Social Networks, Behavioural Biases, and Institutional Investor Trading

Dong, Ming | $31,784

Ontario York University 2021 SSHRC

The importance of investor psychology to the efficiency of markets has been in the forefront of research in finance for many decades, as highlighted by Nobel prize-winners Daniel Kahneman, Robert Shiller, and Richard Thaler. A relatively unexplored area has been the impact of social networks on professional investment managers. With the advance of communication technologies and social network tools such as Facebook and Twitter, people geographically dispersed are increasingly socially connected. An emerging field of finance has shown remarkable effects of social networks on investor behaviour. Social networks transmit both valuable information and biased opinions, and they can significantly influence markets. We seek to quantify the degree to which social networks influence the trading behaviour of investment managers and financial market stability. The proposed research project intends to exploit extreme market events like the market crash of 2020, and variation over time in risk aversion from behavioural effects like seasonal depression. The literature on social network effects has largely focused on retail investors, showing problematic herding and over-reaction, as anyone watching the gyrations of meme stocks like GameStop will have noticed, but has left largely unresolved the vulnerability of professional money managers to social contagion. This proposal represents a novel undertaking with important implications for our target audiences, which include policy makers, regulators, financial professionals, and the public.

The first phase of this agenda will be to examine the effect of social networks on mutual fund manager trading during the Covid-19 pandemic outbreak. Preliminary work of our team suggests that social connection intensifies biases associated with panic selling, and social connections to Covid hotspot areas promote panic selling. The second phase will have us investigating the effect of social interaction across historical market crashes, recoveries, and periods of market calm. The end goal of this phase is to generalize the insights from the pandemic study by looking at the trading behaviour during multiple market crashes, and to extend this by exploring “normal” market conditions as well as recoveries from crash periods. The third phase will fold in investor mood and characterize not only seasonal patterns in portfolio rebalancing but also the role of social networks in mitigating or exaggerating fund manager biases associated with a form of stock market seasonality – seasonal affect disorder (SAD). It has been documented in the literature that SAD likely accounts for the well-known stock market seasonality that sees lower returns from May through October. We will also examine how investor skill interacts with social connections. Preliminary work suggests that unskilled managers are adversely affected while skilled mangers can distill valuable information from behavioural biases and benefit from social connections.

This research contributes to the rapidly emerging field of social economics and finance by exploring the transmission of cognitive biases through the social networks of institutional investors in contrast to prior research focused on retail investors. We expect this research will interest policy makers, corporate executives, professional money managers, and members of the general public alike since these decision-makers rely on market prices to guide their assessment of market conditions. If social interactions intensify behavioural biases among investors during times of crisis, social connectivity can instigate market volatility and destabilize financial markets. This research agenda will help inform policy makers of the prevalence of social connectedness and its impact on markets.

With funding from the Government of Canada

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