Robeco QI Institutional Global Developed Quality Equities T12 EUR
Systematic approach to benefit from companies with strong balance sheets and high profitability
Every share class of a product invests in the same portfolio of securities and has the same investment objectives and policies. However, their parameters might deviate. For instance and amongst others, their distribution type, currency exposure or fees and expenses might differ. The most common share classes at Robeco are:
a) D/DH shares, which are regular shares and available for all Investors;
b) I/IH shares, for institutional investors as defined from time to time by the Luxembourg supervisory authority.
For more information on share classes please go to the prospectus.
Class and codes
MSCI World Index
Under the EU Sustainable Finance Disclosure Regulation, products can be labelled as either Article 6, 8 or 9 fund.
Article 6 - The fund is not in scope of enhanced sustainability disclosures compared to Article 8 and 9.
Article 8 - The fund does not have a sustainable investment objective but promotes environmental or social characteristics and is subject to enhanced sustainability disclosures.
Article 9 - The fund has a sustainable investment objective and is subject to enhanced sustainability disclosures.
Regardless of Article 8 or 9, the companies in which investments are made must follow good governance practices, and sustainable investments must not do any significant harm.
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- Performance & costs
- Part of Robeco's range of factor-premium strategies, which includes Conservative Equities, Value Equities and Momentum Equities
- Quantitative stock-selection strategy aimed at selecting securities of companies that have good quality characteristics, e.g. strong balance sheets and high profitability.
- Avoid going against other factors, avoid unrewarded risk and prevent unnecessary turnover.
About this fund
Robeco QI Institutional Global Developed Quality Equities invests in stocks with good quality characteristics in developed economies. The fund's long-term aim is to harvest the quality premium by selecting the most attractive quality stocks. The selection of these quality stocks is carried out using a quantitative model, which ranks stocks, based on a number of quality variables as well as value and momentum variables.
Total size of fund
Size of share class
Inception date fund
Jan Sytze Mosselaar
Pim van Vliet
Guido is Head of Robeco’s Factor Investing strategies and Co-head of the Quant Fixed Income team. He also holds a position as Professor of Behavioral Finance and Financial Markets at Erasmus University Rotterdam. Guido has published in top-ranked academic journals including the Journal of Financial Economics, the American Economic Review and Management Science. He started his career in the investment industry in 2004. Before joining Robeco in 2017, Guido was Head of Quantitative Research Fixed Income and Multi Asset at NN Investment Partners. He has worked together in research projects with the 2017 Nobel Prize laureate Richard Thaler. Guido holds a PhD and a Master's (cum laude) in Financial and Business Economics from Erasmus University Rotterdam. Daniel Haesen is Portfolio Manager Quantitative Equities and focuses on managing Factor Investing portfolios such as the Value-, Momentum-, Quality- and Multi-Factor portfolios. He specializes in factor research and portfolio management. Daniel joined Robeco in 2003 as a quantitative researcher, with a specific focus on quant selection research, working on both equity and corporate bond multi-factor selection models. He was also responsible for quantitative sustainability and quantitative allocation research. He has published in several academic journals, including the Journal of Banking and Finance. He holds a Master's degree in Econometrics and Quantitative Finance from Tilburg University in the Netherlands and is a CFA® charterholder. Wouter Tilgenkamp is Portfolio Manager Quantitative Equities and focuses on managing Factor Investing portfolios, such as the Value-, Momentum-, Quality- and Multi-Factor portfolios. Wouter joined Robeco in 2016 as a Data Scientist, with a specific focus on Equity Trading Research, automatization of portfolio processes, portfolio construction, and optimal execution of strategies. He started his financial career in 2014 as Derivative Trader at Optiver. He holds a Bachelor of Science in Applied Mathematics from Technical University of Delft and a master’s degree in Quantitative Finance. Jan Sytze Mosselaar is Portfolio Manager Quantitative Equities. He focuses on managing the wide range of regional and global Conservative Equities strategies, Robeco’s Low-volatility strategy, and the factor investing portfolios, such as Value-, Momentum-, Quality- and Multi-Factor portfolios. Jan Sytze is the author of ‘A Concise Financial History of Europe’, published by Robeco. He started his career in 2004 at Robeco and worked for ten years as a multi-asset portfolio manager, responsible for multi-asset funds, quant allocation funds and fiduciary pension mandates. He holds a Master’s in Business Economics with a specialization in Finance & Investments from the University of Groningen. He is a CFA® charterholder. Pim van Vliet is Head of Conservative Equities and Chief Quant Strategist. As Head of Conservative Equities, he is responsible for a wide range of global, regional, and sustainable low-volatility strategies. He specializes in low-volatility investing, asset pricing, and quantitative finance. He is the author of numerous academic research papers including publications in the Journal of Banking and Finance, Management Science, and the Journal of Portfolio Management. Pim is a guest lecturer at several universities, author of an investment book and speaker at international seminars. He became Portfolio Manager in 2010. Pim joined Robeco in 2005 as a Researcher with responsibility for asset allocation research. Pim holds a PhD and a Master's cum laude in Financial and Business Economics from Erasmus University Rotterdam.
