Investment Strategies

Why Behavioural Finance Needs Great Tech To Thrive

Tom Burroughes, Group Editor, London, 17 May 2022

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Mainstream
Behavioural finance is now being used as a marketing and branding strategy. For example, behavioural finance is the “dominant differentiator” in the philosophy and marketing strategy of Fusion Family Wealth, a Long Island, New York-based wealth manager, according to CEO Jonathan Blau. The giant software vendor Orion issued a white paper Don’t Call it a Fad: Behavioral Finance is the Future of Fintech, along with an on-demand webinar on behavioural finance’s role “in the future of our industry” by Dr Daniel Crosby, the firms’ chief behavioural officer.

Without the tech to gather the insights and put them to work, however, the “cash value” of all these theories will not be achieved. 

Schulenburg took a step back to review where the subject came from. “2008 highlighted the limitations of classical economics and its associated models of both the economy and risk. Central banks knew their tools had failed. This failure gave rise to new ideas being developed in areas such as Complexity Economics, Agent-Based Modelling (ABM) and associated areas of Artificial Intelligence (AI) and Machine Learning (ML),” she said. “More specifically, within this realm, our data- driven approach uses AI/ML to identify trading strategies and Agent-Based Modelling to adapt them to market regimes. In other words, strategies that can exploit evolving trading patterns in security prices. We use Agent-Based Modelling to adapt those strategies to market regimes, where ABM considers the market as an ecosystem of continually evolving 'agent’ investors.”

To illustrate, Schulenburg said she finds “core” investment strategies to exploit inefficiencies in short- and long-term market dynamics, such as periods of higher market volatility and changes in direction that create opportunities in the short term, and where there are steady and trending periods with lower volatility that can be exploited by long-term approaches.

When it comes to trying to automate strategies to make money, investors might naturally worry that there need to be “circuit-breakers” or some other in-built tools to stop a strategy running amok. 

“Because of high levels of automation, we would expect that systematic strategies (including the mean reverting and trend following named above) would have breakers to avoid extreme market behaviour and events such as fat finger trades,” she said. (By “fat finger” she means when a trader hits the wrong button on the keyboard, with subsequent mayhem.)

“Other types of breakers are designed to prevent getting carried away and keep trading constantly in big market moves. These are typically part of systematic execution strategies where algorithms are in place to control the trades. And in addition, risk systems will typically take care of these types of extreme events,” she said. 

“For example, in extreme events (as market prices are dropping intra-daily or over a few days), a trend-following strategy will start selling a stock as the price drops and crosses certain metrics (this reinforces the drops), and in the case of a mean-reverting strategy designed to buy stocks at cheaper prices, the strategy starts buying cheap bringing some liquidity and stability to the system, however if prices continue to fall sharply, the strategy has to stop buying at some point,” she said.

“Regarding fat finger trades, examples include a 'flash crash’ in May 2010, and more recently we experienced a flash crash in Europe where it was reported by Citi that one of their traders booked an erroneous order in the Nordics. This had a ripple effect in Europe. These errors are mainly originated by people and seem to happen every other decade,” she said.

Not a taboo any more
Schulenburg argued that acceptance of AI tools is growing and not seen as a weird or sinister development any longer. 

“AI has had a significant impact over the last few years in the asset and wealth management sectors,” she said. As costs continue to rise and managers are under pressure to keep fees down, they need to look at AI as a way to help with running portfolios as efficiently as possible. “We are trying to help the end-investor….it is a noble goal and an innovative one.”

To see other recent articles on the topic, look here and here.
 

 

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