The CAPM relies on markets being efficient. However, we have seen numerous examples that challenge this idea. Thousands of papers describe value, momentum, reversal effects and other “market anomalies”, which all relate to the behavior of market participants. Next to those, a large body of academic literature focuses on the setup of the market itself. An interesting stream looks at inefficiencies around the rebalancing of stock indices. Indices, such as the S&P 500 or AEX index, can be seen as a weighted average of included assets. Index providers create these indices, for example to facilitate benchmarking, but the decisions they make on in- and excluding assets in them can have significant impact on asset return.
As investors we want to avoid to become victims of these inefficiencies. During this project you will investigate the effects around index rebalance of a list of major market-cap and smart-beta stock indices. In addition you will develop predictive models to cope with these inefficiencies. Robeco Quantitative Research has access to rich historical databases that enable back-testing and evaluating investment strategies. You will also conduct a literature study, work with several data sets providing data on indices, implement various algorithms, and conduct back-tests on stocks. Robeco’s experienced researchers will help you with these steps. Creative, analytic and programming skills are essential to successfully complete the project.
Chen, Noronha and Singal (2004) “The price response to S&P 500 index additions and deletions: Evidence of asymmetry and a new explanation”, Journal of Finance 59(4)
Huij and Kyosev (2016) “Price response to factor index additions and deletions”, SSRN Working Paper
Fernandes and Mergulhão (2016) “Anticipatory effects in the FTSE 100 index revisions”, Journal of Empirical Finance 37