- Per period
- Per annum
Since inception 02/2020
Tracking error ex-post (%)
The ex-post tracking error is defined as the volatility of the fund's achieved excess return over the index return. In fund management, most managers are subject to an ex-ante (pre-determined) tracking error, which defines the extent of the additional risk they may take when aspiring to outperform the fund's benchmark. The ex-post tracking error explains the distribution of past fund performances compared to those of its underlying benchmark. With a higher tracking error, the fund's returns deviate more from its index's returns, hence there is a greater chance that the fund may outperform. The wider the spread of returns relative to the benchmark, the more "actively" a fund has been managed. In contrast, a low tracking error indicates more "passive" management.
This ratio serves to evaluate the quality of the excess return a fund manager has achieved because it takes the active risk involved into account. The information ratio is defined as the excess return over the benchmark return divided by the fund's tracking error. The higher the information ratio, the better. For example, a fund with a tracking error of 4% and an excess return of 2% over benchmark has an information ratio of 0.5, which is quite good.
This ratio measures the risk-adjusted performance and allows the performance quality of different investments to be compared. It is calculated by subtracting the risk-free rate from the fund's returns and dividing the result by the fund's standard deviation (risk). So the Sharpe ratio tells us whether a fund's returns are the result of smart investment decisions or stem from taking extra risk. The higher the ratio, the better, meaning that a greater return is achieved per unit of risk. This ratio is named after its inventor, Nobel Laureate, William Sharpe.
Alpha measures the difference between a portfolio's actual return and its expected performance, given the level of risk, compared to the benchmark. A positive alpha figure indicates that the fund has performed better than expected, given the level of risk. Beta is used to calculate the level of risk compared to the benchmark..
Beta is a measure of a portfolio's volatility, or systematic risk, in comparison to the benchmark. A beta of 1 indicates that the portfolio will move with the benchmark. A beta of less than 1 means that the portfolio will be less volatile than the benchmark. A beta of more than 1 indicates that the portfolio will be more volatile than the benchmark. For example, if a portfolio's beta is 1.2 it is theoretically 20% more volatile than the benchmark.
Standard deviation is a measure of the dispersion of a set of data from its mean. The more spread out the data is, the higher the deviation. In finance, standard deviation is applied to the annual rate of return of an investment to measure the investment's volatility (risk).
Max. monthly gain (%)
The maximum (i.e. highest) absolute positive monthly performance in the underlying period.
Max. monthly loss (%)
The maximum (i.e. highest) absolute negative monthly performance in the underlying period.
Months out performance
Number of months in which the fund outperformed the benchmark in the underlying period.
Hit ratio (%)
This percentage indicates the number of months in which the fund outperformed in a given period.
Months Bull market
Number of months of positive benchmark performance in the underlying period.
