LCH SwapAgent, a service for the non-cleared derivatives market, has registered its first Sonia/Sofr cross-currency basis swap, on behalf of Bank of America and Lloyds Bank Corporate Markets.
LCH, the UK clearing house said the trade was completed ahead of the upcoming discounting and price alignment interest transition to USD SOFR at LCH SwapAgent, which is scheduled for 16 October.
“This latest milestone for LCH SwapAgent demonstrates the service’s capability to facilitate a coordinated transition to risk-free rates for non-cleared OTC derivatives,” said Nathan Ondyak, global head of LCH SwapAgent, “This neatly complements our existing offering which is delivering operational and funding efficiencies to a growing community of members.”
Richard Pattison, head of CCY and CSA, Lloyds Bank Corporate Markets, added, “As a major participant in the sterling rates market, it is important for us to see liquidity develop in the new risk free benchmark rates. We are happy to contribute to that developing liquidity and welcome the efficiencies SwapAgent brings to the uncleared OTC derivatives market.”
Sofr and Sonia are the alternative reference rates to Libor for US dollar and UK sterling derivatives. Sonia is a well established benchmark but Sofr was designed specifically for the Libor transition and there has been debate in the industry as to whether it should be the substitute.
The deadline for the Libor tranistion is 31 December 2021 although new derivatives and swaps contracts are already moving to alternative overnight rates set by central banks like the Bank of England and the Federal Reserve.
Scott O’Malia, CEO, ISDA.
The International Swaps and Derivatives Association (ISDA) is amending documentation used as a template for swaps trades globally to state what would be the alternative or “fallback” interest rate used if Libor disappeared for pricing outstanding contracts.
There are question marks as to when the protocol will be published and if this will change the timetable. Last week, Edwin Schooling Latter, the UK Financial Conduct Authority’s head of markets policy, told a Bank of England webinar that banks could sign up to the fallback from “sometime in October”.
Tushar Morzaria, chair of a financial industry working group on Libor transition, added in the same webinar that the “ISDA protocol should be published quite shortly…in days and weeks rather than months,”
However, ISDA said it now expects the effective date for amendments to documentation in mid-to-late January, less than a year before Libor is due to cease.
The trade group’s CEO Scott O’Malia said the timetable hinges on approval from the U.S. Dept. of Justice and other competition regulators.
“Once we hear from the competition authorities, we’ll give market participants approximately two weeks’ notice of the official launch date,” O’Malia said in a blog.
The delay could affect an anticipated sequence of events, including more detailed announcements on the phase-out of Libor and its variants from the FCA, and from the administrator that compiles Libor.
Valdis Dombrovskis, executive vice-president in charge of financial policy, European Commission.
The European Commission warned that the European Union must reduce its dependency on the City of London for entrée to capital markets as well as strengthen its financial regulations to help companies hard hit by Covid-19.
“This is particularly important in light of Brexit, as Europe’s biggest financial centre is leaving the single market,” said Valdis Dombrovskis, an executive vice president of the European Commission. EU efforts to improve access to capital markets date back to at least 2014 but the Commission hopes that Brexit, the economic hit of coronavirus and the need to finance the “green transition” will give it fresh impetus.
Companies will have to refund themselves as they emerge from recession caused by pandemic lockdowns. The EU would like them to tap the equity and bond markets for funding instead of relying on bank loans, which has been a traditional source of financial support.
The Commission said plans would help give the EU market “strategic autonomy” when Britain exits the bloc’s single market on 31 December “in order to prevent a race to the bottom after Brexit.”
The Commission has published an action plan to build a capital markets union, a long-term strategy to establish large integrated sources of finance for businesses in the bloc. However, the road to the CMU has been long and bumpy.
The hope is that this will give the CMU the impetus to move forward. In a communication to EU governments, the Commission noted that “Brexit has a significant impact on the Capital Markets Union. It further strengthens the need for the EU to have well-functioning and integrated capital markets.”
It added that it is even more important to have strong financial supervision at the EU level to prevent competition from lower standards in London or elsewhere in the bloc.
“An enhanced single rule book and effective supervision will be crucial to prevent regulatory arbitrage, forum shopping and a race to the supervisory bottom,” the Commission said.
A new study by analyst firm Capco has outlined the drivers, pros and cons for buy-side outsourced trading, yet Capco was unable to say how much outsourced trading is happening today.
