INSIGHTS Opinion

Hi there! I’m Mabelle and I’m an AI Researcher at Arabesque AI working in research and development. I specialise in Natural Language Processing (NLP), and spend most of my research time on analysing social media data. During my PhD, I extracted discrete emotions from historical tweets and used them to identify Twitter users at risk of depression. At Arabesque AI, I now focus on how we can estimate future stock price movements using Twitter data. In this post, I will walk you through how this could be achieved, using Twitter data for an anonymised company.
by Dr. Mabelle Chen

With the revolutionary growth of social media, the use of big data has become the latest trend for researchers analysing stock market movements. Using techniques from NLP, sentiment analysis has been the dominant method of extracting features from such data sources. A quick search of “stock market prediction Twitter” on Google Scholar will show that 9 out of 10 papers have either “sentiment analysis” or “mood” in the title, demonstrating a ubiquity of sentiment analysis in NLP applications. See for example Bollen et al. (2011), Mittal et al. (2011), Yu et al. (2012), Nguyen and Shirai (2015), and Sahana et al. (2019). The concept of using sentiment analysis to predict stock price movements has its origins in behavioural economics. According to Nofsinger (2010), the level of optimism or pessimism in a society affects the decisions made by consumers, investors, and corporate managers. This has an influence on aggregate investment and business activity, which suggests social mood can help gauge future financial and economic activities. Hence, many researchers seek to predict the movement of the market using the dynamics of companies, economic scenarios, and public moods.

However, is sentiment the only meaningful feature that one can extract from such data? The answer is definitely no. In this post, I explore what other information and features can be extracted from tweets and how effective these additional features are, in conjunction with sentiment, for estimating future stock price movements.

This blog is split into four sections:

• Features: I start by introducing a number of features that can be extracted from Twitter data and align to these three categories:

  1. Basic Features
  2. Twitter Platform Features
  3. Content-based Features

• Prediction: I then experiment with these features to assess how they can be used to predict the movement of four stock targets.

• Explanation: Next, I use model interpretation to examine how these features contribute to each prediction task.

• Conclusion: Finally, I share my conclusion of how platform-specific and content-based features perform, in comparison with sentiment.

Features: So, what can we really measure from tweets?

While extracting sentiment from tweets is fairly simple, there is actually a wealth of information hidden in each one. In this section, I delve into all the different types of features that can be extracted from these tweets, some of which could prove useful for modelling purposes. For the demonstration of this post, I studied one particular company as an example, referred to as Company A. I used tweepy (a Python wrapper for the Twitter API) to collect public tweets that mentioned this company from 26th November 2019 to 20th July 2020. In total, 85,490 tweets were collected, covering 242 days, and the distribution of these tweets is presented in the chart below. The tweets were grouped on a daily basis to create a set of aggregate features for every day, as outlined in this section.

Before describing these features, it is important to stress that all of the features are snapshots taken at the end of each day. For every tweet, the number of likes and retweets might continue to increase every day. If snapshots are not taken, the data will contain information from the future. This common pitfall in machine learning is known as data leakage and as our data comes as a time series, it is absolutely crucial that we do not make this mistake for future prediction. Let’s now explore the features which can be generated for modelling purposes, as outlined in the diagram below.

1. Basic Features

   To start, some simple statistics can be extracted fairly easily such as the volume of tweets and the average length of tweets each day. You can always get your creative juices flowing and define more measures in this category. The distributions of each feature for the entire dataset are shown in the subsequent plots below.

   

2. Twitter Platform Features

   Twitter offers a number of functions for online users to share content and express themselves. These platform-specific functions can be used as features. For instance, from the use of hashtags, two measures can be created by counting 1), the number of unique hashtags used and 2), the total number of hashtags used. Since hashtags are used for tagging the subject or topic of a tweet, these features describe how many specific subjects are discussed in a day and the volume of those subjects.

   

   The same procedure can be followed for user mentions to obtain the number of unique mentions, and the total number of mentions which describe the volume of user interactions through tweets, on a given day.

   
   

   Another important Twitter function is the retweet. By extracting the retweet volume and its ratio to all tweets on a given day, I can capture whether a trending tweet or topic has gone viral, which increases its likelihood to have a social impact. To encapsulate this information, I calculate the average number of retweets and the ratio of retweets to all tweets for each day.

   
   

   Similarly, shares of an external link (in the form of a URL) or likes of tweets carry information about what content has gained the most public attention on a given day. To capture this information, I calculate the percentage of tweets containing URLs to all tweets on a given day as the URL ratio and the average number of likes per tweet for each day.

   

3. Content-based Features

   Let’s now dive into the actual content of tweets and apply NLP techniques to the text. When we read a piece of text, we usually focus on the entities or subjects that are being discussed, what topics are being covered, and the opinion or sentiment that the author is trying to convey. This is automatically processed by our brains. NLP techniques allow machines to mimic the same function.

   • Named entities mentioned in tweets

     Named entities (NEs) are a range of pre-defined categories mentioned in unstructured text, such as a person’s name, organisations, locations, time expressions, quantities, monetary values, and percentages. The task of identifying, predicting, and extracting these NEs is known as Named Entity Recognition (NER). To demonstrate how this works, imagine I post the following tweet: “Last week, I met Tim at the London Stock Exchange in London”. As seen in the next image, NER is able to categorise the content of this tweet into the NEs described in the table below.

     

     From this, I can begin to understand the actual content of a tweet. Using NER, I can create features that describe what type of subjects are discussed. These different entity types might have different impacts for a specific company.

     TYPE	DESCRIPTION
     Date	Absolute or relative dates or periods.
     Event	Named hurricanes, battles, wars, sports events, etc.
     GPE	Geopolitical entity i.e. countries, cities, states.
     Location	Non-GPE locations, mountain ranges, bodies of water.
     Money	Monetary values, including unit.
     NORP	Nationalities or religious or political groups.
     Organisation	Companies, agencies, institutions, etc.
     Percentage	Percentage, including ”%“.
     Product	Objects, vehicles, foods, etc. (Not services.)
     Person	People, including fictional.

     With the NER tagger from spacy (a Python package for NLP), a total of 20 entity types are recognised from our daily tweets. I pick some common ones in the table below that seem reasonable to experiment with. For each entity type, I accumulate the counts from tweets on the same day and create 10 NE features for each day.

     

   • Topics / Clusters

     To capture what the public talks about on a given day, topic modelling or clustering can be employed to separate the tweet stream into smaller and more specific “sub-streams”. From these sub-streams, you can create more complicated features and models. In this category, financial event detection on Twitter alone is a popular and fast-growing research area. However, for this demonstration, I use a simpler method to extract features. Without going into too much detail, I generate term frequency–inverse document frequency (tf-idf) vectors for each tweet and feed them into DBSCAN to identify the number of clusters. For all tweets (with duplication i.e. retweets), I allocate each tweet to its cluster and calculate the ratio of these tweets to all tweets. These features describe how many mainstream topics are expressed by the Twitter public on a given day and the proportion of engagement on these topics.

     

   • Sentiment

     There are a number of packages for producing the sentiment score from text. Rather than locking ourselves into a specific package, let’s average the scores generated by two popular sentiment analysis packages, afinn and vader. Each of these two sentiment scores are scaled to the range $[-1, 1]$, where $0$ represents a neutral sentiment, and $(0, 1]$ and $[-1, 0)$, represent a positive and negative sentiment, respectively. The final scores are normalised by the length of the tweet (word count) and averaged over tweets on the same day.

