By Rupert Walker, Managing Editor, GlobalTrading
Regulatory and technical changes are rapidly reshaping the trading landscape and all industry participants need to adapt.
The growth of the exchange-traded fund (ETF) sector, preparations for the launch of the Markets in Financial Instruments Directive (MiFID) II and the potential of artificial intelligence (AI) were dominant themes at the Singapore FIX Conference, held on 10 November 2017.
Speakers and panellists included senior executives from buy-side firms: BlackRock, Eastspring Investments, Janus Henderson Investors, Nikko Asset Management and UBS Asset Management; sell-side firms: Bank of America Merrill Lynch, CLSA, Deutsche Securities, J.P. Morgan, Société Générale and State Street; from the Singapore Exchange, Hong Kong Exchanges and Clearing, and alternative trading platforms; as well from leading trading technology vendors.
ETF efficiency
ETFs offer investors liquidity, transparency and wide market exposure, and are cost effective. Asian money managers are raising their exposures to US and European ETFs, often trading them in the same manner as individual stocks. It is important to understand that the liquidity of ETFs is determined by the liquidity of the underlying shares, and that the stated volumes traded on exchanges are not truly reflective of the liquidity that is available, argued speakers.
However, Asian home-grown ETFs are 10-to-15 years behind the US and Europe in development. The region needs to create new, unique products in order to attract investor interest, rather than simply replicate existing forms. The Singapore Exchange recently listed three innovative Reit ETFs, and the exchange is also trying to make the tax regime for retail investors more attractive, and promote ETFs to the country’s Central Provident Fund. Other segments targeted by leading ETF sponsors include private wealth management.
Although the Asia market is fragmented with competing jurisdictions, many investors are suspicious of the true value added by active strategies and continue to support the growth of passive funds. Issuers and sponsors can tap into this demand by offering new types of ETFs, such as inverse and fixed income funds.
MiFID II preparations
The approach of MiFID II implementation on 3 January 2018 is inevitably preoccupying many buy- and sell-side firms. The unbundling of research and trade execution commissions is forcing money managers to choose the most appropriate method to account for research costs under the new regime. Competitive pressures suggest that many buy-side firms will feel compelled to absorb broker research expenses directly through their profit and loss accounts, rather than pass them on to their clients.
Best execution methodology for non-equity asset classes is also a major consideration across the industry. There seems to be a consensus that simply replicating the process used for equities is insufficient and inapposite for other types of securities, particularly fixed income. The regulators appear to recognise this, and the intention of the new rules points to firms showing a clear methodology that consistently aims to achieve best execution, rather than best price in all circumstances.
Furthermore, it is widely agreed that greater automation and electronification of trading, which MiFID II implies, will be beneficial. Processes will be more efficient, transparent, auditable and professional.
Nevertheless, there are still areas of uncertainty. In particular, the role of systematic internalisers will need to be assessed and there is likely to be pressure to ensure there is equivalence with other liquidity sources, such as exchanges.
New technologies
There are clearly important megatrends that will affect the future of stock trading. Most notably, the wealth of information increasingly available is prompting the formation of new technologies and the development of systems to process, analyse, understand and apply these swelling data sources, both structured and unstructured, to enhance trade execution. Meanwhile, cloud technology is also changing the nature of connectivity between counterparties.
Curiously, considering the size of its resources, the financial industry lags behind other industries in its application of new data analysis techniques – although tighter regulation compared with the controls on pure technology companies might explain its loss of ground.
For instance, a failure caused by the unsupervised use of AI would likely arouse widespread political fallout, so it makes sense for the financial industry to incorporate it more slowly and in a more circumspect fashion. Moreover, respect for client security means many front office applications must stay outside the cloud, while economics dictates that investment in technology is determined by immediate client demand rather than long-term research projects that are not guaranteed to garner a financial return.
The application of AI and machine learning has become a regular discussion topic at finance industry conferences. However, as several speakers pointed out, these are not new technologies. Instead, a confluence of factors has made them more significant in recent years. These include the expansion of computer processing power, democratisation in the investment industry, increased information accessibility and the development of different skillsets among a new generation entering the industry.
Certainly, AI and machine learning technologies will have an increasingly important role in the trading cycle. The more controversial issue is whether or not they will eventually take over the whole investment process.
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