![]() Sustainable Active Quant has a more extended values-based exclusion list and also excludes companies with low SDG scores from the investment universe.įurthermore, Sustainable Active Quant has a significantly better ESG profile than the benchmark and a 30% lower carbon footprint. For example, value investors can use qualitative analysis (which will likely include a lot. We have a version of Active Quant available in our product range that offers improved sustainability compared to our flagship Active Quant strategies. Quant trading is a way of implementing strategies, not a strategy. We apply a direct link between the enhanced engagement program and the portfolio. We integrate the carbon footprint in the portfolio- process by ensuring that the footprint of the portfolio is lower than that of the benchmark. We ensure that the ESG score is better than that of the benchmark. We take ESG into account as a variable in the quality factor. We integrate proprietary Smart ESG scores in our stock ranking model. The strategy adheres to the general Robeco exclusion policy. When Do Quant Strategies Outperform From 2010 to 2017, quant managers generally did a better job than fundamental managers at beating their benchmarks. We incorporate sustainability in the investment and decision-making process in multiple ways: ![]() It is classified as Article 8 under the EU Sustainable Finance Disclosure Regulation. This strategy promotes, among other characteristics, environmental and/or social characteristics, which can include exclusionary screening, ESG integration, ESG risk monitoring and active ownership. An algorithm can analyze 100 different strategies, each with several criteria, in a split. Finally, we focus on reducing trading costs at every step of the investment process. Quantitative trading strategies give leverage. The active quant strategies have a higher tracking error and more concentrated portfolio than our enhanced indexing strategies, while our robust portfolio construction algorithm enables fully explainable positions. Machine learning has found numerous commercial uses in Finance - across the quantitative investment. Our Active Quant approach focuses on a high information ratio while controlling risk. Deep Learning for Quant Finance Strategies. Portfolio managers and researchers monitor the entire investment process closely, resulting in full control and human overview of the portfolio. Portfolios are rebalanced on a monthly basis after new rankings have been generated by the model. We determine the relative attractiveness of stocks based on value, quality, momentum and analyst revisions.Īll decision making at portfolio level is the result of signals from the quantitative stock-ranking model and the settings of our portfolio construction algorithm. We offer both absolute return strategies, which target zero exposure to traditional markets, either at all times, or on average and total return strategies, which maintain some exposure to traditional markets. The investment strategy allows us to act on both positive and negative views on companies by overweighting and underweighting them against the benchmark. Using both qualitative and quantitative tools, we’re meticulous in every detail of the investment process.
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