There has been much publicity around the drivers for outsourced trading, but where data is available, uptake appears to be happening in a specific and limited way.
Northern Trust currently reports having 61 clients using its outsourced trading services, up from 23 in 2018, all of which it notes are institutional and involved in a range of public equities, fixed income and derivatives investment strategies. These are typically in the US$1 billion to US$10 billion assets under management (AUM) range of traditional long-only asset managers.
In a survey of 300 fund managers, mostly private equity specialists with less than US$50 billion AUM, which was published by WBR Insights and Northern Trust in June 2020, 17% of firms reported they outsourced trading functions, equating to about 51 firms.
A 2018 report into outsourced trading by Greenwich Associates, which surveyed 44 asset managers of whom 9 had an AUM over US$10 billion, 48% of respondents were currently working with at least one outsourced trading desk.
Capco noted in its new report that outsourcing was particularly of interest to hedge funds, but also cited a study from consultancy Opimas in 2018 which had predicted that by 2022 about 20% of investment managers with assets under management greater than US$50 billion will outsource some portion of their trading desks.
A large number of firms offer outsourced trading – Capco cites 17 providers – suggesting the estimated market size by outsourcing providers is significant. Northern Trust also says the size of the firms it is engaged with is changing. “As we grow, not only do the size and sophistication of manager grow, but so too the complexity of their instrument coverage,” noted a spokesperson.
If focused on the sub-€10 billion (US$11.7 billion) AUM market, that would still present a target of 113 asset managers globally out of the top 500 firms.
Hard to fill
Putting analyst predictions aside, it is hard to find real-money firms that have outsourced trading today. Pension fund Railpen had engaged in a well-reported deal in 2015, but its annual reports for all subsequent years reference its growing “inhouse trading capabilities”; the current state of that outsourcing project is unknown and it did not respond to requests for comment. Hedge fund manager Ardevora, (US$5.1 billion AUM) was contacted for this article and outsourced its trading operations in April 2020. One fund manager contacted had supplementary outsourced trading capacity if needed, but still operated a centralised trading desk.
Primary drivers to outsource trading as laid out in the Capco report include:
• Cost saving, with higher trading costs and lower revenues the costs of both technology and staff can be reduced via mutualisation through an outsourced provider, along with movement to a variable or on-demand cost model;
• Passing on regularity requirements such as MiFID II obligations;
• And access to wider trade support such as 24-hour markets, larger broker network and larger liquidity pools through higher trading volumes provided by an outsourced provider.
Amongst the buy-side firms spoken to for this article, the value of outsourced trading was most clearly seen in adding value to services – allowing discrete trading of large positions in small cap names for example, or accessing a more expansive broker list in less traded markets which cannot justify permanently onboarding of brokers.
Cost rarely surfaced as a driver, primarily because making trading decisions based upon the lowest explicit costs risked ignoring higher implicit costs, such as market impact and implementation shortfall which can be more significant.
There were also concerns about the way costs of trading could be allocated via a third party. Under MiFID II an asset manager must pay its trading costs, and make them transparent to the client. However, if a fund is paying a fee to a service provider without the intermediation of a trading function, it is possible that trading costs could be hidden from the client.
The trading process is integral to the investment process, and provides valuable input into wider portfolio and risk views, which makes any outsourcing of the function – even partial – contingent upon considerable value being generated as a result. Information captured by the trading team was seen as feedback that would be wasted if it were shared across multiple other rival firms.
Clearest view
A lack of conflict between business areas, access to natural liquidity and being seen as a genuinely ‘buy-side’ trading desk were all seen as positive attributes for a firm offering outsourced trading.
Several buy-side interviewees felt approaches that outsourcing providers had taken in sales approaches and marketing strategies were misrepresenting the business capabilities offered and the firms’ client bases.
Across a wide range of real-money asset managers, spoken to for this article, all with AUMs of over US$10 million, all had centralised trading functions, and only one had supplementary cover from an outsourcing provider.
Getting to the facts, based on supplied by the providers themselves and all of the available research published in the public domain, it seems clear that asset managers with up to US$10 billion AUM, can potentially find value in outsourcing trading. However, there is no clear evidence that the model has found fertile ground with any larger asset managers to date.
Jennifer Peve talks to Lynn Strongin Dodds about innovation, experimentation and connections.