     

Prediction: How do the features perform?

So far, I have generated 23 daily features from tweets collected for Company A, which is a 238 (days/records) x 23 (measures/features) matrix. For this study, let’s define some classification target labels that I can attempt to predict with these features. I define four binary classification labels that denote whether the 1) adjusted closing price, 2) daily return, 3) trading volume and 4) daily volatility of a stock will increase by some threshold over the next day. Mathematically, this can be denoted as sign $\Delta Z$. With these four targets, I experiment with a simple binary classification model.

For all available dates in the data set (26th November 2019 to 20th July 2020), I calculate the rolling mean of features from date $t$ to $t-n$ to smooth noisy fluctuations, where the number of days $n$ is a hyperparameter. This feature set ($X$) is paired with each of the four target labels for the next day $t+1$ ($y$) as the dataset for classification experiments. The first seven months of the dataset (Nov 2019 – May 2020) are used for training, and the remaining two monthes (Jun and Jul 2020) are used for testing and evaluating the effectiveness of the features. I choose a simple logistic regression model (from the machine learning package scikit-learn) for this task in order to make the performance rely more on the features than the learning model.

This process was done for each $n$ up to $n=14$ days and each of the four target labels. The pictures above show the classification performance over $n$, measured by three performance metrics: AUC (area under the receiving operating characteristic), classification accuracy and $f_1$ score. From these results, I observe that the performance of the models is generally better for larger windows except for the daily return and volatility.

Explanation: What features mattered?

To examine how features contribute to the prediction, I generate the SHAP values for each classifier. SHAP is a game-theoretic approach to understand the impact that each feature has on a model. Overall, the features have a different effect on estimating different targets. A number of features are shown to carry more predictive information than sentiment score. What this result indicates to us is that you can do much more than just performing sentiment analysis on this dataset.

Conclusion

Based on the above, our analysis suggests that sentiment score is not necessarily the most important feature for stock price modelling. From this feature engineering experiment, I have managed to create 23 features, which can be useful to evaluate the performance of stocks. The main conclusion is that there are always other ways to improve our forecasting, whether it be additional data, features, analysis or experiments. So what can Twitter really tell us about stock prices? The simple answer is a lot more than sentiment analysis which is what the literature suggests. Alternatively, perhaps we should also ask another question which is, what more can we do with this realisation and how do we make our study more meaningful? The possibilities are endless.

INSIGHTS Opinion

The COVID-19 crisis has posed a number of severe challenges for businesses, from reacting to the outbreak, preparing for a potential recession, anticipating an eventual rebound in demand and placing bets against the post-crisis landscape. But it also provides an opportunity for organizations to step back and assess their approach to strategy and their strategic capabilities. As the context in which businesses operate becomes more dynamic and unpredictable, driven by the pace of technological change and a high degree of interconnectedness, we should expect other shocks of a similar nature moving forward, whether the trigger comes from biological pathogens, cyberattacks, market crashes, or another sources. Some will be exogenous to the business world, but some will be endogenous.

How can companies be better prepared for when those shocks occur? We see 10 strategic lessons emerging from the current crisis:

1. Think in multi-level systems for highly interconnected problems. Companies are embedded in markets, which are embedded in highly interconnected economies and societies, which are in turn embedded in natural ecosystems and the biosphere. In such nested complex adaptive systems, disturbances often cascade up from lower to higher levels and back down again, reshaping the whole system in the process. COVID-19 started as a local outbreak, which many believed would be contained in China. However, by adopting a systems perspective, forward-thinking leaders, forewarned by prior epidemics, might have seen that there was a strong chance that it could spread globally — with cascading effects on economies, markets, and companies. Systemic risk is a common feature of highly interconnected systems, from banking systems to infectious diseases and beyond, begging a systemic approach.

2. Design and manage for resilience. During stable times, companies tend to compete by building scale and static efficiency. From this standpoint, redundant resources and capabilities could be seen as wasteful. However, redundancy is one of six characteristics that we have identified that increase the resilience of natural and social systems. The others are: heterogeneity (a diversity of perspectives and approaches), modularity (creating “firebreaks” to prevent whole system collapse), adaptability (the ability to flex designs in changing circumstances using a process of variation, selection and amplification), prudence (stress testing for plausible tail risks) and embeddedness (coherence with higher-level systems like society and nature). In the case of COVID-19, we see that organizations that failed to build resilience, such as governments that lacked reserves of critical health-care equipment or companies with distressed balance sheets, have much more difficulty responding to the crisis.

3. Create a sense of urgency and avoid complacency. Even after the coronavirus started spreading globally, many countries delayed ramping up testing and adopting mitigation measures, and as a result the outbreak spread and intensified. However, some countries that had experienced prior coronavirus outbreaks, such as Singapore (SARS) and Korea (MERS), were less complacent and intervened more rapidly and forcefully. Many companies found that while they had a “crisis response plan” on paper, they had never used or simulated it, so it was difficult to actually implement. To avoid complacency in future crises, leaders should instill a sense of vigilance and urgency in their organizations by, among other measures, conducting “war games” to create mental and physical preparedness for a range of possibilities.

4. Avoid communications gridlock. Once they eventually grasp the significance of a crisis, many organizations become hyperactive and gridlocked by incessant, ever-changing instructions cascading up and down the hierarchy. There are of course benefits to sharing information, but there are also costs: communication takes time away from the real work that needs to be done, over-communication drowns out critical messages, and the agility of the organization can be diminished. This is an example of a larger issue that pervades many organizations: new instructions, processes or structures get built but few are ever removed, so complexity tends to increase over time. In the case of crisis communications, leaders should employ the military principle of Commander’s Intent (auftragstaktik), focusing on communicating key facts, principles and objectives, and allowing the rest of the organization to decide on appropriate tactics, informed by the local circumstances they face at the time. Effective decision-making requires finding the right balance between leadership and collective action.

5. Match your strategy to your environment. Classical strategies that depend on deliberate, episodic planning cycles, such as those adopted by most governments and businesses, can be effective in stable environments. However, the COVID-19 crisis is extremely unpredictable and fast-moving, due to unknown characteristics of the virus and the exponential trajectory of infections. As a result, many organizations found they needed to use an adaptive strategy in rapidly changing circumstances, and to accelerate decision making accordingly. Furthermore, as the crisis recedes, they will need to adopt shaping and visionary strategies to influence and exploit the post-crisis landscape. Each style constitutes a distinct approach to problem solving and requires very different metrics, processes, capabilities and leadership styles. Companies increasingly need to choose the right approach to strategy at the right time for each part of their business. To effectively implement multiple approaches to strategy in this way, they will need to master the art of strategic ambidexterity.

6. Operate on multiple timescales simultaneously. In early stages of the crisis, companies focused primarily on reacting to immediate threats. However, the outbreak also surfaced other challenges and opportunities: preparing for a potential recession in the near-term, taking advantage of a potential rebound in the medium-term, and eventually reimagining offerings and business models for the post-crisis world. Many companies are learning that they cannot wait to tackle these challenges sequentially, because each requires significant mental and physical preparation — rather, they have to consider multiple timescales simultaneously to both survive and position themselves for the future. The clock speed of most organizations is determined by the annual planning cycle. But at a time when strategically relevant timescales are being stretched from the algorithmic (milliseconds) to the planetary (decades), they need to build the capability to operate at multiple clock speeds.

