Robeco QI Dynamic High Yield IH USD
Looking for long-term capital growth and diversified exposure to global high yield via CDS index derivatives
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
Bloomberg Global HY Corporate
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
- Liquid exposure to global high yield corporates
- Performance driven by a unique quantitative model
- An alternative for passive or direct high-yield investments
About this fund
Robeco QI Dynamic High Yield is an actively managed fund that aims to provide long-term capital growth and offers diversified exposure to global high yield corporates, by investing primarily in CDS index derivatives. The selection of these instruments is based on a quantitative model. The performance is model-driven by taking active beta positions to decrease or increase the exposure towards the high-yield market within pre-defined risk limits.
Total size of fund
Size of share class
Inception date fund
Johan Duyvesteyn is Portfolio Manager Quant Fixed Income. His areas of expertise include government bond market timing, credit beta market timing, country sustainability and emerging-market debt. He has published in the Financial Analysts Journal, the Journal of Empirical Finance, the Journal of Banking and Finance, and the Journal of Fixed Income. Johan started his career in the industry in 1999 at Robeco. He holds a PhD in Finance, a Master's in Financial Econometrics from Erasmus University Rotterdam and he is a CFA® charterholder. Patrick Houweling is Co-Head of Quant Fixed Income and Lead Portfolio Manager of Robeco’s quantitative credit strategies. Patrick has published seminal articles on Duration Times Spread, factor investing in credit markets, corporate bond liquidity and credit default swaps in various academic journals, including the Journal of Banking and Finance, the Journal of Empirical Finance and the Financial Analysts Journal. The article 'Factor Investing in the Corporate Bond Market' he co-authored received a Graham and Dodd Scroll Award of Excellence for 2017. Patrick is a guest lecturer at several universities. Prior to joining Robeco in 2003, he was Researcher in the Risk Management department at Rabobank International where he started his career in 1998. He holds a PhD in Finance and a Master's (cum laude) in Financial Econometrics from Erasmus University Rotterdam.
- Per period
- Per annum
Since inception 08/2014
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.
The average credit quality of the securities in the portfolio. AAA, AA, A en BAA (Investment Grade) means lower risk and BB, B, CCC, CC, C (High Yield) higher risk.
Option Adjusted Modified Duration (years)
The interest rate sensitivity of the portfolio.
The average maturity of the securities in the portfolio.
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.
Currency risks are hedged.
All income earned will be accumulated and not be distributed as dividend. Therefore the entire return is reflected in the share price development.
Robeco QI Dynamic High Yield offers well-diversified exposure to US and European high yield corporates by investing in highly liquid CDS indices. These indices are much more liquid than direct investments in high yield bonds. Because of their high liquidity, investors can use these CDS indices to efficiently get high yield exposure with much lower transaction costs than through high yield bonds. The performance of Robeco QI Dynamic High Yield is driven by a unique quantitative market-timing model. This proprietary model has a track record of over 10 years. The model is based on academic research and uses a variety of factors, amongst others from credit and equity markets, to forecast credit returns. Based on this forecast, the exposure of the fund to the high yield corporate bond market will be decreased or increased. As a result, the beta of the portfolio varies between 0.5 and 1.5, to reduce risk in declining markets and to benefit more in rising markets. Robeco QI Dynamic High Yield Fund aims to offer a better return than the Bloomberg Barclays Global High Yield Corporate index. The index is used to express the benefits of the strategy as an alternative to passive or direct investments in high yield bonds. Weekly positioning updates are available upon request.
The investment strategy of the fund aims to outperform its 100% exposure to high yield corporates by taking active beta positions based on Robeco's quantitative market timing model. These active positions are set to always meet the predefined guidelines. As the investment exposure of the fund is obtained to a material degree through derivatives, it is important to manage counterparty risk. Therefore the credit quality of the counterparties is monitored and collateral is exchanged on a daily basis to reflect market movements in the value of the instruments. The predefined guidelines also restrict the leverage exposure of derivatives on a fund level and the currency exposure as described in the prospectus.
The fund is classified as falling under Article 6 of Regulation (EU) 2019/2088 of 27 November 2019 on sustainability-related disclosures in the financial sector. 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].
The global high yield bond spread widened slightly by 2 bps. The high yield CDS indices widened more: both the European iTraxx Crossover and the US CDX High Yield by 16 bps. Therefore, Europe performed in line with the US. The global CDS index return was -0.30% and the underlying government bonds contributed 0.05% due to a small decline of German Bund yields. Therefore, the combined return of investing in CDS indices and government bonds was -0.25% this month, underperforming the 0.08% return of the high yield cash bond index. Credit spreads reversed the tightening of June and July, and began widening out in August, with the exception of US high yield, which remained flat over the month. Stagflation fears were kept alive due to uncertainty over the inflation outlook. The number of corporates on rating watch negative has exceeded the number on rating watch positive. S&P 500 sold off before rallying into month-end, with VIX moving in sympathy. Sovereign yield curves remained inverted and steepened slightly.
Based on transaction prices, the fund's return was -0.26%. The fund's gross return underperformed the high yield cash bond market index by -0.47%. The overweight credit beta position detracted, while the region allocation contributed neutrally. The underweight duration position contributed positively due to the underweight in the US. The combined return of investing in CDS indices and government bonds underperformed high yield cash bonds and was the main detractor this month. In the long run, we do not expect structural return differences between CDS indices and bonds.
Expectation of fund manager
The positions of the fund are fully determined by the outcomes of our proprietary models. At the end of the month, the fund had an overweight credit beta position, driven by the positive momentum and valuation variables. The region allocation had an overweight position in Europe and an underweight position in the US, based on the relative valuation. The fund had underweight duration positions in Germany and the US.