Trade Execution Challenges Buyside

Terry Flanagan

Trade execution monitoring is occupying an increasing portion of buy side trader attention as liquidity fragments and fulfilling best execution mandates becomes more complex.

In the U.S. it is now possible to trade stocks at 300 different venues. Of these, only 13 are exchanges, the rest are broker operated alternative trading systems (ATS) and other broker operated systems which are known as “dark pools” and account for over 35% of share volume traded in the U.S.

The number of dark pools has grown substantially in the years following Regulation ATS, which institutionalized the concept of alternative trading systems, and especially Regulation NMS (National Market System), which prevented “trade throughs,” or the execution of trades at prices inferior to protected quotations displayed by other trading centers.

Alex Hagmeyer, Franklin Templeton Investments

Alex Hagmeyer, Franklin Templeton Investments

“Because the tools to measure execution quality have improved dramatically over the past decade, there are a myriad of tools now available to analyze the execution quality of orders and broker placements,” Alex Hagmeyer, U.S. equity trader at Franklin Templeton Investments.

There are some vendors in the space which take in allocation level custodian data and compare average prices to simple benchmarks created from market data, Hagmeyer said. Other vendors leverage historical tick data and individual executions to make comparisons of each individual execution price to the market at the time of execution.

“Brokers and vendors are also now beginning to provide transparency into the execution venues that are accessed over the life of the order,” said Hagmeyer. “Whichever tool is used, it’s important to ensure that the methodology employed to analyze an order is in line with the trading strategy used for that particular order.”

ITG, an execution and research broker, recently launched Smart Trading Monitor, part of its Smart Trading Analytics suite. Smart Trading Monitor is a web-based dynamic TCA tool which enables institutional traders and portfolio managers to track global equity trading performance in real-time.

“Smart Trading Monitor is a powerful tool for institutional investors, allowing them to view and track execution performance with a high level of transparency and best-in-class monitoring tools,” said Ian Domowitz, head of analytics at ITG.

Institutional traders and portfolio managers can now monitor trader and broker execution performance across a broad range of benchmarks and regions, taking into account historical and current market conditions, as well as the statistical deviation between them. The tool provides users the ability to rapidly identify outlier or sensitive trades, drill down for specific context at the broker, venue or security level, and take corrective action if necessary.

Tick Data, a provider of historical intraday time series data for the equities, options, and futures markets, is expanding its packaging of historical data to facilities execution quality analysis following a management buyback of the company from Canada’s Desjardins Group.

“Our first objective will be to broaden our coverage,” said Neal Falkenberry, president and founder of Tick Data. “We will be adding new markets and asset classes into the containers of data that we provide to the trading community.”

As volumes of data grow, so do the challenges of storing and analyzing them. Hence, a move to the cloud is indicated.

“Today, we are in the business of shipping very large data sets of tens of terabytes,” Falkenberry said. “Progressively, data is getting too large to be shipped. By moving to the Amazon Cloud, we will be able to host data in the cloud and allow firms to access that data much more effectively.”

Tick Data’s main competition comes from the customers themselves. “Larger firms have streaming data coming in, and they archive those large feeds for research,” Falkenberry said. “One of the challenges with storing hundreds of terabytes of data is the risk of dropping packers, resulting in errors. So data quality is one of the primary reasons they seek us out.”

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