7. Compete on the rate of learning. The pace of history and strategy is not linear. Sometimes there are long stretches of time when little of strategic significance happens. At other times, every second counts. In a quickly changing, interconnected digital world, with access to the rapid pattern detection capabilities of machine learning, organizations can and need to learn faster. The need is further amplified in rapidly moving crises like COVID-19. Companies increasingly need to compete dynamically and cultivate the capability to learn rapidly. Traditional measures of an economy’s or company’s activity, such as GDP statistics and earnings reports, are far too infrequent and lagging to be of use during the COVID-19 crisis. To understand how activity is changing during the outbreak and see hints of the emerging post-crisis future, organizations need to access and analyze high frequency, granular data, such as daily information on specific products or sub-categories. Digital pioneers that have built massive data ecosystems, and the analytical capabilities to learn from them on a continuous basis, are advantaged in this regard. But it’s not just a technological matter: companies need to build hybrid learning organizations that combine human ingenuity and machine learning in order to compete effectively.

8. Find advantage in adversity. When the economic environment gets challenging, companies tend to act defensively. However, 14% of companies across sectors increase both growth and margins during downturns. As a result, competitive divergence increases during recessions. The companies that emerge stronger from a downturn tend to take a long-term perspective and treat the crisis as an opportunity. Benchmarking suggests that while the majority of companies are focused on reacting to and managing the current crisis, some are seeing and executing against emerging longer term opportunities. For example, Apple made several acquisitions during the heart of the crisis, leveraging its strong cash position to take advantage of depressed valuations.

9. Compete on imagination. There is no tried-and-tested playbook to tackle an unprecedented crisis like COVID-19. And in a strategic sense there could not be, since the impact on each company will be largely determined by its ingenuity and ability to see and shape new possibilities. History shows that new attitudes and patterns of demand emerge during a crisis, prompting many innovations, but the spoils accrue disproportionally to imaginative pioneers. Imagination is often the first victim of a crisis, but it is an essential ingredient for long-term success. Imagination is not, as is often believed, mainly about serendipitous individual inspiration — it can be developed and cultivated as an organizational capability in a structured manner.

10. Shape collaborative solutions. COVID-19 is a global crisis that touches nearly all aspects of society, and solving it will require a collaborative response across business ecosystems, sectors and nations. Atomistic competition within current governance and regulatory frameworks will not get the job done. When confronting global issues, such as pandemics and climate change, governments and business leaders alike will need to build and shape coalitions for collective action at a global scale. This is necessary both for society as a whole to thrive, and to preserve the viability and legitimacy of the canvas upon which business operates. Business ties across nations create the empathy and connection that can facilitate broader collaboration. In addition, businesses are highly effective problem-solving entities and have a crucial role to play in tackling our common problems. This agenda will, however, require innovations in how we lead, collaborate, govern and collectively mobilize.

About the Authors

Martin Reeves is a managing director and senior partner in the San Francisco office of Boston Consulting Group and the Chairman of the BCG Henderson Institute.

Simon Levin is the James S. McDonnell Distinguished University Professor in Ecology and Evolutionary Biology at Princeton University.

Georg Kell is Chairman of Arabesque, an ESG Quant investment firm, and founder and former head of the UN Global Compact.

Kevin Whitaker is the head of strategic analytics at BCG Henderson Institute.

Saumeet Nanda is a consultant in the San Francisco office of Boston Consulting Group and an ambassador to the BCG Henderson institute.

Read the original article here.

INSIGHTS Opinion

Georg Kell explores why human wellbeing and the health of the planet are interconnected, and key lessons we can learn from the Coronavirus pandemic. This article was originally published in Forbes.

Neither military power nor wealth can stop the destructive global spread of COVID-19, a tiny member of the Coronavirus family. Its full human impact and economic cost will not be known for months to come. The virus is only now spreading amongst the most vulnerable populations, the millions who are cramped into refugee camps, and the hundreds of millions who live in city slums or in poverty without proper sanitation or medical support. As the pandemic is unfolding, it is revealing human vulnerabilities and showcasing the importance of good leadership and well-functioning, universal social and health care systems. 

While the current focus is on responding to the pandemic and on coping with its immediate effects, the lessons we will collectively learn from this crisis are equally if not more important, as we know that the next global crisis – the climate crisis – is already well under way, building up its destructive potential around the globe. This is of particular relevance for the younger generations. They will inherit the political and economic systems that are now being reshaped in response to the COVID-19 pandemic and their future is being mortgaged with enormous debt as governments are mobilizing unprecedented stimuli packages to avoid a deep recession.  

There are at least four lessons we should learn from the pandemic: 

1) Human history and natural history can no longer be separated – human health and the health of the planet go together 

“Mother nature is striking back, and humans are caught on their back feet,” is how a senior finance executive recently summed up the pandemic. Indeed, the pandemic should above all be a wakeup call that our wellbeing is closely tied to the health of the planet. Despite scientists’ warnings about the high risk of animal-borne infectious diseases, we continue to destroy natural habitats. The evidence of the destructive human impact on the natural environment from water to soil to the air, and its negative impact on human health and wellbeing, is overwhelming. Yet, we find it difficult to change course. Despite the many warning signs, humans have become a geophysical force as we continue to destroy, pollute and poison on a massive scale the very foundation we depend on for survival and wellbeing. Every year we dump over 30 billion tons of carbon into the atmosphere. We destroy entire animal and plant species at an alarming rate. We have cut down forests everywhere. We poison the soil and the water, and our garbage covers the floors of the oceans. And yes, every year, we kill over 100 billion animals to feed our carnivorous appetites. Our industrial-era mindset of ‘growth at any cost’ has become a recipe for self-destruction.   

We have long known that markets cannot succeed in failing societies. Now we must learn that healthy societies and markets depend on the health of the natural environment. We know in principle what needs to be done and we have the means to do it: shifting the goalposts and the incentives that put a premium on clean and healthy growth instead of subsidizing the destruction of the environment, and putting decarbonization of economic activity and material reuse center stage, while restoring natural habitats and forests. With the enormous stimuli packages now being rolled out, we have a unique opportunity to change course. We can respond to the current crisis while at the same time building a healthier, greener and safer future. Going back to business as usual would be short-sighted and self-destructive – we would respond to one crisis by fueling the next one. Green and inclusive growth is no longer a nice thing to have. It is the only way to prevent the next crisis which, according to scientists, could well turn out to have an even greater destructive impact than COVID-19.   

2) Prevention is better than cure

– we must learn to listen to science 

The pandemic is a strong reminder that ignoring science carries steep costs. Scientists have long warned about infectious diseases, especially since the recent outbreaks of Ebola, SARS and the bird flu. Only last September did the WHO’s Global Preparedness Monitoring Board issue an authoritative report urging governments to better prepare. Alas, their call was widely ignored. Scientists’ consistent and overwhelming warnings about the human impact on the global climate, on soil and water, and on plant and animal diversity have equally been ignored.  

 In our era of deliberate misinformation, fake social news and divisive political propaganda, we now have an opportunity to rediscover science as a reliable arbitrator and a guide to informed decision making. COVID-19 has already helped to elevate trust in credible mainstream scientists and thereby reversed the decade-old trend of eroding trust in established institutions. According to a recent New York Times article, the voice of science has become indispensable to inform policymakers and the public on how to deal with the pandemic. The fact that scientists collaborate across borders, even in the light of political divides, adds further credentials to their efforts, and their pursuit of the public good often trumps narrow interests. Moving forward, scientists should be encouraged to play a greater role in public debates and policymaking and the public should be encouraged to take a greater interest in science and support their work. 