Jennifer Peve, managing director of Business Innovation at Depository Trust & Clearing Corporation (DTCC) is living up to her job title. In the past five years, the US based market infrastructure provider has been at the forefront of the cutting-edge trends of digitalisation and tokenisation.
Peve oversees business development activities across the DTCC Solutions portfolio, working internally as well as externally with clients and third-party providers to seek opportunities for new products. In addition, she is responsible for identifying potential acquisitions, partnerships, and mergers to broaden DTCC’s capabilities.
The other aspect of Peve’s job is to define DTCC’s strategy for new and emerging technology innovation, which includes exploring and experimenting with fintech. She, along with her colleagues and the industry, also discuss key topics and develop thought leadership.
“We look at how we can leverage technology to bring an idea to life and introduce new ways of working to mitigate risks, generate greater operational efficiencies and reduce costs for clients,” says Peve. “The thought leadership role is about sharing lessons learnt and staying abreast of the latest developments.”
However, before the team even gets to a drawing board, they engage in zero based thinking which is a systematic process that allows a person to reflect on past decisions and then ask, based on actual outcomes, if they would choose the same or change direction. In effect, it works like hindsight in that it is based on experience and then applied from a hypothetical future to the actual present in order to maximise the chance of success and/or avoid the risk of failure.
“Zero-based thinking is like taking a blank sheet of paper that allows you to tear something down and then build it up again,” says Peve. “It is helpful when you are looking at a new business initiative or want to explore a new idea because it provides a better understanding of the market, trends and industries. It allows you to consider the capabilities and processes that may not have existed before.”
Peve is also a strong believer in the value of industry collaboration to develop solutions because as she says, “market structures shouldn’t build solutions in isolation but instead partner with industry participants who have the capabilities, skillset or knowledge to identify relevant initiatives and make a project work.”
Currently, DTCC is looking for client engagement on two projects – ION and Whitney – which are at the experimentation stage. They both aim to use blockchain technology to improve the current business models. The former, which, is targeted at public markets, is a proof of concept (POC) that aims to validate an alternative, faster digital settlement service that maintains central netting and prevents fragmentation of the clearing and settlement ecosystem.
Project Whitney, on the other hand, is a prototype for a digitised private market infrastructure for each stage of private securities, from issuance to transfer. The theory is that security tokens among other solutions could eliminate much of the manual processes, leading to a smoother, more efficient market for private securities.
“Projects Ion and Whitney represent the next steps in our digitalisation journey,” Peve said. “Both serve as examples of practical experimentation incorporating innovative technology and business concepts designed to strengthen post-trade processes and provide a resilient, secure and efficient post-trade infrastructure for the industry.”
Although Covid-19 has created challenges for the industry, Peve believes that it has also “underscored the importance of digitisation and reinforced that digital transformation of post-trade infrastructure has the potential to reduce risk and costs, enhance efficiency, and increase safety and stability of the marketplace. Particularly since the market volatility in March, we have seen the benefits of a more automated digitized ecosystem, as well as the need for further dematerialisation regarding physical securities processing.”
On a more micro level, Peve has tried to replicate her team’s collaboration as well as maintain their enthusiasm and entrepreneurial spirit in a virtual setting. “DTCC has always had flexible work arrangements in place, but my team always preferred to engage in person,” she says. “What we are doing now is having to reset a new normal. People have had different experiences, but they have had to create new patterns and routines.”
She says technology has been an enabler that has allowed them to connect with each other, as well as other colleagues and clients daily. “A huge part of what our team did was use white boards to write down different solutions, but this is not as easy with a mouse as it is with a pen. As a result, we are leveraging different video tools to facilitate the process.”
While maintaining strong professional relationships is key, Peve also ensures that her team stay connected on a personal level as working from home can be difficult for some people. “We have our daily call, but we also make sure we have virtual ‘happy hours’ where we are not allowed to discuss work,” she adds.
Although project management, design, strategy, and innovation have featured throughout Peve’s career, her first job was not in financial services but in the energy sector in Texas where she spent part of her childhood. She honed her skills at companies such as Basis Petroleum and Cargill Investor Services before moving onto CME Group in 2008 where she served as executive director of OTC Product Management, responsible for the firm’s cleared OTC credit default swaps (CDS) business including growth strategy, business development, and go-to-market activities.
