[blockchain], [defi], [dlt], [hash_rate], [digital_currency]
Fear of inflation was also translated into cryptocurrencies’ rally. SZ-NLP engine, identified the causality between [decentralised digital assets] and [inflation hedging] via an extreme TINA (There Is No Alternative) scenario; this could be explained as the focal point described in “mixed motive games”.
Our model took exposure to the [blockchain] theme via a number of single stocks specialised in the sector.
[economic_recovery], [purchasing_pattern], [school_closures], [entertainment], [local_production]
Households’ excess savings has caused a shift in [spending patterns] towards nonessentials. With most parents working from home, and school closures around the world, it was not only the online gaming sector that saw a boost; all types of children’s entertainment including toys and children’s streaming services as well as [online education] providers enjoyed an unusual increase in demand.
[Toy manufacturers] that managed to put the lessons learnt from the global [supply chain disruptions] due to the pandemic in place by quickly shifting to more [local production] and [supplier diversification], were the absolute winners of this race, more specifically during the [holiday sales].
One of the themes identified by SZ-NLP that would react positively to the increasing long-term yields, was the financial sector (inc. lending, fintech, banking, etc). Coupled with specific themes from the shift in [consumer behaviour] and [purchase patterns] to nonessentials, [recreational vehicle financing] was a very niche theme proposed by the engine that contributed very well to our February returns.