3) Global threats need global collaboration 

Former UN Secretary General Kofi Annan referred to climate change, diseases and terrorism as ‘problems without passports’ that cannot be stopped at the border and that can only be tackled if we cooperate. The premium for cooperation is growing as global threats are becoming national security threats. A virus can’t be stopped at borders and climate change does not respect national sovereignty. Yet, sadly, international cooperation has given way to strategic rivalry and fragmenting power blocks. The Paris Agreement of 2015, which had China’s and the USA’s cooperation, seems like from another era. The United Nations’ recent call for cooperation to deal with the pandemic was hardly noticed and its most important organ, the Security Council, is “missing in action”. Some political observers fear that the pandemic may accelerate existing divergences, supercharging nationalism and undermining free trade even further, leading to a world in even greater disarray. Indeed, ancient power concepts and myths of the past still set the tone and have not evolved since Thucydides, despite the growing interdependence of humanity and the many lessons history has taught us. Policymakers seem to have no grasp of “global public goods” and their importance for national security.   

Over time nature will force our hands, whether we are prepared or not. The idea of a “common enemy” may sound outlandish to many at this point, but COVID-19 demonstrates that conventional power concepts are no longer useful when dealing with global threats. The notion of “global stewardship” and the imperative to build stronger collaborative bonds across and between nations will ultimately become a necessity. Human security needs more than military deterrence: it needs a new focus on good stewardship for the life-supporting services that nature provides and a collective willingness to improve the state of affairs everywhere. No country is prepared for the next pandemic if the rest of the world is not. And no country can stop the impact of climate change alone. COVID-19 gives us an opportunity to change course in this direction. Heeding UN Secretary General Antonio Guterres’ call to better coordinate and mobilize efforts to deal with the impact of the pandemic in less developed countries would be a good first step for the better.  

4) The pivotal role of the private sector  

Commerce has long acted as a bridge-builder between nations by connecting cultures and people, not through military power, but by spreading knowledge, mutual understanding and economic benefits. The world will remain deeply interconnected also in the post-COVID-19 era, and economic interdependence will remain the most viable pathway to secure peaceful co-existence and prosperity. In a fragmenting world where policymakers seem to have forgotten the lessons of history and largely ignore common interests that are shared by all of humanity, the private sector is playing an ever more critical role.  

While coping with the pandemic in a struggle to survive, many well-managed companies have put the health and safety of their workers first while cooperating and working with clients and customers across borders and along supply chains. Many companies have retooled their manufacturing capacities to supply medical supplies and have mobilized community-based efforts to cope with the pandemic. One such example is Volkswagen, which in late January already donated medical supplies to Hubei Province of China. China in turn is now providing massive supplies to Germany. Leading technology companies are collaborating to develop “contact apps” and pharmaceutical companies have initiated unprecedented cooperation in the race to develop vaccines.  

Good corporate citizenship practices are much needed to complement government efforts. The idea and practice of corporate sustainability and its financial equivalent – sustainable investing – is now playing an important role in coping with the crisis, affirming once again that values and purpose are the enduring features of resilient organizations. Equally, if not more important, is the fact that corporate sustainability and responsible investing now also serve as counterweights to the dark forces of economic nationalism and protectionism.    

The sustainability movement will gain further relevance in the post-COVID-19 era. For corporations and investors, the need to align strategies with a broader purpose that speaks to the needs of society will be the key to growing and building trust. The pandemic has put a spotlight on human vulnerability and the fact that human safety and the health of the natural environment go hand in hand. This may well reinforce existing consumer trends towards healthier and more sustainable lifestyles. Environmental priorities are bound to gain greater strategic relevance over time and far-sighted executives will use the current crisis to accelerate decarbonization and to resource-efficiency measures. And arguably most important of all, the pandemic has acted as an accelerator for everything digital. Innovation and new business models will enjoy a premium and will give a boost to automation, resource efficiency and decarbonization, touching all segments of the economy. Moreover, digitalization and better smart data analysis are the fuel that drives ESG investing. Early evidence is already suggesting that ESG investing is gaining greater relevance in the light of the pandemic. Moving forward, the convergence between corporate sustainability and sustainable investing offers unprecedented opportunities to renew markets from within. 

Are we capable of learning?  

While coping with the crisis, we have an opportunity to rediscover basic values of humanity and the bonds that connect us. We now have it in our hands to lay the foundation for a safer, healthier and cleaner life on planet earth. We have the technology and the means to come out stronger if we understand that human wellbeing and the health of the planet are two sides of the same coin. Now is the time to retire old dogmas and to give way to a fresh start. 

Georg Kell is Chairman of Arabesque, and the founding Executive Director of the UN Global Compact.

INSIGHTS Opinion

By Georg Kell

Responsible investing is widely understood as the integration of environmental, social and governance (ESG) factors into investment processes and decision-making. ESG factors cover a wide spectrum of issues that traditionally are not part of financial analysis, yet may have financial relevance. This might include how corporations respond to climate change, how good they are with water management, how effective their health and safety policies are in the protection against accidents, how they manage their supply chains, how they treat their workers and whether they have a corporate culture that builds trust and fosters innovation.

The term ESG was first coined in 2005 in a landmark study entitled “Who Cares Wins.” Today, ESG investing is estimated at over $20 trillion in AUM or around a quarter of all professionally managed assets around the world, and its rapid growth builds on the Socially Responsible Investment (SRI) movement that has been around much longer. But unlike SRI, which is based on ethical and moral criteria and uses mostly negative screens, such as not investing in alcohol, tobacco or firearms, ESG investing is based on the assumption that ESG factors have financial relevance. In 2018, thousands of professionals from around the world hold the job title “ESG Analyst” and ESG investing is the subject of news articles in the financial pages of the world’s leading newspapers. Many investors recognize that ESG information about corporations is vital to understand corporate purpose, strategy and management quality of companies. It is now, quite literally, big business. But what explains the remarkable rise of ESG investing and what does this mean for the future?

The story of ESG investing began in January 2004 when former UN Secretary General Kofi Annan wrote to over 50 CEOs of major financial institutions, inviting them to participate in a joint initiative under the auspices of the UN Global Compact and with the support of the International Finance Corporation (IFC) and the Swiss Government. The goal of the initiative was to find ways to integrate ESG into capital markets. A year later this initiative produced a report entitled “Who Cares Wins,” with Ivo Knoepfel as the author. The report made the case that embedding environmental, social and governance factors in capital markets makes good business sense and leads to more sustainable markets and better outcomes for societies. At the same time UNEP/Fi produced the so-called “Freshfield Report” which showed that ESG issues are relevant for financial valuation. These two reports formed the backbone for the launch of the Principles for Responsible Investment (PRI) at the New York Stock Exchange in 2006 and the launch of the Sustainable Stock Exchange Initiative (SSEI) the following year.

Today, the UN-backed PRI is a thriving global initiative with over 1,600 members representing over $70 trillion assets under management. PRI’s role is to advance the integration of ESG into analysis and decision-making through thought leadership and the creation of tools, guidance and engagement. The SSEI, supported by the Geneva-based UNCTAD, has grown over the years with many exchanges now mandating ESG disclosure for listed companies or providing guidance on how to report on ESG issues. However, despite its rapid growth into the mainstream, the rise of ESG investing has been neither smooth nor linear.

Institutional investors were initially reluctant to embrace the concept, arguing that their fiduciary duty was limited to the maximization of shareholder values irrespective of environmental or social impacts, or broader governance issues such as corruption. Incredibly, such arguments are still being made. But as evidence has grown that ESG issues have financial implications, the tide has shifted. In many important markets, including the U.S. and the EU, ESG integration is increasingly seen as part of fiduciary duty. See, for example, Al Gore’s update on relevant developments.

