Embracing the new regime of trading models
By Sylvain Thieullent, CEO of Horizon
Very few people predicted or planned for the current crisis. What was unthinkable earlier this year has happened and triggered extensive losses in the markets. As ever though, it’s what a business does to adapt in the face of change that defines it. Most regions are entering something more closely resembling normality and, as we do move in this direction, it will be key for financial institutions to quickly update trading strategies to the new market conditions.
Trading is increasingly more automated using quantitative analytics, predictive models, and innovative algorithms. However, because the scope of the current situation was so unimaginable and the change in asset values so drastic, the models used to inform many previous trading algorithms are now effectively redundant. The data they were built on is outdated and they will no longer accurately calculate risk and forecast market movements.
Looking at equities, the way we value companies is now significantly different. For example, prior to the crisis, a tourism business would be valued in more or less the same way as a retail or hospitality business. That will have to change now, and institutions will have to apply specific variables depending on the kind of business and its location. Additionally, the extent of the losses by French investment banks in Q1 from equity derivatives shows that trading algorithms, and the commonly used models that underpin them – such as Value at Risk (VaR) – need to be adjusted. Even more so considering derivatives are often used to hedge trading positions in a market downturn. Although these losses are not expected to continue, firms need to be able to value derivatives more accurately as we emerge out of this crisis.
The fact that many existing trading models are no longer suitable has thrown the active vs passive debate back into the forefront of conversation, with active tipped for a big comeback. It’s true that active managers can provide much more value than passive strategies in current circumstances. This is because they can more quickly identify which companies are likely to succeed in the post-covid19 economy when algorithms stick to their formula. Having said this, the rise of active will likely be short lived, and it will become more important for firms to improve the agility with which their models can adapt to new economic scenarios.
Before the crisis, there was a relatively level playing field in passive strategies. When the market is stable for a long time, people tend to end up with similar models. However, with such drastic changes to the market and such large pricing spreads to examine, competing industry players will end up drawing different conclusions. Their view on the future will vary depending on their analysis of the new data. This could really shake up the market. Understandably, financial institutions do not share their successful strategies so this new environment could create a disparity between those who can move quickly and those who can’t. It will, therefore, be increasingly important that firms have software that can easily interact with different pricing models and different sources.
Overall, the weight of modernising trading infrastructure is heavy, but firms must embrace new methodologies. Interestingly, there are now some actively managed ETFs, which could represent the best of both worlds in that they are more active than algorithms but also electronic. It could be an indication of where things are heading. Active managers may be able to better navigate the upswing for now, but the ultimate trading system will be a hybrid of the two. And, eventually, the lines between active and passive may blur as an active manager moulds into one who trades electronically but regularly and rapidly updates their trading models.