The Future of Trading is Faster than Ever; The Network is More Important than Ever

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David Walsh Bronxville David Walsh Bronxville
With the explosion of data, the growth of cloud-based platforms, the rise of automated systems, more stringent regulations, new digital currencies, and the continued globalization of exchanges and alternative trading domains, change is the only constant when it comes to supporting professional traders. Ultimately, identifying and demonstrating best execution will continue to be one of if not the most important competitive advantages for the rapidly evolving trading ecosystem, and the support of algorithmic platforms and services will require more speed and security than we’ve witnessed up to this moment – this New Year 2020 and the arrival of the third decade of the 21st Century. Technological advancements over the last twenty years have generally made markets more efficient, more accessible and more transparent. While we’ve experienced significant periods of volatility, particularly in 2008 when the global markets nearly collapsed, computer systems have continued to improve, supporting innovation in trading applications, and driving the need for faster fiber optic networks able to handle “pervasive” computing. The definition of real time has changed with the growth of high-frequency trading, for example, when milliseconds mean millions. For example, there is one fiber-optic cable laid between the New York and Chicago exchanges running 827 miles simply to gain the advantage of the fastest possible speed. Computer programmers are writing code which enables the execution of trades thousands of times faster than any human can. While some continue to argue that better technology and faster networks make markets less accessible and competitive, we are seeing startups causing incumbents to step up their game to provide better services to their clients, from retail investors to the largest institutional investors. With an increasingly ubiquitous, faster and more affordable Internet, and the ability to secure Internet transport, the good news is that access to more information and cheaper access to markets is available to all. Let the games continue! The buy side’s ability to execute equity trades using algos, and the sell side’s ability to automatically respond to a request for quote in the bond market is one example out of hundreds which enable trading desks to operate more efficiently and improve execution quality. In 2020 and beyond, expect to see data sets growing even larger, and the use of complex analytics, including AI and Machine Learning, to support asset managers seeking the best price on a trade and working with the best counterparties. Given large investments in more sophisticated trading systems and real time analytics which take advantage of cloud economics, we’ve only scratched the surface with the world’s top capital markets developers seeing AI as one of several disruptive technologies that will play out early in this new decade. No disruption comes without risk, so we will see parallel investments in, and development of solutions focused on cybersecurity, risk management, and regulatory oversight which will make auditing and compliance also more automated and simpler to in the coming years. The last decade brought with it some very hard lessons associated with the need to further strengthen risk management in order to avoid catastrophic events like the London Whale. Firms must apply at least as much real time analytics for risk management as they do for trading transactions to support continual “self-examination” before they wake up to massive frauds or system breaches that can destroy their brands and businesses. We cannot leave cryptocurrency debacles out of this equation, nor can we ignore the huge potential of tokens; regardless of the type of currency, be it fiat or non-fiat, the same principles apply: speed, security and systematic software applications are the future of more stable and sustainable traded markets. Real-time pre-trade analytics will allow traders to make more informed execution and counterparty decisions in the moment, with the results of these decisions fed back into analytics platforms, making not only the traders but the pre-trade analytics smarter with every trade. While this may seem tactical given the enormity of technology innovation, those who are experienced on “Wall Street” will confirm that while strategies are key, improving tactical operations can make all the difference, especially when it comes to the human relationships which will never disappear from the financial services industry. As has been the case in both our private and business lives, cloud computing, high-speed Internet, enterprise blockchain and distributed ledger technologies will continue to profoundly impact how work gets done, especially taking into consideration that millennials have grown up as digital natives, and have experienced the impacts of “AI”  throughout their lives, whether Spotify recommends songs, Amazon recommends books, Whole Foods recommends foods, or Grammerly corrects every text message and email your produce thus “perfecting” your work with your having to know grammar at all. A study in 2019 by Greenwich Associates stated a whopping 61% of respondents to their survey of trading professionals said they are either using AI today or plan to in the next 12–24 months. Those firms are hiring PhDs in physics and particle science, knowing they still have a long way to go when it comes to data architecture and data integrity. Fintech is continuing to experience explosive growth, and the use of AI in execution algorithms, and the analysis of structured and unstructured data, are starting to learn traders preferences and behaviors, and while we are nowhere near the scale use of AI as we see in the “Google” world, given the fee pressures and tough market conditions the buy side is facing, many are forcing their trading counterparties to make investments in AI. Done with quality and commitment, improving pre-trade analytics, enhancing systems with intuitive, real time big data visualization tools and innovating new risk modeling approaches can dramatically improve the efficiency and profitability of trading desks.  This decade, the stakes will grow even higher, as disrupters leverage advances in cloud computing, big data, cybersecurity, and AI – along with ultra-fast broadband networking, with all the bits gravitating towards the fastest fiber routes, as the only way to remain relevant in the future. Trading will continue to change but given my personal experience in the world of trading systems and networking over the last three decades, I believe the future will always be defined by the relationship of human talent and technology innovation. While trading desks on the buy and sell side will succeed or fail in large part due to personal relationships and humanly conceived strategies, the finer edge will be gained or lost based on the systems and high-speed networks chosen and put to work to support the work of future traders.

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