4 Follow our indicators to arrive at a fair view
Step 5 Use our active/passive fund allocation recommendation
Step 1 : Identify the right set of funds/benchmarks
- First, we identify the right funds for the investment objective, BSD Investing uses a proprietary algorithm that gives a representative benchmark of both active/passive funds for each universe.
- This allows us to systematically select only active and passive funds which follow the same official benchmark.
- The selected benchmark is the most representative in terms of assets under management and the number of funds for each specific universe.
*Mutual funds include 77.2% of active funds and 22.8% of index funds. **Benchmark : MSCI Europe NR EUR
Sources: Morningstar and BSD Investing data in EUR from 01 January 2008 to 31 December 2020. Past performance is no guarantee of future results.
Step 2 : Find comparable funds
The market currently approximates passive returns with an index. However, comparing active funds with an index is not relevant.
As passive funds' performance varies from that of the index they replicate due to fees and tracking error, comparing active funds with indices can lead to erroneous investment decisions.
What is the market looking at?
Active funds vs. index
What is BSD Investing looking at?
Active funds vs. ETFs
Step 3 : Access our refined data for a reliable comparison
Accurate comparisons can only be done based on a reliable database. We build our database from Morningstar data using 31 active/passive fund universes.
All our data is reprocessed to give a fair comparison between active and passive funds. We select the most representative share class and all comparisons are done with the same currency and the same standardized calendar. Additionally, all funds are adjusted for any change in Morningstar category.
All our data is reprocessed to give a fair comparison between active and passive funds. We select the most representative share class and all comparisons are done with the same currency and the same standardized calendar. Additionally, all funds are adjusted for any change in Morningstar category.
Raw data
- 4 share classes per fund on average
- X different currencies
- Different trading days among countries
- Morningstar category of funds changes
- Multiple benchmarks for funds in the same category
BSD Investing database
- 1 share class per fund
- 1 currency = Euro
- Same standardized calendar
- Data are adjusted for historical category changes
- Only funds following the same benchmark are part of the BSD Investing universe
Based on this reliable database, we created 31 new BSD Investing universes for both active and passive funds. They are based on a strict, proprietary fund selection methodology to perform fair comparisons between active and passive. We select the BSD Investing funds from a database of 11000 European domiciled funds representing €4 trillion.
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BSD Investing All funds universes : 31 active and passive universes of funds. Each of the 31 active/passive universe duos follow the same benchmark.
- BSD Investing ESG fund universes : 11 active and passive universes which only include the ESG funds among our BSD Investing All funds universes.
Step 4 : Follow our indicators to arrive at a fair view
The market is focused mainly on the percentage of active funds outperforming their benchmark over a specific period.
- We have developed a whole range of analytical tools and more than 100 indicators that help avoid the survivorship bias, over-reliance on one indicator and other biases currently not addressed by the market.
- We calculate not just the percentage share of active funds outperforming between two fixed dates, but also based on a yearly and quarterly average of daily returns and even over a fund’s lifetime.
- We also measure the regularity and consistency of active performance, the dispersion of performance and other risk/return measures.
⇒ Investors should take into consideration that not all data are equivalent and can lead to significantly different active / passive fund allocation decisions
Example of right vs. wrong methods to calculate the % of active funds beating the benchmark over 10Y
| Indicator | Definition |
|---|---|
| 10Y Market | Comparing an unamended category from fund data providers with a regular index over this period |
| 10Y BSD Investing | Comparing BSD Investing reprocessed universe with ETFs over this period |
| 10Y BSD Investing yearly avg | Comparing rolling yearly, quarterly and monthly BSD Investing universes active fund performance with their passive counterparts over the last 10Y on a daily basis |
| 10Y BSD Investing lifetime | Comparing BSD Investing active fund performances during their respective lifetime vs. ETFs (ie without survivorship bias as all funds present during the last 10Y are taken into account during their life) |
Proof of the relevancy of these 4 steps
The percentage of active funds outperforming depends a lot on the choice of the benchmark and the time periods, which significantly impacts the allocation decision between active and passive (see BSD Investing approach for more details).
- According to BSD Investing, 25% of active funds outperformed passive funds during their respective life time over 10 years*, while
- based on market approach, 7% of active funds outperformed the index over the same period.
% of active funds outperforming
*Sources: Morningstar and BSD Investing data in EUR from 31 December 2013 to 31 December 2023. Past performance is no guarantee of future results.
Step 5 : Use our active/passive fund allocation recommendation
To help investors make fair comparisons and take efficient active/passive fund allocation decisions, we introduce:
- BSD Investing Active/Passive fund allocation view : An equal weighted average of key indicators to give investors a fair description of the active/passive environment during a specific period.
- BSD Investing Active/Passive fund allocation recommendation : provides an estimate of active/passive fund environment by giving more importance to variables that identify market inefficiencies, such as cross-sectional standard deviation of active fund returns (dispersion), volatility of returns and more. It aims at helping investors adjust the active/passive weights in their portfolio to optimize performance.