Another major barrier has been a lack of data and the necessary tools to get a handle on the fragmented and incomplete information available. However, corporate disclosure on ESG issues has steadily improved since the launch of the Global Reporting Initiative (GRI) in 2000. Today, 80% of the world’s largest corporations use GRI standards. More recently, the International Integrated Reporting Initiative (IIRC) and the US-based Sustainability Accounting Standard Board (SASB) have helped to advance industry sector-specific reporting and its relevance for investors. Overall, the market for ESG information is maturing and quality, while still imperfect, is getting better all the time. And new technology based on machine learning and big data can already unlock valuable insights and offer easy ways to apply ESG data in addition to conventional financial information.

The steady growth of ESG investing was greatly accelerated around 2013 and 2014 when the first studies were published showing that good corporate sustainability performance is associated with good financial results. Work by academics such as George Serafeim, Bob Eccles and Ioannis Ioannou shows the importance of ESG information for assessing corporate risks, strategies and operational performance.

The idea that investors who integrate corporate environmental, social and governance risks can improve returns is now rapidly spreading across capital markets on all continents. In Europe, for example, a critical mass of pension funds and insurers have started to award new business exclusively to asset managers with ESG capabilities. The global investor community has developed a variety of methods for optimally integrating ESG information, such as outlined in A Practical Guide To ESG Integration for Equity Investing). Among the many ESG factors that are viewed as having financial relevance are especially those related to climate change. The reason for this is that climate change is no longer a distant threat on the horizon, but one that is here and now, with multi-billion-dollar economic consequences. Many investor initiatives are now pushing for de-carbonization and the Task Force on Climate-related Financial Disclosures (TCFD) has given much impetus for improving risk preparedness and, by implication, de-carbonization actions.

Cynics may argue that responsible investing is just a fad. But a closer look at the forces that have driven the movement over the past 15 years suggests otherwise. Firstly, technology and the rise of transparency are here to stay. Gathering and processing data will become ever easier and cheaper. Smart algorithms will increasingly allow for better interpretation of non-traditional financial information which seems to be doubling in volume every couple of years. Secondly, environmental changes, in particular climate change, will with scientific certainty put a growing premium on good stewardship and low carbon practices as natural assets will appreciate in value over time. And thirdly, people everywhere are increasingly empowered by technology. ESG investing allows them to express their own values and to ensure that their savings and investments reflect their preferences, without compromising on returns.

The rise of ESG investing can also be understood as a proxy for how markets and societies are changing and how concepts of valuation are adapting to these changes. The big challenge for most corporations is to adapt to a new environment that favors smarter, cleaner and healthier products and services, and to leave behind the dogmas of the industrial era when pollution was free, labor was just a cost factor and scale and scope was the dominant strategy. For investors, ESG data is increasingly important to identify those companies that are well positioned for the future and to avoid those which are likely to underperform or fail. For individuals, ESG investing offers the opportunity to vote with their money. And for policy makers, it should be a welcome market-led development that ensures that the common good does not get lost in short-term profit making at any cost.

Today, ESG investing has matured to the point where it can greatly accelerate market transformation for the better. As corporations and investors experience growing influence and power, their actions and decisions increasingly shape the future. Provided that political framework conditions based on openness and global rules do not deteriorate further, market-led changes will act as a force for good on a truly massive scale.

INSIGHTS Opinion

Recent years have seen an increase in public climate change disclosures from companies due to increases in mandatory reporting policies, however many companies still do not publicly report their emissions. Despite this, investors are integrating climate scores into their investment decisions. How? Estimating emissions using models; the current climate rating system offers metrics for upwards of 10,000 companies.

This strategy prevents investors from accurately managing risk, as there is no way to differentiate between the companies that are reporting and taking the lead on climate action, and those that are not. Consequently, non-reporting, high emitting companies are not incentivized to report. Furthermore, insufficient disclosures indicate that companies may not have a full understanding of their impact. Companies may appear to be taking steps to reduce their impact on climate change, but without public scrutiny of the data, this cannot be verified.

In this webcast, Dr. Rebecca Thomas and Emily Matthews from Arabesque S-Ray speak about the current challenges and opportunities surrounding carbon data and its relevance to the investor community.

Download the webcast via FactSet to learn more (link)

INSIGHTS Opinion

Speech given by Mark Carney, Governor of the Bank of England

European Commission Conference: A global approach to sustainable finance, 21st March 2019

A New Horizon?

A few years ago, I spoke of the Tragedy of the Horizon – how the catastrophic impacts of climate change will be felt beyond the traditional horizons of most banks, investors and financial policymakers, imposing costs on future generations that the current one has no direct incentives to fix.1 Once climate change becomes a clear and present danger to financial stability it could already be too late to stabilise the atmosphere at two degrees.

The paradox is that risks will ultimately be minimised if the transition to a low-carbon economy begins early and follows a predictable path. But for markets to anticipate and smooth the transition to a 2-degree world, they need the right information, proper risk management, and coherent, credible public policy frameworks.

Today, catalysed by the COP21 Paris Agreement, and national policies such as the UK Government’s Clean Growth Strategy, some of these elements are coming into place, creating a potential path to break the Tragedy of the Horizon. But the task is large, the window of opportunity is short, and the stakes are existential.

In pursuit of that New Horizon, let me briefly discuss progress and prospects in three critical areas – reporting, risk and return.

First, reporting

Three years ago in response to a call from G20 leaders, the FSB began addressing the financial stability risks associated with climate change by ensuring the market had the right information to price climate risk and reward climate innovation. The FSB established the Task Force on Climate-Related Financial Disclosures (TCFD) led by businesses from a wide range of industries across the G20. Eighteen months later, the TCFD delivered to the Hamburg G20 Leaders Summit its recommendations for voluntary disclosures of material climate-related financial risks. Since then there has been a step change in both demand and supply of climate reporting.

On the demand side, current supporters of the TCFD include three-quarters of the world’s globally systemic banks, 8 of the top 10 global asset managers, the world’s leading pension funds and insurers, major credit rating agencies and the Big Four accounting firms.2 In total, these financial firms manage almost US$110 trillion in assets.

As a consequence, the incentives for companies to disclose and manage climate-related risks have increased dramatically. Moreover, climate change claimed its first S&P 500 bankruptcy last year,3 climate related shareholder resolutions spiked to 90 last year,4 investment managers controlling over 45% of global assets under management now back shareholder actions on carbon disclosure, and companies representing over 90% of all shareholder advisory services now support the TCFD.
Not surprisingly, the supply of disclosure is responding. Over 600 organisations, with a total market capitalisation of US$9 trillion, have endorsed the TCFD recommendations since 2017.

The TCFD’s September 2018 Implementation Report assessed, using artificial intelligence, some 1800 companies, and analysed in detail an additional 200 of the largest companies, drawn from eight representative sectors from across the G20.5

In both cohorts, the majority of companies were already disclosing information in their 2017 filings that aligned with one or more of the TCFD’s recommendations. This is commendable given companies only had six months to respond to the final TCFD recommendations, but more progress is needed.

In particular:

Financial implications are often not yet disclosed;

Disclosures are often in multiple reports making comparisons harder; and

Disclosure varies by industry and region, with higher percentages of European firms and higher shares of those on the climate frontline – such as the energy sector – disclosing more information aligned with the recommendations.

