Transaction Cost Modeling

Two of the most important goals of asset managers are generating outperformance, and implementing portfolios in the best way possible. At Robeco quantitative strategies, we strive to achieve outperformance for our clients by gaining exposure to factor premiums.

However, implementing portfolios in the best way possible is just as important. Strategies that look profitable on paper may turn out to be losing after trading costs. Classical momentum factor portfolios exhibit high turnover and take considerable positions in small-cap stocks, characteristics that make it difficult to adopt such a strategy in reality. The problems are visible throughout portfolio implementation: not all stocks are liquid enough to absorb a large position, some stocks have higher transaction costs than others, and some strategies generate a lot of turnover on the portfolio level.

At Robeco we take transaction costs into account in the quant investment process. Transaction costs are usually measured by the distance between the execution price and the price at the moment you decided to make the investment decision, which is also known as the ‘implementation shortfall’. We already have a proprietary transaction costs model, but we are convinced that with our expanded dataset of Robeco’s executed transactions, this model can be further improved.

At this stage there are a lot of open questions. Examples of research questions:

  • How do we get the best estimate of trading costs, before executing? What variables to use and in what kind of model?

  • What is the best trading costs estimate after we executed the trade? The stock price will have moved due to our trade execution, but also because of general market movement and other market participants trading. If we can disentangle our own market impact from other factors we can use smaller samples to accurately calibrate the model.

This Super Quant internship will be in Quant Research in close collaboration with the Trading Desk at Robeco. You will be responsible for analyzing a proprietary dataset of historical transactions, improving the cost model that is used in various live strategies and thinking critically about trade execution.

Due to the technical nature of the project and the wide variety of techniques that can be used to model transaction costs, candidates from a wide variety of masters are welcome (Econometrics, Math, Physics, Data science etc.). However enthusiasm and affinity with Finance and Trading is required.

Are you interested?
Let us know your motivation and send it together with your top-3 favorite internship topics, your CV and list of grades to
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Almgren and Chriss (2001) “Optimal execution of portfolio transactions”, Journal of Risk 3

Perold (1988) “The implementation shortfall: Paper versus reality” Journal of Portfolio Management 14(3)

De Groot, Huij and Zhou (2012) “Another Look at Trading Costs and Short-Term Reversal Profits”, Journal of Banking and Finance 36(2)