Short Term
Balanced allocation between active and passive funds
BSD Investing fund allocation recommendation
- Our short term recommendation (6 to 12 months) is based on an estimate of the active/passive fund environment from our proprietary model.
- Our model gives more weight to variables that identify market inefficiencies such as the cross-sectional standard deviation of active fund returns (dispersion), volatility of returns and more.
- Our model uses more than 10 years of data to closely monitor market and fund evolutions with the help of more than 30 indicators.
Sources: Morningstar and BSD Investing data in EUR from 31 December 2013 to 31 December 2023. Past performance is no guarantee of future results.
Glossary
| Percentage of active funds outperforming | Percentage of active funds with a superior return than that of the passive benchmark over a specific period |
| BSD Investing Lifetime | Percentage of active funds outperforming passive funds during their respective life time over a period (i.e., we include all the funds that existed either for the entire duration or a part of that period) |
| Active/Passive fund portfolio | The active or passive portfolio is the AUM-weighted average of all funds under consideration. We simply refer to it as active or passive |
| Passive benchmark | This is the same as the passive fund portfolio |
| Return / performance | Percentage change in NAV, net of fees, of the funds. Returns / performances for a period greater than a year are annualized |
| Volatility | The standard deviation of daily returns of a fund. This measure is then annualized |
| Performance Spread | Excess return of active fund portfolio over that of the passive benchmark |
| Rolling period | Any measure calculated on a rolling basis is the measure calculated for the specified period and rolled over daily. For e.g., ‘Rolling yearly % of active funds outperforming the passive fund benchmark’ is calculated on a daily basis by measuring the percentage of active funds that outperformed the passive fund benchmark based on yearly spread |
| Long term (LT) Average | All LT averages are calculated using the rolling period measures. |
| Outperformance consistency of active funds vs. passive funds | For a specific period, this measure takes into account a timeline of 3 times the period. In the first period, we measure the percentage of active funds that outperformed the passive fund benchmark. Of these outperformers, we then measure the percentage that outperformed in the second period. Similarly, in the third period, we measure the percentage of outperformers from the outperforming lot in the second period. |
| Spread Dispersion | The standard deviation of the active vs. passive funds’ performance spreads across all the funds of a universe. Positive and Negative spread dispersion only takes into account the funds with positive or negative spreads respectively. |
| Outperformance duration | % of time more than 50% of active funds outperform passive funds |
| Spread duration | % of time active vs. passive fund benchmark spread was positive |
| Risk-adjusted returns | Ratio of the return of a fund to its volatility during the same time period. |
| Asset-weighted Beta | AUM-weighted average of the beta of all BSD Investing active funds of a universe. |
| Active/Passive Sharpe ratio | AUM-weighted average of the Sharpe ratios of each BSD Investing fund present in the universe of concern. |
| Risk Free Index | Our calculations use EONIA Capitalized 90Day TR EUR index as the risk-free index |
| BSD Investing funds | These are the funds selected, using our proprietary selection process, from the entire universe of funds that exist in the market. |
| Selection of share class | Each fund that we look at may have multiple share classes and we select only the more representative share class based on size & length of historical data. |
| BSD Investing all funds universe | 31 active and passive universes of funds. Each of the 31 active/passive universe duos follow the same benchmark. |
| BSD Investing best funds universes | 31 active and passive universes of BSD Investing best funds universes. They include only the funds from the BSD Investing all funds universes that had the best performance |
| BSD Investing ESG funds universes | 11 active and passive universes which only include the ESG funds among our BSD Investing all funds universes |
| Market 10Y indicators/10Y calculated with market data | These indicators are calculated based on the 10-year data that is available as is from Morningstar without any pre-processing. This data includes funds with multiple benchmarks. In addition, it does not account for Morningstar category changes. |
| BSD Investing 10Y indicators/10Y calculated based on our refined data | These indicators are calculated after pre-processing the 10-year Morningstar data using our proprietary selection process. |
| BSD Investing yearly average | Average of rolling yearly returns calculated on a daily basis over 10 years |
| Amplitude | Difference between the maximum and the minimum of a given indicator |
| Interquartile range | Difference between the third quartile and the first quartile values of a given indicator |
| ETF | Exchange traded fund. They are included in the passive funds together with index funds |
| AUM | Assets Under Management of a fund |
| Skewness | It is the measure of symmetry of the distribution of returns of a portfolio |
| Kurtosis | Kurtosis is a measure of whether the data are heavy-tailed or light-tailed relative to a normal distribution |
| VaR | VaR or Value at Risk is the maximum value a portfolio can lose (with a given probability) over a specific time frame |
| CVaR | CVaR or Conditional Value at Risk is the the amount of tail risk an investment portfolio has. CVaR is derived by taking a weighted average of the “extreme” losses in the tail of the distribution of possible returns, beyond the value at risk (VaR) cutoff point |
| Maximum Drawdown | A maximum drawdown (MDD) is the maximum observed loss from a peak to a trough of a portfolio, before a new peak is attained. Maximum drawdown is an indicator of downside risk over a specified time period. |
Contact
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