Reflecting on her career to date, Peve says that most of the companies she has worked for have been supportive of workforce collaboration and opening career opportunities. The way I evolved is I took the opportunities that were available. I jumped in and raised my hand. This does not mean that I did not run into difficult situations, but it made me think about the best ways to manage them and to progress. Having confidence in your abilities is the best way to get noticed.”
She adds, “The hope one day is that we will not need a special category for women in finance and it will just be people but in the meantime, women continue to be underrepresented in the industry and it is important to celebrate their successes. The more visibility we give them, the more we advance diversity and inclusion. For example, younger women may be discouraged from entering a career in finance or technology but organisations that make it a high priority will attract their talent.”
Gary Paulin, global head of Integrated Trading Solutions, Northern Trust Capital Markets.
Front office outsourcing trading is not a new trend on the buyside, but it is accelerating due to the disruption caused by Covid-19 along with increased competition, fee pressure and regulation, according to a new paper from Northern Trust – From Niche to Norm.
The paper points out that over the past six months, asset managers have had to grapple with market volatility, extreme margin pressure, technology resiliency, cyber-risk and business continuity plans. However, many of these challenges were already bubbling under the surface and the pandemic is now forcing asset managers across the size and strategy spectrum to closely assess their operating models.
This is leading many to either embark or think about farming out functions to a third-party provider that were once considered core such as in-house dealing, foreign exchange and transition management.
“Big outsourcing waves have typically occurred at the end of bull markets as falling asset prices expose high fixed costs and margin pressure ensues. Last year however, many managers faced margin pressure despite markets going up” says Gary Paulin, global head of Integrated Trading Solutions at Northern Trust Capital Markets. “Covid has provided the opportunity for them to look at their operations and to make the necessary changes.”
While important cost is not the only driver though. As Paulin says, “The question fund managers are now asking is what functions do I have that add value to the investment decision making process. “For example, portfolio managers formulate strategy, while dealers implement that strategy. They are distinct roles and should therefore be resourced in distinct ways.”
He adds, “The aim of outsourcing should be to move asset managers to an optimal and future state which includes cost savings but also streamlined and greater efficiencies as well as an enhanced system of governance and control. This is particularly important in the light of the Senior Managers & Certification Regime (SMCR) “
The SCMR which came into force last year, holds individuals accountable for their conduct and business failures under their management.
With Dwayne Middleton, Head of Fixed Income Trading, and Amit Deshpande, Head of Quantitative Fixed Income Investments & Research, T. Rowe Price
What has been the evolution of automation in fixed income trading and what is the current state of play?
Dwayne Middleton, T. Rowe Price
Dwayne Middleton: The evolution of automated trading in fixed income, from a buy-side perspective, emanated from efficiency and scalability efforts. Data aggregation initiatives, the acceptance/growth of third party algo driven pricing and the increasing role of the buy-side trader as a price decision maker have all contributed to provide flexible, rules based, data driven opportunities to trade. Whether it is setting an execution level vs. one of the composite level pricing sources, a range of liquidity scores, and/or a required number of quotes received, the ability to generate automated orders for execution that fit these rules based constraints has been beneficial to increasing the efficiency of the trading desk.
Amit Deshpande: While the buy side has made significant progress in automating fixed income trading, we are still very early in the game, especially when compared to some other asset classes. The market is increasingly seeing use of electronic trading platforms that has led to more efficiency. However, much of this gain has been in the segments of the market that have been traditionally more liquid, and for orders that are homogenous. Large and complex executions such as portfolio trades still take manual intervention and can take hours to complete. The inherent complexity of fixed income markets has slowed the evolution somewhat, especially compared to equities and currencies.
What are the benefits of automation in fixed income trading?
DM: A key benefit is capturing the pricing information, dealer quotes, and Trace data at that point of time and being able to prove out the quality of our executions. Capturing the full liquidity opportunity set for a security is critical today given how fast the velocity of information and data flows across the desk. Feeding this data back into our pre/post trade analysis tools is a benefit to our investment process across portfolio management, research and trading. Time management and multitasking under pressure situations are key characteristics of a desk that operates at a high level, so moving repeatable trades of securities to a more automated workflow and gaining access to that data in near-real time frees up the desk to participate in more value-added discussions in the investment process.
