It is one of the hypotheses that pops up every year, during Christmas an uncle tells he will retire because of his crypto gains and FOMO will hit hard. In order to how much truth there is to this we constructed a dataset with randomly selected social media profiles and see if they mention Crypto now (and in what context) and how this evolves during the december month.

The dataset

We

Past year we introduced our general narrative dashboard. This dashboard summarizes all (potential) relevant hot topics in financial markets for the future and gives insight in to how much they are top of mind in the investment community in order to catch risk and opportunities early. We have updated our default narrative/scenario set and this post will provide an overview and descroption of all monitored narratives. These include new relevant financial narratives that will be monitored in the default model (on request user specific narratives can always be added). The

Stress testing or scenario analysis is a tool that is in every portfolio manager, financial risk manager or strategist’s toolbox. Additionally regulators nowadays require all financials to perform stress tests. The main critique on scenario analysis is that it always remains a bit vague and not concrete in as to whether which scenario will play out as mainly scenarios are defined as: “if this will happen, then this scenario will play out and it will probably has this effect on our portfolio.”. The problem here is that it is hard

Short insight in to our model. We trained it on the Dow Jones with our default narratives and we wanted to share the results: Dow Jones dashboard

We will present cases on various tickers the next coming weeks, so stay tuned! We will also post updates on our twitter feed: Twitter

Alternative data and Machine Learning are gaining rapid traction in the investment industry. However AI and Machine learning still is not able to beat the market or most regular investors in a real life environment, even though the internet is full of articles predicting stock prices with 99% accuracy (overfitting is no joke). One can safely say there are domains where humans outperform AI and there are domains where it is the other way around. This also goes for investing. But why only use either human input or AI input

Did you ever notice that you are more cautious in traffic after there has been a large accident in the news? Then you are aware that sometimes the human brain takes shortcuts that behavioural economists call heuristics. Additionally, you are probably aware that alternative (big) data is giving rise to new real-time insights. Finally, the fact that artificial intelligence, AI or machine learning is rapidly changing the world probably also hasn’t gone by unnoticed. In this paper I am going to describe how these three components (behavioural psychology, alternative data

Alternative data and Machine Learning are gaining rapid traction in the investment industry. However AI and Machine learning still is not able to beat the market or most regular investors in a real life environment, even though the internet is full of articles predicting stock prices with 99% accuracy (overfitting is no joke). One can safely say there are domains where humans outperform AI and there are domains where it is the other way around. This also goes for investing. But why only use either human input or AI input