2 min read

Finding Market Intelligence and Signals in Data

Finding Market Intelligence and Signals in Data

traders and portfolio managers need to have tools to  provide meaningful market intelligence that informs the investment and trading decision. 

The recent macro environment has made investing far more complex, with an ever increasing set of factors that need to be taken into account. From Fed announcements, rates and budget decisions, to ESG and counterparty risk, portfolio managers and traders have to analyse ever-increasing amounts of data. 

With current market conditions and volatility, traders and portfolio managers need to have the right tools — tools that go beyond simply providing an indiscriminate firehose of data and instead provide meaningful market intelligence that informs the investment and trading decision and highlights dislocations in the market. 

Thomas Yasin, Liquidnet

Thomas Yasin, Regional Director EMEA, Liquidnet Investment Analytics, said “In markets like these,  investment decision makers often need to react quickly to fast changing events and spot key signals that can influence those decisions. The buy side wants data and analytics that do not just help with the execution decision, i.e. how, where and when to trade but also the investment decision, i.e. what to trade.

Yasin continued Firms are increasingly looking for data and analytics that can glue together different parts of their organisation, portfolio management and stock selection, performance and risk management, and execution. Fee and margin compression means the buy side needs to make their workflow more efficient and more automated.”

The big technology challenge many firms face today is the effective harmonization of data and ensuring that revenue-generating functions have access to the right data from different departments. 

“The Cloud has helped with the collection and hosting of data, but connecting it with all the integrated tools that financial firms use to trade is a significant challenge,” explained Yasin. “For example, portfolio managers want to find the right stocks that best fit their asset allocation goals, risk profile, time horizon and fund mandates, and often need tools that can highlight longer term dislocations. Traders want to execute those orders in a time horizon and manner that helps them obtain Best Execution.” 

According to Liquidnet, this is an area where Liquidnet Investment Analytics can help, with analytics and signals to look at not just whether a stock should be traded but how it is traded, where it is traded and how aggressive or passive in the market the firm should be.

Yasin said “There are also different approaches depending on the firm. For example, some investors are long-term holders of stocks and are not interested in analysing intraday factors, while for others intra-day liquidity is extremely important such as tracking lit versus dark volume, or assessing participation rate and market impact cost.”

Liquidnet introduced its Investment Analytics offering in 2020, following the acquisition of  Prattle and RSRCHXchange in 2019 and OTAS Technologies in 2017. Investment Analytics combines a range of AI-driven analytics, machine-learning, and natural language processing technologies to enable more efficient decision making.

“A lot of firms are realising they want to specialise in what they do best, which is investment management,” said Yasin. “They do not want to be, or have the resources to be data or technology houses and so require vendor solutions to help them in their technology journey.”

 

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