Robeco QI Chinese A-share Active Equities I USD
Systematically benefiting from mainland China companies
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 China A International Index (Net returns, USD)
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
- Aims to consistently outperform the benchmark
- Diversified exposure to an integrated multi-factor stock selection model
- Using proven return factors value, quality and momentum
About this fund
Robeco QI Chinese A-share Active Equities is an actively managed fund that invests in stocks of companies with an A-share listing in mainland China. The selection of these stocks is based on a quantitative model. The fund's objective is to achieve a better return than the index. The fund uses a quantitative stock selection strategy which ranks stocks on their expected future relative performance using three factors: valuation, quality and momentum. The portfolio overweights stocks with an attractive valuation, a profitable operating business, strong price momentum, and positive recent revisions from analysts.
Total size of fund
Size of share class
Inception date fund
Wilma de Groot
Jan de Koning
Han van der Boon
Wilma de Groot is Head of the Core Quant Equities capability and Deputy Head of Quant Equity. She is responsible for Enhanced Indexing, Active Quant and Sustainable Beta strategies and specializes in asset pricing anomalies, portfolio construction and sustainability integration. She has published in various academic publications including the Journal of Impact and ESG Investing, Journal of Banking and Finance, Journal of International Money and Finance, Journal of Empirical Finance and the Financial Analysts Journal. She is a guest lecturer at several universities. Wilma joined Robeco as a Quant Researcher in 2001. Wilma has a PhD in Finance from Erasmus University Rotterdam and holds a Master’s in Econometrics from Tilburg University. She is a CFA® charterholder. Tim Dröge is Portfolio Manager Quantitative Equities. He focuses on managing Core Quant strategies, both Enhanced Indexing and Active Quant portfolios. Tim specializes in quantitative stock selection, portfolio construction and Emerging Markets. Previously, he held positions as Portfolio Manager Balanced Investments and Account Manager institutional clients. Tim has been working as a Portfolio Manager since 2001. He started his career at Robeco in 1999. He holds a Master's in Business Economics from Erasmus University Rotterdam. Machiel Zwanenburg is Portfolio Manager Quantitative Equities. He focuses on managing Core Quant strategies, both Enhanced Indexing and Active Quant portfolios and specializes in quantitative stock selection and portfolio construction. One of his areas of expertise is sustainability integration within quantitative equities. Previously, he held positions as Risk Manager at RobecoSAM and Head of Client Portfolio Risk at Robeco. He joined Robeco in 1999 as a member of the Quant Research team. He holds a Master's in Econometrics from Erasmus University Rotterdam and a Master's in Economics from the London School of Economics. Jan de Koning is Portfolio Manager Quantitative Equities. He focuses on managing Core Quant strategies, both Enhanced Indexing and Active Quant strategies and specializes in quantitative stock selection, portfolio construction and sustainability integration. He is also the author of a book on quantitative investing and has published in The Journal of Impact and ESG Investing. Before joining Robeco in 2015, he worked as a fiduciary manager at NN Investment Partners. He started his investment career in 2005 with Centuria Capital and was a Portfolio Manager at Somerset Capital Partners. Jan holds a Master's in Organizational Studies from Tilburg University, is a CFA®, CAIA®, CIPM® and CMT charterholder. He is also a PhD Researcher at the University of Amsterdam focusing on index capitalism in the age of sustainable investing. Han van der Boon is Portfolio Manager Quantitative Equities. He focuses on managing Core Quant strategies, both Enhanced Indexing and Active Quant portfolios and specializes in quantitative stock selection and portfolio construction. He was a Technical Portfolio Manager and Operational Portfolio Manager with a focus on equities in the period 2009-2018. He joined Robeco in 1997 as a Business Controller. He holds a Master's in Business Administration from Erasmus University Rotterdam. Vania Sulman is Portfolio Manager Quantitative Equities and focuses on managing the Core Quant strategies. She specializes in the stock selection and sustainability integration in customized portfolios. She rejoined Robeco in 2022. Previously, she worked as a data scientist for three years and prior to that as a Quant Researcher at Robeco with a focus on quantitative stock selection. She joined the industry and Robeco in 2016. She holds a Master's (cum laude) in Quantitative Finance from Erasmus University Rotterdam.
- Per period
- Per annum
Since inception 11/2017
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.
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.
Included service fee
This fee is intended to cover official fees, such as the cost of annual reports, annual shareholders' meetings and price publications.
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 Luxembourg and is subject to the Luxembourg tax laws and regulations. The fund is not liable to pay any corporation, income, dividend or capital gains tax in Luxembourg. The fund is subject to an annual subscription tax ('tax d'abonnement') in Luxembourg, which amounts to 0.01% of the net asset value of the fund. This tax is included in the net asset value of the fund. The fund can in principle use the Luxembourg treaty network to partially recover any withholding tax on its income.