The next milestone will be the TCFD implementation report for the G20 Leaders Summit in Osaka, which should set out:

The growing momentum behind disclosure;

The types of disclosures that are most decision-useful for investors; and

Best practice examples, including examples of scenario analysis so that firms can test their strategic resilience to different climate outcomes.

The momentum behind TCFD’s voluntary disclosure is creating a virtuous circle by encouraging learning by doing. As companies apply the recommendations and investors increasingly differentiate between firms based on this information, adoption will continue to spread, disclosure will become more decision-useful and efficient, and its impact will grow.

As firms work to enhance their disclosures, they are being supported by various TCFD Preparers’ Forums from energy to finance.6 The TCFD will also continue to work with market participants to refine metrics so that they are consistent, comparable and decision-useful; and it will share best practices on the disclosure of risk management and governance.

In the future, disclosure will move into the mainstream, and it is reasonable to expect that more authorities will mandate it. IOSCO could play a constructive role in coordinating such mandates and in any event, the current iterative process of disclosure, reaction and adjustment will be critical to ensure that these eventual market standards are as comparable, efficient and effective as possible.

Second, risk analysis

The second step on the path to a new horizon is better climate change risk management.

Climate change creates both physical and transition risks.7

Physical risks arise from the increased frequency and severity of climate- and weather-related events that damage property and disrupt trade.

Transition risks result from the adjustment towards a lower-carbon economy. Changes in policies, technologies and physical risks will prompt a reassessment of the value of a large range of assets as costs and opportunities become apparent. The longer meaningful adjustment is delayed, the more transition risks will rise.

Climate risks also have a number of distinctive elements, which, in combination, require a strategic approach. These include their:

Breadth, as climate risks affect multiple lines of business, sectors and geographies;

Magnitude, as the full impacts of climate risks are large, potentially non-linear and irreversible;

Foreseeable nature;

Dependency on short-term actions given that the size of future impacts will, at least in part, be determined by the actions taken today; and

Uncertain time horizon which may stretch beyond traditional business planning cycles.

The nature of these risks means that the biggest challenge in climate risk management is in assessing the resilience of firms’ strategies to transition risks.

Part of the genius of the private sector-led TCFD is its recognition that disclosure needs to go beyond the static to the strategic. Markets need information to assess which companies can seize the opportunities in a low carbon economy and which are strategically resilient to the physical and transition risks associated with climate change.

The Bank of England has also become increasingly active in such assessments, consistent with our financial stability and prudential mandates.

As the supervisor of the world’s fourth largest insurance industry, we know that general insurers and reinsurers are on the front line of managing the physical risks from climate change. Insurers have responded by developing their modelling and forecasting capabilities, improving exposure management, and adapting coverage and pricing.8 In the process, insurers have learned that yesterday’s tail risk is closer to today’s central scenario.

Sadly with climate, history repeats not as a farce but as tragedy and with growing frequency.

For banks, the financial risks from climate change have tended to be beyond their planning horizons. The PRA’s survey of 90% of the UK banking sector, representing over $11trn of assets, found that these horizons averaged four years – in other words, before risks would be expected to be fully realised and prior to ambitious climate policies taking effect. 9

That notwithstanding, the PRA’s latest survey finds that almost three quarters of banks are starting to treat the risks from climate change like other financial risks – rather than viewing them simply as a corporate social responsibility issue.

Banks have begun considering the most immediate physical risks to their business models – from the exposure of mortgage books to flood risk, to the impact of extreme weather events on sovereign risk. And they have started to assess exposures to transition risks in anticipation of climate action. This includes exposures to carbon-intensive sectors, consumer loans secured on diesel vehicles, and buy-to-let lending given new energy efficiency requirements.

Informed by these findings, the PRA will soon publish its final Supervisory Statement for banks, insurers and investment firms.10 This statement will set out the PRA’s expectations regarding firms’ approaches to managing the financial risks from climate change, including with respect to:

Governance, where firms will be expected to embed fully the consideration of climate risks into governance frameworks, including at board level, and assign responsibility for oversight of these risks to specific senior role holders;

Risk management, where firms will need to consider climate change in line with their board approved risk appetites;

The regular use of scenario analysis to test strategic resilience; and

Developing and maintaining an appropriate disclosure of climate risks.

Recognising the need for industry to build capacity and to develop best practices, the PRA has established a Climate Financial Risk Forum, jointly with the FCA, to work with firms from across the financial system.11

The responses to our supervisory consultation reflect the urgency and significance of the issues. Perhaps for the first time in financial regulation, firms are both thanking their supervisors for raising an issue and pushing us to go further; with some asking for more prescriptive recommendations and others for mandatory disclosures.12

Certainly, while climate risk management is improving, there is more to do particularly when assessing strategic resilience.

For companies, that means conducting scenario analysis.

The TCFD 2018 Status Report found that non-financial industries (energy, transport, building and agriculture) were the most advanced at measuring strategic resilience, including some examples of scenario analysis.13,14

The TCFD review found that the financial sector is also moving toward enhanced strategic analysis. For example half of all insurance companies reviewed used the 2°C scenario, and the majority of banks described the potential impact of climate-related issues on their businesses.

However, the September TCFD report showed that while firms were starting to consider strategic resilience, few systematically conducted scenario analysis.

Indeed, the PRA has found that despite the sophistication of insurers in modelling climate risks, there are still gaps in their own risk management. The PRA is increasingly focused on cognitive dissonance in some insurers whose careful management of climate risks on the liability side of their balance sheets is not always matched by similar considerations on the asset side.

And the PRA’s banking survey last September found that, although almost three quarters of banks recognised the risks of climate change, only one in ten were taking a long term, strategic approach to them.

With that in mind, we expect firms to consider scenario analysis as part of their assessments of the impact of climate risks on their balance sheet and broader business strategy.

An important question is the form these scenarios should take. Climate scenarios aren’t forecasts, but data driven narratives that help companies think through different possible futures. The scenarios should be comprehensive, rigorous and challenging. The assumptions and methodologies in the models – such as the assumed global temperature rise, the energy mix, or whether the transition happens smoothly or abruptly – should be sufficiently transparent to allow for comparisons and external challenge. And finally, scenarios should be implemented consistently across the business, linking identification of risks and opportunities to both strategy and disclosure.

To do this, firms will need either to develop their own transition scenarios or build on commonly available models. The TCFD report signposts existing models that firms can use, and the PRA’s Climate Financial Risk Forum will work with industry to review tools and metrics, with the view to publishing reference scenarios and standard assumptions.15

For supervisors, assessing strategic resilience will require climate-related stress testing. This involves linking high-level data-driven narratives on the evolution of physical and transition risks to quantitative metrics to measure the impact on the financial system.

Next month, the PRA will ask UK insurers, as part of a market-wide insurance stress test, to consider how their businesses would be affected in different physical and transition risks scenarios.

Testing the banks, and possibly other participants in the financial system, with climate-change scenario stress tests would have two objectives:

To consider whether, across the financial system, financing flows are consistent with an orderly transition to the climate outcome set out in the Paris agreement. These long-term scenarios can facilitate discussions between firms and their clients about possible risks across different sectors and geographies; and

To consider whether the financial system would be resilient to shorter-term shocks – including a climate “Minsky moment” when climate risks materialise suddenly.These long and short-term risks are, of course, linked – any overall misalignment with climate goals increases the short-term risks from a disorderly transition, possibly caused by extreme weather events or abrupt shifts in climate policy. A system-wide stress test can help supervisors and climate policymakers judge the adequacy of the current transition and whether further actions could be expected.
As the Bank of England considers the timing and design of such a stress test, we are working with colleagues in the Network for Greening the Financial System (NGFS) to develop a small number of highlevel scenarios.16 And in our Climate Financial Risk Forum we will work with banks, insurers and asset managers to ensure these scenarios are rolled out effectively within their organisations. Together with our work on this year’s insurance survey, these initiatives will provide a basis for our future assessments of the system-wide exposure to climate risks.

