The increasing frequency and severity of natural catastrophes is leaving vulnerable groups of society at greater risk of economic ruin and is rapidly shifting public sentiment toward the promotion of environmental and economic resilience. This has led to institutional and retail investors developing a strong predilection for investments that promote environmental sustainability. I have followed this research stream along two different directions.

 

‘Green Bonds’ have emerged as a popular ‘green’ investment vehicle – they are, according to the Climate Bonds Initiative, debt instruments that are “almost entirely linked with green and climate-friendly assets or projects”. They have grown quickly. Since first being released by publicly traded firms in 2013, they have gained a 4% share of total corporate bond proceeds. The fervent demand for large-scale ‘green’ products raised questions on whether markets were behaving efficiently. We investigated this phenomenon a little closer, by looking at stock price activity amongst firms who announced an upcoming issue of green bonds. Using different subsets of financial data, we looked at the dynamics and predictability of firm-level returns.

 

Two interesting findings came out of this research. First, investors, on average, viewed the issuance of green bonds favourably – first-time issuers tended to see a boost in stock prices. Secondly, and more importantly, we found that stock price anomalies were found to be predictable by Neural Networks, but not by more traditional means of examination (Linear Regressions). Our research provided further evidence that i) new financial instrument can introduce inefficiencies, and ii) deep learning techniques can have a place at the table in finance.

An ongoing research effort involves leveraging alternative data streams like satellite imagery to investigate the geospatial sensitivity of stock markets to catastrophic climate events. Understanding how stock markets move following climate disasters can unlock key insights on economic responses to climate disasters, which can:

 

1. Identify the climate risks that elicit the strongest reaction from investors, based on their location and exposure to specific risks

2. Establish the link between business model resilience to climate change (supply chain reliance, etc.), and stock price movements during climate events.

 

This latter research effort is being developed with the anticipation that it can inform sustainable corporate and public policy actions in the aftermath of climate disasters.

RELEVANT WORKS

• Shannon, D. and Sheehan, B., – . Anticipating Equity Investor Reactions to Green Bond Announcements. Submitted for Publication