Amit Deshpande, T. Rowe Price
AD: In addition to the important points above, elimination of friction caused by manual trading is an added advantage of such automation. In most cases, better price discovery is a natural consequence of increased reliance on systematic trading algos. In the ideal state, fuller automation would lead to more orderly and predictable markets. This means lower inter-temporal variation of the liquidity premium and better value attribution to the various market risk premia. Over time this could lead to a dampening of the volatility-of-volatility from today’s levels and improve risk adjusted returns for the intelligent investor. This would also lower trading costs resulting in more seamless and efficient market making.
What are the challenges/limitations of automation in fixed income trading?
DM: Fixed income has many facets of high touch trading in sectors/markets that benefit structurally from human intervention to facilitate best client outcome. Extreme volatility as we saw in March 2020 posed some challenges for some of the low touch automated workflows but as that volatility subsided, we did see the percentages of automated volumes return. To benefit from the efficiency and data aggregation benefits from automation, the workflow is limited to securities where there is robust price visibility and quality composite pricing to make rules-based execution consistent with our efforts for best client outcome. Our technology platform must incorporate broker restrictions, guideline compliance and the ability to capture all of the prices/quotes at the point of execution.
AD: It is almost a fallacy to lump all bonds into one “fixed income” category. Emerging Markets Local, for instance, has as much to do with Treasuries as Oil has with to do with Chinese Real Estate Trust. Most fixed income asset classes have neither the transparent price discovery of equities nor the advantage of liquidity enjoyed by FX. Trade execution is improved greatly by automation for certain assets but not significantly for others. One challenge is optimization of electronic order flow in a market traditionally dominated by manual processes, including both buy-side orders and inter-dealer platforms. We are at a stage where dealers have efficient execution platforms for the more liquid instruments but still use non-automated environments for others. The paucity of historical data combined with lack of transparency has hampered development of trading algorithms which could facilitate a greater electronic presence in execution. These issues are exacerbated by market volatility as Dwayne pointed out.
What areas within fixed income trading are suitable to automate and which may not be?
DM: We have seen an uptake for trade automation in more liquid sectors such as on-the-run Treasuries. Credit securities with a well-defined market context and visible pricing also have seen growth in this area. Liquid portfolio products trades such as generic trades in rates derivatives and CDX/iTraxx indices are areas where automation works. There have been innovations in mortgage backed securities (MBS) and even parts of emerging market debt. Less liquid segments of fixed income or where the human touch is required do not now fit this workflow. Security selection driven by the unique insight of our research teams combined with the risk parameters set by portfolio managers also lean to more high touch trading. Even within high touch trading, we are looking for ways to reduce clicks and streamline the execution.
AD: I agree with Dwayne. Liquidity and trade automation seem to be inexorably tied in a self-referential loop. As long as price is a function of volume and trader interest, we will continue to see this dichotomy. There is a reason why fixed income traders – and not just the Physics majors — are familiar with Heisenberg’s Uncertainty Principle.
For a buy-side firm, is automation in fixed income trading about automating in-house, or is it more of a sell-side story?
DM: Fixed income trade automation is unique to each firm, in my opinion. We need to partner with dealers and platforms regarding our efforts around automation. We are focused on getting smarter and more resourceful in our search for liquidity. This is the intersection within fixed income between defining efficient methods to deploy our trading, data science and quantitative efforts to deliver investment results for clients. Automation fits within our strategic efforts on maximizing our trading platform and efforts to streamline repeatable processes.
AD: Buy-side firms can gain a lot of leverage by harnessing the power of data and trade automation. Almost every firm of size has access to price, volume, and position information but it is often highly fragmented. Centralization of this data on an intelligent digital platform can help a firm identify dislocations of price and demand. Taking advantage of the changing cost of liquidity, for instance, can add an uncorrelated source of alpha to client portfolios. Integration of research and trading platforms can lead to better relative value calls. It is well-recognized that the shelf life of research has shrunk as the asset management industry has grown. The upshot is that arbitrage strategies are becoming more dependent on technicals than on fundamentals. Automation can help the buy-side reduce costs, gain flexibility, and ultimately be more nimble with opportunistic trades.
What is T. Rowe Price doing to advance automation in fixed income trading, whether that be in-house or in terms of leaning on sell-side partners to automate?