The third and final area is return

A new horizon brings new opportunities.

The IEA estimates that the low-carbon transition could require $3.5trn in energy sector investments every year for decades – twice the rate at present. Under their scenario, in order for carbon to stabilise by 2050, nearly 95% of electricity supply will need to be low carbon, 70% of new cars electric, and the CO2 intensity of the building sector will need to fall by 80%.

With an estimated US$90 trillion of infrastructure investment expected between 2015 and 2030, smart decisions now can make sure that investment is both financially rewarding and environmentally sustainable. 16 The voluntary network was set up by 8 central banks and supervisors in December 2017 at the One Planet Summit, and has since grown to 29 members, representing countries accounting for nearly half of global emissions, and five observers. It is a voluntary, consensus-based forum whose purpose is to share best practices, contribute to the development of climate- and environment-related risk management in the financial sector and mobilize mainstream finance to support the transition toward a sustainable economy. The analytical work is split into three work streams and the research will be published in April 2019: WS1 microprudential/supervisory; WS2 macrofinancial; and WS3 Scaling up green finance.

Regulators and market participants are collaborating to facilitate cross-border investments in green infrastructure. The European Commission’s Sustainable Finance Action Plan is developing a classification system for sustainable economic activities, a harmonised green bond standard and methodologies for lowcarbon indices.17 The three major credit rating agencies have all integrated environmental risk and green certification into credit ratings. And international organisations such as the Climate Bonds Initiative (CBI) and International Capital Markets Association (ICMA) have developed definitional frameworks, certification and validation methods for green financing.18

This work is helping the green bond market to gather pace, with issuance quadrupling from $45bn in 2015 to $168bn in 2018.19 Last year also saw inaugural sovereign green issues from five countries.20

For investors, green bond markets offer stable, rated and liquid investments with long duration. For issuers, green bonds are a way to tap the huge US$100 trillion pool of patient private capital managed by global institutional fixed-income investors. The shift to the capital markets from banks will also free up limited bank balance sheet capacity for early-stage project financing and infrastructure lending.

Over the last two years, the City of London has been glowing green with sixteen renewable infrastructure funds with a value of $7bn listed on the LSE. The City has been the centre of a series of landmark global green bond issuances, from China’s first Green Covered Bond – the country’s first ever international issuance of a green bond – to the first green Masala Bond worth INR 20bn. In our view, such local currency green bonds will be particularly important to the climate transition in emerging market economies (EMEs).

However, while they are important catalysts, green bonds will not be sufficient to finance the transition to a low carbon future. They accounted for only 3% of global bond issuance in 2018.

Achieving the transition will require mobilising mainstream finance.

Advances in reporting and risk analysis are paving the way for investors to realise the opportunities in climate-friendly investment by re-orienting their focus to broader, more sustainable long-term value creation.

Such investment approaches are becoming increasingly common. There are now almost 2000 signatories, with over $80 trillion in assets under management, to the UN Principles for Responsible Investment (UN PRI), an international network of investors committed to considering ESG factors in their work.21

This swell of support is driven by the expectation that sustainable investment can generate excess returns in three ways.

First, companies that score well on ESG metrics could better anticipate future climate-related risks and opportunities. This makes them more strategically resilient and therefore able to anticipate, and adapt to, the risks and opportunities on the horizon, generating true alpha from ESG.

Second, strong ESG scores could signal that a firm is more naturally disposed to longer-term strategic thinking and planning. Climate disclosure is increasingly seen not only as necessary in and of itself, but also as informative about the extent to which companies are focused on long-term value creation.

And third, strong ESG firms may enjoy valuation premiums consistent with shifting investor preferences. Millennials, keenly focused on company values and sustainability, are set to inherit $24trn of wealth in the US alone over the next 15 years and will seek the investment opportunities to match.22 Already, assets are moving to ESG strategies at 20 per cent annual growth.23

A review of over 200 sources on ESG performance by Oxford University and Arabesque showed that in the overwhelming majority (88%) of companies that focused on sustainability, operational performance was improved, translating to higher cash flows.24

And meta-analysis of over 2000 studies confirms that the responsible, as well as the economic case for ESG investment is tangible. 90% of studies find that there is no penalty on return on ESG investment, and the majority suggest that focusing on ESG criteria generates a positive return.25

The outperformance of strong ESG companies is uncorrelated with underlying factors such as return on equity or capital employed, and reflects greater earnings stability and lower share price volatility. While “screening” – excluding poor ESG performers – is still the most common tool among investors, some research finds that a more proactive consideration of ESG factors may pay off. 26,27, 28

“Tilt” strategies, which overweight ESG stocks, and “momentum” strategies, which focus on companies that have improved their ESG rating, have outperformed global benchmarks for close to a decade.29

This suggests that there is more to well-regarded ESG companies than simply better management of downside risk.

Given this growing track record, companies are developing ways to better score ESG performance and invest accordingly. For example, Arabesque uses machine learning models to assess the performance and sustainability of companies, and stock selection strategies to tailor portfolios to a wide range of investor ESG preferences. This week BNY Mellon adopted such an approach motivated in part by the EU’s Directive on Pensions (IORP II).30 Earlier this year UBS launched a pilot project that will allow investors to rate how much weight they want to place on different ESG factors.31 And last month, BlackRock launched six new Exchange Traded Funds (ETFs) that combine an ESG uplift and a 30% reduction in carbon emissions.32 These sustainable building blocks can be substituted into many traditional portfolios, improving ESG scores and reducing greenhouse gas (GHG) intensity without sacrificing performance.

In the future, climate and ESG considerations will likely be at the heart of mainstream investing. Investors will tailor their investments and fulfil their fiduciary duties through: better quality and more widely available data on sustainability and performance; superior data analytics through the advent of AI and Machine Learning; and more informed judgements of strategic resilience.

Conclusion: a New Horizon

Financial policymakers will not drive the transition to a low-carbon economy. Governments will establish the climate policy frameworks, and the private sector will make the necessary investments.

Nonetheless, financial policymakers do have a clear interest in ensuring the financial system is resilient to any transition hastened by those decisions. Our role is to develop the frameworks for markets to adjust efficiently.

A market in the transition to a two-degree world is being built. It will reveal how the valuations of companies could change over time as climate policies adapt and carbon intensity declines.

It will expose the likely future cost of doing business, of paying for emissions, and of tighter regulation.

It will help smooth price adjustments as opinions change, rather than concentrating in a climate “Minsky moment”.

And it will allow feedback between the market and policymaking, making climate policy a bit more like monetary policy, with policymakers learning from markets’ reactions, and markets internalising policymakers’ objectives, strategies and instruments.

In this way, recent progress in disclosure, risk management and return optimisation is creating a path to a New Horizon. A virtuous circle is becoming possible where companies disclose more information, investors make better informed decisions, and sustainable investment goes mainstream.

But the speed with which this market develops will be heavily influenced by the coherence and credibility of climate policies. Finance will complement – and potentially amplify – but never substitute for climate policy action.

