Financial marketsDoes The Partnership Between Google and CME Cloud Favor High Frequency Traders.

Kennnedy MuturiFebruary 1, 202347210 min

Traders’ investments could be thrown off by a partnership between Google and CME Cloud.

According to industry observers, CME Group Inc.’s intention to shift core trading systems to Google Cloud could upend hundreds of millions of dollars in traders’ communications and data centre expenditures.

According to Larry Tabb, head of market-structure research at Bloomberg Intelligence, high-frequency traders and other CME users have spent years developing state-of-the-art systems suited for extremely time-sensitive markets. Latency, or the time it takes for these systems to respond, is measured in millionths of a second or less.

Just previously, it was assumed that the cloud would be unsuitable for high-frequency trading. Companies rent access to shared computing infrastructure in the cloud, which may be accessed from many places. The cloud is typically used for more minor time-critical business operations like surfing, email, streaming video, and even supply-chain management. High-performance corporate applications rarely require the same level of performance as high-frequency trading.

CME and Google, a subsidiary of Alphabet Inc., signed a 10-year deal on Nov. 4 to shift CME applications to the cloud. The apps will be moved to the cloud in stages, with the main trading systems being the first to go. CME and Google will have to recreate the cloud systems that match the ultra-low-latency performance of technical trading infrastructure before that can happen.

“This is a more difficult cloud migration than typical,” said Philip Moyer, Google Cloud’s vice president of strategic industries.

A cloud-enabled exchange, if successful, may cut operating expenses and lead to the establishment of new revenue-generating data goods and services, according to Mr Tabb.

According to the company, the agreement will help CME bring on new users faster, streamline operations, and develop new tools using Google technology, such as artificial intelligence software for monitoring market risks.

Moving core trading systems to the cloud, according to Mr Tabb, will “upend the persons who heavily leveraged the CME data center, which include active traders in futures markets, their brokers, and technology providers, as well as active stock traders who rely on high-speed data from the CME.” Customers of CME will have to rebuild their systems to work in the new environment if the exchange’s trading infrastructure is shifted to the cloud, according to Mr. Tabb. However, Nasdaq Inc.’s chief technology and information officer, Brad Peterson, believes the cloud benefits exchanges.


“The global pandemic has strengthened our view of the benefits of our cloud transition,” he said, citing greater elasticity, scalability, and speedier innovation while retaining market robustness and integrity. Last year, according to CIO Journal, Nasdaq intended to shift its markets to the public cloud over the next decade. “These are early days since our announcement,” a CME spokesman stated, “and we don’t have any details for you beyond the release at this moment.” Google Cloud said, “We are thrilled to work with CME to overcome these difficulties.” It declined to elaborate on the challenges of moving to the cloud.

According to David Lariviere, a professor affiliated with the University of Illinois at Urbana-colleges Champaign’s of engineering and business, larger trading firms frequently rely on proprietary software that works with customizable hardware, giving them control over the speed and consistency of their trading algorithms. He estimates that reworking the hardware for a cloud-based environment will take a significant amount of time.

High-frequency trading firms frequently co-locate their servers with the exchanges in the same physical data centre. According to Michael Persico, CEO of Anova Financial Networks, a technology provider that runs communication networks used by high-frequency trading firms, the traders’ technology infrastructure is connected to the exchange using as close to equal lengths of cable as possible so that all traders communicate with the exchanges with equal delay. The Wall Street Journal said that Google Cloud Chief Executive Thomas Kurian and his colleagues were working with CME engineers to ensure that the exchange’s new cloud-based infrastructure would meet trading firms’ latency standards.

To maintain the proper operation of markets, trading businesses also demand that they obtain market data from exchanges as near to the same time as feasible, according to Mr. Lariviere. This is accomplished by a multicast method in which an exchange delivers market data to trading businesses and data suppliers, who then spread it to remote trading servers. Historically, the cloud hasn’t supported IP multicast protocols, he explained. Amazon Web Services, the cloud computing branch of Inc., is aiming to offer multicast capabilities. Last year, the company announced that it had completed a test of such a system with Singapore Exchange Ltd. and Aquis Exchange, a European market operator.

Amazon did not return requests for comment.

Mr. Tabb believes that if CME and Google Cloud succeed in transferring their trading engines to the cloud, it will pressure specialized companies that serve the exchanges.

Communications firms, such as Anova Financial Networks and companies that sell trading software and other services to traders and brokers, help traders.

Mr. Tabb believes that if the exchange industry shifts to the cloud, some enterprises may become obsolete. Others may need to re-engineer their platforms and connections to accommodate the cloud.

Mr. Persico of Anova Financial Networks sees it as an opportunity. “Well-run businesses with brilliant employees and a track record of innovation will do OK,” he said.

Kennnedy Muturi

Ken is a Quantitative Trader with experience in investments, quantitative finance, financial modelling and algorithmic trading in Global Investable Markets (GIM). He enjoys using Bayesian Statistics, Time Series and Machine Learning in developing Robust consistent Alphas in Equities Market, FX, ETPs and Derivatives instruments. He enjoys deep dives in understanding High Frequency Trading infrastructures and improving how the African financial markets work. He holds a Bachelor's in Actuarial Science from Strathmore Institute of Mathematical Sciences : An Executive Program in Algorithmic Trading (EPAT) certificate in Algo Trading from QuantInsti : A current MSc student in Financial Engineering at World Quant University.

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