Direct Edge Selects FINRA for Market Surveillance

With the Addition of Direct Edge, FINRA Will Have Surveillance Oversight of More Than 90% of U.S. Equities Trading JERSEY CITY, NJ and WASHINGTON, DC — Direct Edge®, the third largest stock exchange operator in the U.S.

via Pocket http://www.finra.org/Newsroom/NewsReleases/2013/P265419 May 23, 2013 at 06:51PM

Opacity Through Transparency: Why Traditional TCA Needs to Change

Opacity Through Transparency: Why Traditional TCA Needs to Change
Transactional transparency in the US equities market is higher than ever. But as orders are increasingly sliced, venues fragmented, and timescales compressed, we are no closer to providing clarity into our complex execution process.
Unquestionably, the US equities market is more transparent than ever before. Every order is electronically submitted, routed and matched. Each execution has a unique number, timestamp and audit trail. We know exactly what time orders are submitted, when they hit the trading desk, who they were given to, which liquidity pools they were routed to, their execution times, and how these trades eventually were allocated, confirmed, cleared and settled. Each execution increasingly can be analyzed down the microsecond.

While transactional transparency is higher than it has ever been, however, market opacity is murkier than ever. As institutional orders are sliced and diced into fractional executions, the quantity and granularity of transactional data make it increasingly difficult to tell the forest from the leaves. Though every execution has an audit trail, like the fractured Humpty Dumpty, putting all the pieces back together seems increasingly out of reach.

The inability to put together these pieces degrades traders’ ability to understand the market, their executions, who they are trading with, and how (or if) they are being gamed. TCA is not enough

While Transaction Cost Analytical tools initially helped traders better understand their execution quality, increasingly, traditional TCA tools have no ability to solve the complex challenges created by heavily fragmented, message-overloaded, microsecond-based markets. TCA tools were initially developed to help money managers and plan sponsors more easily manage trading costs and the impact of their investment decisions. While traditional TCA solutions were created to analyze data on a quarterly basis, over the past decade they have expanded to leverage daily data to help traders benchmark their performance against a host of market measures, such as volume weighted average price (VWAP), implementation shortfall (IS) targets, and other standard (or, for that matter, customized) benchmarks.

With larger orders being sliced and diced into hundreds or thousands of child orders, and individual child orders being routed to multiple destinations (which then can subsequently route to multiple locations), a single order can spur thousands of electronic messages as child orders ping-pong around the market looking for the other side.

As trading technology becomes faster, and matching engines migrate from milliseconds to microseconds (millionths of a second), even more messages are needed. In addition, the faster the market gets, the more critical and difficult clock synchronization becomes — synchronizing server timestamps across a non-synchronized execution fabric is a complex technical problem.

Message overload, however, is not the real issue. The challenge is, everyplace a message is sent, footprints are left. These footprints can leak valuable information, which can degrade the execution. To reduce market impact, algorithms and routing engines need to be more sensitive to how orders are sliced and where they are sent, and manage the impact of these small child orders on overall execution quality. Eventually we will be at a point where we can measure this impact in real time and adjust one’s routing strategies accordingly.

In this complex world, measuring transaction cost needs to take into consideration venue analysis. Traders must understand not only which algorithms to use, and how each algo should be set, the technology needs to analyze how each algorithm routes, each venue’s order types, and how these order types either protect or expose that trade to various liquidity sources, as trading venues, exchanges, and dark pools each have their own unique footprint.

For buy-side firms, the level of data needed to analyze these issues may be more data than they can either process or, for that matter, even generate. If a firm does not actively trade a significant number of names, there may not be enough information to obtain a composite picture. Given the number of venues and algorithms, even larger firms may not trade through enough brokers, in enough venues, with enough names to get the full picture.

We once imagined that, if machines could be substituted for paper tickets, the information we could glean from automated data would make us all into better traders. However, not unlike the strategy of obfuscation through data overload, the goal of transparency through automation has brought us no closer than before to providing clarity into the opaqueness of our complex execution process.

Victory, unfortunately, always seems one more step away. But that, I guess, is the nature of progress: Simple answers are few, and solutions are always one more broken eggshell away.

Market opts for cautious US circuit breaker rollout

A potential two-month delay to the implementation of enhanced circuit breakers designed to combat volatility in US equities will help the industry adjust to the new mechanisms.

via Pocket http://thetradenews.com/USA/newsarticle.aspx?id=6442451270 January 09, 2013 at 06:47PM