Months outperformance Bull
Number of months in which the fund outperformed positive benchmark performance in the underlying period.
Hit ratio Bull (%)
This percentage indicates the number of months the fund outperformed a positive benchmark in an underlying period.
Months Bear market
Number of months of negative benchmark performance in the underlying period.
Months outperformance Bear
Number of months in which the fund outperformed negative benchmark performance in the underlying period.
Hit ratio Bear (%)
This percentage indicates the number of months the fund outperformed a negative benchmark performance in an underlying period.
Dividend paying history
Indication of annual charges that are deducted for this fund. This indication is based on the costs over the last calendar year and may vary from year to year. Transaction costs incurred by the fund, any performance fees and other one-off costs are not included in the ongoing charges.
Included management fee
A fee paid by the fund to the asset management company for the professional management of the fund.
The transaction costs shown are the average annual transaction costs over the last three years calculated in accordance with European regulations.
Fiscal product treatment
The fund is established in the Netherlands. The fund is tax transparent for Dutch corporate-income tax purposes. This means that all results, from a Dutch tax perspective, deemed to be attributed directly to the investors. As a consequence, the fund is not liable to corporate income tax and is not required to withhold Dutch withholding tax on any distribution.
Fiscal treatment of investor
- Top 10
Currency risk will not be hedged. Exchange-rate fluctuations will therefore directly affect the fund's share price.
The fund may distribute dividend.
Robeco QI Institutional Global Developed Quality Equities is part of Robeco's offering on factor premiums and invests in stocks with good quality characteristics in developed economies. The fund's long-term aim is to harvest the quality premium by selecting the most attractive quality stocks. The selection of these quality stocks is carried out using a quantitative model, which ranks stocks, based on a number of quality variables as well as value and momentum variables.
Risk management is fully integrated in the investment process to ensure that positions always meet predefined guidelines.
Full sustainability-related disclosuresDownload full report
Summary sustainability-related disclosuresDownload summary
The fund systematically incorporates sustainability in the investment process via exclusions, ESG integration, ESG and environmental footprint targets, engagement and voting. The fund does not invest in stocks issued by companies that are in breach of international norms or where its activities have been deemed detrimental to society following Robeco's exclusion policy. Financially material ESG factors are integrated in the portfolio construction to ensure the ESG score of the portfolio is better than that of the index. In addition, the environmental footprints of the fund are made lower than that of the benchmark by restricting the GHG emissions, water use and waste generation. With these portfolio construction rules, stocks issued by companies with better ESG scores or environmental footprints are more likely to be included in the portfolio while stocks issued by companies with worse ESG scores or environmental footprints are more likely to be divested from the portfolio. In addition, where a stock issuer is flagged for breaching international standards in the ongoing monitoring, the issuer will become subject to engagement. Lastly, the fund makes use of shareholder rights and applies proxy voting in accordance with Robeco's proxy voting policy.
Based on closing GAV, the fund's return was -0.70%. The fund aims to achieve higher risk-adjusted returns than both the broad market and generic quality indices over a full business cycle by taking an efficient, well-diversified exposure to the enhanced quality factor, present in stocks that exhibit above-average profitability, have high earnings quality and are conservatively managed.
Expectation of fund manager
Jan Sytze Mosselaar
Pim van Vliet
The fund follows a bottom-up driven investment strategy to gain exposure to the proven quality factor. Rather than using generic factor definitions, it uses enhanced definitions to avoid unrewarded risk and maximize its return potential. The Robeco quality factor has a multi-dimensional view of quality that incorporates profitability, earnings quality and management policy. Each of these three themes has deeply rooted academic underpinnings and has shown to have strong stand-alone performance potential. Furthermore, the strategy aims to prevent that exposure to the quality factor results in negative exposure to other factors, like value, momentum and low-volatility. By doing so, the strategy avoids unwanted and unintended factor tilts. It is a rules-based process that tries to avoid unnecessary transaction costs by only buying stocks if the expected gains outweigh the costs of the trade.