DM: We are in various stages of planning and development to build our trading ecosystem to be as future-proof and scalable as we can. Data and connectivity go hand-in-hand for an effective automated workflow. We are learning from our colleagues on the equity side of the house who have lived through this electronification and are using automation for certain workflows. As traders, we partner with internal colleagues including portfolio managers, analysts, technology, compliance, and legal as well as external partners for order workflow and data aggregation initiatives. Conversations with our dealer partners start first with our focus on clients. We are working on several initiatives to bring a higher-quality level of engagement with our dealer partners. Direct connectivity is one avenue that will create value-added engagement on behalf of our clients. Dealers play a leading role in risk transfer and their efforts to bring innovative tools in partnership with the buy side are welcome.
What role does artificial intelligence play in the automation of fixed income trading?
AD: The use of AI in traditional fixed income trading platforms is so rudimentary that nearly every major area could potentially benefit from such techniques. More accurate pricing is one such opportunity. Most pricing services use recent trades to update their marks. However, it is not a trivial exercise to update prices for bonds that have not traded for days, if not weeks. If, for example, we see a large trade in VZ 2.5 of 5/16/30, it will likely have a price impact on other bonds across the issuer’s curve, on the Wirelines sector, and on the BBB curve. This propagation has traditionally been a high touch activity with significant differences between firms especially in High Yield, EM, and Munis. AI techniques like cluster analysis and backpropagation algorithms can help with faster price discovery. Another potential area is in identifying transient and long-lasting sources of value. Traditional investing has favored the latter because of its better signal-to-noise ratio. But with the help of deep learning algos, one could identify short lived pockets of local dislocation that mean revert faster than traditional value metrics. There are several other use cases where supervised and unsupervised learning can complement manual trading processes. Over time, we will see the emergence of higher-frequency and high mean reversion trade ideas add significant alpha to real money portfolios, as they have done to alternative investment strategies.
What role do algorithms play in the automation of fixed income trading?
DM: Within equity and FX markets, algos are more prevalent. The growth of automated market making across credit markets has dramatically improved the response rates and hit ratios across many of the electronic platforms. This in turn led to the development of rules-based constraints for automated workflows via the order management system on electronic platforms. The composite pricing created by the platforms also plays a key role. This afforded the buy side the ability to implement automated executions by having readily accepted reference pricing used to evaluate the dealer-sourced bids and offers in combination with the other constraints such as liquidity scoring.
AD: Algos have the potential to add significant value by making data-driven and rules-based trades in real time with minimal human intervention. Minimizing market impact of large order executions, generating alpha through arbitrage opportunities and designing efficient hedges are some areas well suited for quantitative and algorithmic trading. As Dwyane said, we have seen growth in algo-driven trades in the more liquid asset classes like FX and Rates. The most direct way to use algos in fixed income is for non-directional, risk-neutral relative value pairs. An example would be curve trades that take advantage of temporary misalignments amongst different maturities of the same issuer. The advantage of algos is not as much as in generating trade ideas as in the speed of identifying such dislocations. In March 2020, we saw multiple sigma moves in the NAV basis of many large ETFs as markets struggled to find fair value for the underlying securities. At the same time, the cash-synthetic basis in credit derivatives showed a similar pattern. It would have been impossible to manually flag and monetize each opportunity, but an algorithm could easily create a basket trade in near-real time.
What is the role of trading platform providers (e.g. MarketAxess, Tradeweb) in advancing automation in fixed income trading?
DM: The electronic platforms provide a lot of value outside of their original execution models. The composite pricing is one. Another is the enhanced integration with the key OMS providers and EMS providers. They have been essential to the fixed income trading infrastructure developments that have occurred over the last few years. The other role is around data capture and delivery back into our internal systems. Straight through processing is key for efficiency efforts. The platform plumbing also provides a path for all-to-all trading where the desk may passively aggress around liquidity that best meets client outcomes.
What is the future of automation in fixed income trading? Where will it be in five or 10 years?
DM: The role of pure execution fixed income trading is largely over. Traders must add value in the investment process and that includes market intelligence, flexible trading protocols and intellectual curiosity. The complexity of client portfolios, the pace of information flow and operating in a global multi-asset fixed income world requires a high degree of intensity and focus from today’s fixed income trader. Our efforts around efficiency will only increase going forward.
