Knowledge Base Articles
Part I - Portfolio Construction - Parameter & Model Uncertainty
There is a number of challenges associated with portfolio construction based on historical data. This three-part article series explores some of the most common issues attributed to the model-based portfolio optimization: the sensitivity to changes in data, large variations in portfolio weights and the bad out-of-sample performance.
Fourth Quarter 2019: The Most Relevant Trends in WealthTech
The fourth quarter of 2019 was marked by an increased interest in B2B business models among the FinTech robo advisors. Although the shift from B2C to B2B has been in the headlines a few months before, the last three months yielded more concrete examples of how new players tailor their business models to cater to other companies, rather than consumers. Meanwhile, the debate on whether the process of financial advice would be entirely digital or contain hybrid elements continued as well - with many British players robo advisors adding human capabilities to the scope of their services. Finally, in the context of digitalised offerings, it becomes harder for the regulator to tell the difference between financial advice and guidance - and therefore it becomes essential to review the definitions of the services to optimise the consumer protection accordingly.
Is there any point to optimising asset allocation in portfolios?
Over the years, numerous studies have shown how complex investment strategies fail to outperform simple asset allocation methods. Other studies emphasise the amount of sheer luck that goes into the favourable performance of the investment strategies; it has been repeatedly shown that in many instances, an attempt to deviate from the market portfolio has odds no better than a coin flip. These findings seem to point towards one cold fact - the optimal portfolio weights are impossible to find. Or are they?
September 2019 News Update
During September, we distinguished three trends gaining prominence in the financial industry's innovation landscape. The first one explores the tendency of the WealthTech FinTechs moving towards B2B business models aimed at the DIY investment platform providers with established customer bases. The second trend concerns the definition of the appropriate customer base for B2C robo-advisors. While many automated financial advice providers still target millennials, the generations approach was widely criticised at the recent Robo Investing conference, with many delegates favouring adjusting the offerings to life situations experienced by the consumers regardless of their generation. The third theme of the month concerned the rising importance of explainability in automated decision-making, already reflected in Article 22 of the GDPR. Such a requirement may hinder the providers of digital services from using some of the machine learning methods without appropriate validation frameworks.
Robo Investing Event Summary
Through September 10-11th, Kidbrooke Advisory attended the Robo Investing 2019 Event in London. Existing for over two years, the event has become an excellent platform for knowledge sharing and communication between numerous FinTechs, banks, consultancies and other players of the emerging industry, all across the world. Today we are summarising the core trends and themes discussed at the event. The main topics led the overall direction of the robo-advice offerings as well as tips and tricks on achieving more customer engagement.