The policy frameworks with the greatest impact will be: time consistent (not arbitrarily changed); transparent (with clear targets, pricing and costing); and committed (through treaties, nationally determined contributions (NDCs), domestic legislation and consensus).

As countries build their track records and their credibility grows, the market will allocate capital to deliver the necessary innovation and growth and pull forward the adjustment to a low carbon future.

The more prolific the reporting, the more robust the risk assessment and the more widespread the return optimisation, the more rapidly this transition will happen, breaking the Tragedy of the Horizon.

Originally published by the Bank of England.

All speeches are available online at www.bankofengland.co.uk/publications/Pages/speeches/default.aspx

• References

1 Carney, M. (2015). Breaking the Tragedy of the Horizon. Available: https://www.bankofengland.co.uk/speech/2015/breaking-thetragedy-of-the-horizon-climate-change-and-financial-stability

2 Full list of current TCFD supporters available on: https://www.fsb-tcfd.org/tcfd-supporters/    

3 WSJ. (Jan 2019). PG&E: The First Climate-Change Bankruptcy, Probably Not the Last. Available: https://www.wsj.com/articles/pg-e-wildfires-and-the-first-climate-change-bankruptcy-11547820006

4 Horster, M and Papadopoulos, K. (2019). Climate Change and Proxy Voting in the U.S. and Europe. Available: https://corpgov.law.harvard.edu/2019/01/07/climate-change-and-proxy-voting-in-the-u-s-and-europe/

5 Task Force on Climate-Related Disclosures (TCFD). (2018). TCFD:2018 Status Report. Available: https://www.fsbtcfd.org/publications/tcfd-2018-status-report/  

6 For example the Oil and Gas industry group convened by the World Business Council on Sustainable Development and the Institute of International Finance for banks.

7 The other channel concerns liability risks. These stem from parties who have suffered loss from the effects of climate change seeking compensation from those they hold responsible. Such claims could arise well into the future, as the science and evidence of climate change hardens, though some are already taking action against companies on the grounds of failure to disclose the risks posed to their business models by climate change.

8 Prudential Regulation Authority. (Sept 2015). The impact of climate change on the UK insurance sector. Available: https://www.bankofengland.co.uk/-/media/boe/files/prudential-regulation/publication/impact-of-climate-change-on-the-uk-insurancesector.pdf   

9 Prudential Regulation Authority. (Sept 2018). Transition in thinking: The impact of climate change on the UK banking sector. Available: https://www.bankofengland.co.uk/-/media/boe/files/prudential-regulation/report/transition-in-thinking-the-impact-of-climate-change-onthe-uk-banking-sector.pdf?la=en&hash=A0C99529978C94AC8E1C6B4CE1EEC

10 Prudential Regulation Authority. (Oct 2018). Consultation Paper on Enhancing banks’ and insurers’ approaches to managing the financial risks from climate change. Available: https://www.bankofengland.co.uk/prudential-regulation/publication/2018/enhancingbanks-and-insurers-approaches-to-managing-the-financial-risks-from-climate-change.

11 Prudential Regulation Authority. (March 2019). PRA and FCA’s joint Climate Financial Risk Forum. Available: https://www.bankofengland.co.uk/news/2019/march/first-meeting-of-the-pra-and-fca-joint-climate-financial-risk-forum.

12 Forthcoming April 2019

13 As described in TCFD September 2018 report:  These companies disclose the inputs to and outputs of their scenario analyses including strategic responses to the low-carbon transition, such as changes in portfolio mix or investment

14 Encouragingly, all members of the oil and gas preparer forum used the 2-degree energy transition scenario to inform strategic decisions. The materials and building sector also had the highest percentage of companies disclosing information about strategic resilience and most provided some information on the climate-related scenarios they used to make these assessments. 

15 The most widely used and well-known are the IEA transition scenarios, which model six different assumed pathways and associated temperature increases. For modelling physical risks, the IPCC’s four Representative Concentration Pathways (RCPs) fix greenhouse emissions and analyse the resulting change to the climate.

16 The voluntary network was set up by 8 central banks and supervisors in December 2017 at the One Planet Summit, and has since grown to 29 members, representing countries accounting for nearly half of global emissions, and five observers. It is a voluntary, consensus-based forum whose purpose is to share best practices, contribute to the development of climate- and environment-related risk management in the financial sector and mobilize mainstream finance to support the transition toward a sustainable economy. The analytical work is split into three work streams and the research will be published in April 2019: WS1 microprudential/supervisory; WS2 macrofinancial; and WS3 Scaling up green finance. 

17 For more information on the Commission’s Sustainable Plan, see: https://ec.europa.eu/info/business-economy-euro/banking-andfinance/sustainable-finance_en    

18 See: CBI https://www.climatebonds.net/about and ICMA https://www.icmagroup.org/green-social-and-sustainability-bonds/greenbond-principles-gbp/

19 Climate Bonds Initiative. (2018). Green bonds: The state of the market 2018. Available: https://www.climatebonds.net/resources/reports/green-bonds-state-market-2018   

20 By Indonesia, Belgium, Lithuania, Ireland and Seychelles 

21 See: https://www.unpri.org/pri

 22 Deloitte. (Nov 2015). The future of wealth in the United States. Available: https://www2.deloitte.com/content/dam/insights/us/articles/us-generational-wealth-trends/DUP_1371_Future-wealth-inAmerica_MASTER.pdf     

23The Cerulli Edge, Global Edition, Issue 206 (Apr 2018). Available: https://www2.deloitte.com/content/dam/insights/us/articles/usgenerational-wealth-trends/DUP_1371_Future-wealth-in-America_MASTER.pdf   

24 Clark, G, Feiner, A, and Viehs, M. (March 2015). From the Stockholder to the stakeholder: how sustainability can drive financial outperformance. (Oxford University and Arabesque) 

25 Friede, G, Busch, T, and Bassen, A, (2015) ESG and financial performance: aggregated evidence from more than 2000 empirical studies, Journal of Sustainable Finance & Investment, 5:4, 210-233

26 Nordea Markets. (Sept 2017). Cracking the ESG code. Available: https://nordeamarkets.com/wp-content/uploads/2017/09/Strategyand-quant_executive-summary_050917.pdf   

27 BlackRock. (Feb 2019). Sustainability: The Future of Investing. Available: https://www.blackrock.com/us/individual/literature/whitepaper/bii-sustainability-future-investing-jan-2019.pdf   

28 A recent review by Hermes Investment Management shows that companies with good or improving social factors have outperformed other companies by 15bps per month over a decade and good governance generates a 24bps per month elevated return.  A focus on the E in ESG – environmental – meanwhile has no penalising effect on returns, and companies with strong environmental policies do better in downturns by 19bps than their peers.  See: https://www.institutionalassetmanager.co.uk/2018/11/13/270456/hermes%E2%80%99-esg-study-reveals-social-characteristicsoutperforming   

29 Nagy, Z, Kassam, A, and Lee, L-E,. (June 2015). Can ESG add alpha?.Available: https://www.msci.com/documents/10199/4a05d4d3b424-40e5-ab01-adf68e99a169.

30 See: https://www.bnymellon.com/us/en/newsroom/news/press-releases/bny-mellon-debuts-service-to-evaluate-environmental-socialand-governance-factors-in-investment-performance-03-19-2019-newsid-13.jsp   

31 See: https://www.ubs.com/global/en/ubs-news/r-news-display-ndp/en-20190121-wef.html   

32 See: https://www.ishares.com/us/strategies/sustainable-investing#esg