AD: The focus of the modern buy-side trading desk is to seek alpha through idea generation and superior execution. Large platforms such as ours sit at the crossroads of global order flow, real time price discovery, and proprietary research. A big change we have seen in the last decade has been the explosion in data available to make decisions. FINRA alone reports processing more than 75 billion records every day! The nature of data has changed as well. Historical tick data used to dominate earlier, but now trading histories, reference data, and even alternative data like Natural Language Processing (NLP) are gaining importance. However, analytic tools available to transform data into decisions have lagged quite a bit. While human traders are still likely to be calling the shots in a 5-10-year timeframe, they will most probably be assisted by smart decision-making algorithms. We see the mainstreaming of integrated trading/portfolio management tools that will use ML/AI techniques to combine external feeds like news events and price innovations with prop information like quant signals and fundamental research. Automation will help accelerate the value added by trading in the investment process.
With Thomas Kwan, Chief Investment Officer, Harvest Global Investments
Thomas Kwan, Harvest Global Investments
Briefly describe Harvest Global Investments and outline your role and responsibilities as CIO.
Harvest Global Investments is a fully owned subsidiary of Harvest Fund Management, one of the largest asset management companies in China with almost USD 140 billion in secondary market assets under management. As the international arm of the Harvest Group, Harvest Global Investments has been serving as the global gateway for global investors to access to China’s capital markets and the opportunity to participate in its rapid growth since 2008. As the CIO of Harvest Global Investments, I oversee all investment activities conducted by Harvest Global Investments and lead ESG initiatives for the Harvest Group.
How does a firm build an ESG investment framework?
Harvest combines the strengths of international ESG standards and local factors that could weigh on a Chinese company’s growth sustainability. We developed our proprietary ESG investment framework based on extensive research of global frameworks, and applying local expertise and understanding of material ESG issues and trends in the local market. There are a few key considerations for us to take this approach: first and foremost, we want to improve the overall ESG data accessibility and quality in China to gain insights in a company’s capacity for long-term sustainable development. Second, we want to leverage the ESG framework to generate alpha returns for the portfolios we manage and mitigate market downside risks in China. Last but not least, with a team of seven dedicated ESG specialists in Beijing and Hong Kong, the most among Chinese asset managers, Harvest has demonstrated that insufficient ESG data quality in the market can be supplemented by rigorous,in-depth research performed by in-house ESG data scientists and investment analysts.
How does the Harvest Investment team utilize ESG?
At Harvest, the investment team is a critical component of our ESG research and integration program. Our analysts contribute to our ESG research via inputs into our proprietary ESG model. The model’s output – in the form of ESG scores and insights – is then utilized by sector analysts and portfolio managers in their investment decisions. Our ESG model evaluates non-financial aspects of companies to assess their ability to conduct businesses against various tail risks, including environmental, social, and corporate governance, as well as physical and transitional risks arising from changes in regulations and policy. We also analyze ESG performance from a portfolio perspective, and consider underweighting or divesting significant laggards in order to maintain a relative portfolio ESG level.
What are the challenges, and opportunities, with regard to ESG data in investing?
The ESG disclosure quality of Chinese companies has been low. Chinese listed companies are encouraged to voluntarily publish Corporate Social Responsibility reports, but such reports have been often presented as marketing tools rather than proper ESG disclosures. However, there are vast opportunities ahead as regulators strengthen disclosure requirements and market sentiment on ESG matters evolves. ESG rating agencies are expanding their footprints in China, and they will motivate Chinese companies to increase their focus on ESG issues. In the short term, this may mean changes in business strategies. In the longer term, companies will reconsider their business models to pursue sustainable growth.
As a major investor in China, Harvest sees the evolving perception on ESG as an opportunity. We believe our early mover advantage in integrating ESG research and analysis into the investment process will help us to generate alpha in China’s thriving financial markets, both onshore and offshore.
What is the global framework versus the China framework for ESG?
Global ESG frameworks provide a cross-market benchmark reference when investing across a region. However, like every market, China has its unique local market issues, which are sometimes neglected or even omitted by global ESG frameworks for the sake of comparability. The materiality of ESG issues also vary from market –to –market, depending on a variety of socioeconomic and geopolitical factors. For a deep financial market like China, investors may consider developing their proprietary framework to fully internalize and understand the ESG issues and materiality at work. We are also mindful that some issues in developed markets are not prevalent in China at present, but may become material in the future. In these cases, we refer to development trajectories of developed markets and contemplate how China may develop in the future.
Where does artificial intelligence fit into a discussion about ESG?