Fiscal treatment of investor
Investors who are not subject to (exempt from) Dutch corporate-income tax (e.g. pension funds) are not taxed on the achieved result. Investors who are subject to Dutch corporate-income tax can be taxed for the result achieved on their investment in the fund. Dutch bodies that are subject to corporate-income tax are obligated to declare interest and dividend income, as well as capital gains in their tax return. Investors residing outside the Netherlands are subject to their respective national tax regime applying to foreign investment funds. We advise individual investors to consult their financial or tax adviser about the tax consequences of an investment in this fund in their specific circumstances before deciding to invest in the fund.
- Top 10
Currency risk is not hedged.
The fund does not distribute dividend. The fund retains any income that is earned and so its entire performance is reflected in its share price.
Robeco QI Chinese A-share Active Equities is an actively managed fund that invests in stocks of companies with an A-share listing in mainland China. The selection of these stocks is based on a quantitative model. The fund's objective is to achieve a better return than the index. The fund aims for a better sustainability profile compared to the Benchmark by promoting E&S (i.e. Environmental and Social) characteristics within the meaning of Article 8 of the European Sustainable Finance Disclosure Regulation, integrating sustainability risks in the investment process and applying Robeco’s Good Governance policy.The fund applies sustainability indicators, including but not limited to, normative, activity-based and region-based exclusions, proxy voting and engagement. The fund uses a quantitative stock selection strategy which ranks stocks on their expected future relative performance using three factors: valuation, quality and momentum. The portfolio overweights stocks with an attractive valuation, a profitable operating business, strong price momentum, and positive recent revisions from analysts. The majority of stocks selected through this approach will be components of the Benchmark, but stocks outside the Benchmark may be selected too. The fund can deviate from the weightings of the Benchmark. Highly ranked stocks are overweighted against the Benchmark, whereas low-ranked stocks are underweighted, resulting in a well-diversified portfolio. The fund aims to outperform the Benchmark over the long run, whilst still controlling relative risk through the applications of limits (on sectors) to the extent of deviation from the Benchmark. This will consequently limit the deviation of the performance relative to the Benchmark. The Benchmark is a broad market weighted index that is not consistent with the ESG characteristics promoted by the fund.
Risk management is fully integrated into the investment process to ensure that positions always meet predefined guidelines.
ESG score target
Environmental footprint expresses the total resource consumption of the portfolio per mUSD invested. Each assessed company's footprint is calculated by normalizing resources consumed by the company's enterprise value including cash (EVIC). We aggregate these figures to portfolio level using a weighted average, multiplying each assessed portfolio constituent's footprint by its respective position weight. Sovereign and cash positions have no impact on the calculation. If an index is selected, its aggregate footprint is shown besides that of the portfolio. The equivalent factors that are used for comparison between the portfolio and index represent European averages and are based on third-party sources combined with own estimates. As such, the figures presented are intended for illustrative purposes and are purely an indication. Figures only include corporates The reported waste generation by companies in the portfolio and index can include Incinerated Waste, Landfill Waste, Nuclear Waste, Recycled Waste and Mining Tailing Waste. While these types of waste have different environmental impacts, in the comparison all types of waste are aggregated and expressed as total weight. The difference in tonnes/mUSD invested between portfolio and index is expressed as ‘equivalent to the annual waste generation of # people’, based on the average tonnes of household waste generated per European.
Sustainalytics ESG Risk Rating
The Portfolio Sustainalytics ESG Risk Rating chart displays the portfolio's ESG Risk Rating. This is calculated by multiplying each portfolio component's Sustainalytics ESG Risk Rating by its respective portfolio weight. If an index has been selected, those scores are provided alongside the portfolio scores, highlighting the portfolio's ESG risk level compared to the index. The Distribution across Sustainalytics ESG Risk levels chart shows the portfolio allocations broken into Sustainalytics' five ESG risk levels: negligible (0-10), low (10-20), medium (20-30), high (30-40) and severe (40+), providing an overview of portfolio exposure to the different ESG risk levels. If an index has been selected, the same information is shown for the index. Only holdings mapped as corporates are included in the figures.
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.The following sections display the ESG-metrics that are relevant for this fund along with short descriptions. For more information please visit the sustainability-related disclosures. The index used for all sustainability visuals is based on [Index name].
Based on transaction prices, the fund's return was -7.18%. The objective of the Chinese A-share Active strategy is to consistently outperform the MSCI China A International Index, with relatively high activeness and strong exposure to proven quantitative factors such as value, quality and momentum. The portfolio consists of roughly 200 stocks and overweights stocks with an attractive valuation, a profitable operating business, strong price momentum and positive recent revisions from analysts. By using our integrated multi-factor stock selection model, we expect the strategy to consistently outperform the benchmark.