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Factors are supposed to behave differently given different market environments which creates the diversification. In practice, however, such an approach needs to be carried out very carefully and with sophistication to match investor preferences.
No one has a reliable way of predicting the future. That is why we must diversify. It is the cheapest and most effective way of dealing with uncertainty. In our computerised world, the Markowitz-style approaches from the 1950s are not the answer. But how can we establish a reliable and objective way of diversification? How can machines amplify our investment results?
We are currently observing a renaissance of AI. The combination of data sets available, high-performance computing power, infinite storage and more intelligent algorithms have lately fueled the developments. In this first blog entry, we discuss a graph-based machine learning approach to create alternative indices with robust performance and lower risk.