Discussion of ESG issues’ impact on investments involve complex and dynamic issues which could be difficult to quantify. Artificial intelligence can improve ESG data quality on at least two facets. First, artificial intelligence can extract and process unstructured data from a variety of public sources to enhance data quality and granularity. Second, artificial intelligence can help portfolio managers systematically identify and understand issues that are increasingly material to investment outcomes, especially during China’s rapid transition towards a sustainable economy. At Harvest, we utilize Natural Language Processing (NLP) techniques to monitor and categorize ESG issues of companies under our coverage. This helps to enhance the breadth and depth of our ESG analysis.
What is the future of ESG in investing in China?
We view ESG as an emerging and integral part of investing in China’s fast evolving financial markets. For the past several years, Chinese regulators have gradually introduced guidelines and requirements for companies and asset managers to enhance awareness on ESG issues. The People’s Bank of China (PBOC), the Chinese Securities Regulatory Commission (CSRC), stock exchanges and the Asset Management Association of China (AMAC) have published guidelines or codes to promote sustainable investing in China. In addition, as China’s continuously expanding middle class population aspires to a higher quality of life, corporations in China must aspire to higher standards. Against this backdrop, we believe ESG-driven analysis will become more mainstream in China over time.
The WIFAA program recognizes the most talented and accomplished women in multiple categories across the business of finance. WIF nominees may come from buy-side and sell-side trading desks, institutional investors, wealth managers, securities exchanges, technology providers, corporate finance, venture capital firms, start-ups — really any area within the financial sector.
Nominees are first put forth by readers of GlobalTrading Journal and MarketsMedia.com, and shortlists and winners are determined by the editorial staffs of the two platforms, in conjunction with the WIF Advisory Board. As with our six- year-old Markets Choice Awards franchise, our methodology in selecting nominees and then winners for Women in Finance is simple yet thorough, and keeps the focus on the important opinions: those of market participants, not ours.
The following is the shortlist for the 2020 Women in Finance Asia Awards:
Liesbeth Baudewyn, Systematic Trader, Citadel Geraldine Buckingham, Senior MD, APAC Chairman, BlackRock Cheryl Chan, Equity Trader, BlackRock Susan Chan, MD, Head of Asia and Head of EII and TLL Asia Pacific, BlackRock Edna Chan, Director, Asia Pac Head of Cash Equities Middle Office, Citi Cecilia Chan, CIO Fixed Income, Asia Pacific, HSBC Global Asset Management Tricia Chan, Client Sales Lead, MarketAxess Michelle Chen, VP, PB Sales, Citi Carrie Cheng, Trader, BNP Paribas Rachel Chua, Credit Analyst, MarketAxess Wanming Du, Head of Index Management, Asia, FTSE Russell Julie Flack, General Manager, Broadridge Australia Belinda Fong, Director, Credit Suisse Niamh Golden, Head of Analytics, APAC, Virtu Finanicial Lynda Hall, MD, Head of APAC Global Client Services, BlackRock Nithya Jagannath, DVP-Product Development, SBI Funds Management Winnie Khattar, Head of Market Structure, BofA Terecina Kwong, Chief Operating Officer HSBC China, HSBC Janice Lau, Executive Director, Instinet Catherine Lee, VP, Investor Sales/Custody Sales, Citi Natalie Lo, Trader, State Street Global Advisors Elizabeth Lo, Chief Operating Officer, TX Capital Varda Pandey, Fixed Income Institutional Sales, Nomura Mary-Anne Peril, Execution Services, APAC, Virtu Financial Jasmine Pong, Executive Director, Credit Suisse LeiLei Qu, Associate, J.P. Morgan Asset Management Laurence Raby, Chief Risk Officer – Asia Pacific, HSBC Global Asset Management Ashley Sham, VP, Citi Rebecca Sin, Head of Equities, Asia, Tradeweb Susan Soh, Managing Director, Schroder Investment Management Corrinne Teo, Managing Director, Nomura Denny Thomas, COO, HSBC Global Asset Management – India, HSBC Global Asset Management Wei Wang, MD/Head of China – Country Head, BofA Wendy Wang, Director, HR APAC Business Partner for ETF & Index Investment (EII), Investment Platform and Trading, Liquidity, Lending (TLL), BlackRock Erica Poon Werkun, MD, Head of APAC Equity Research, Credit Suisse Jessie Xu, Trader, FMR Joelle Yap, Director – Client Development & Sales, CME Group Angely Yip, Head of Sales and Relationship Management, North Asia, BNP Paribas Securities Services
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