The Blotter (formerly known as Insights) cuts through the noise to explain the issues that impair your trading desk, undermine your investment process, and cloud your business strategies. Subscribe to The Blotter's RSS feed. Find our latest thinking on market structures, technology, and policy to take control of the information you need to set a course in the right direction.
“The most valuable commodity I know of is information” – to quote Gordon Gekko from the 1987 movie classic Wall Street. This line has never been more significant than in today’s data-fuelled financial markets, where detailed analysis of information can provide that all important competitive edge – both now and in the future. To achieve this, firms are looking towards Transaction Cost Analysis (TCA), which enables them to reduce costs and hone trading strategies.
The term ‘TCA’ has now become so common across the industry, and some would argue commoditized, that its value is in danger of becoming misunderstood. While most buyside firms use some form of broker post-trade analysis to measure how they’ve performed against their benchmark, the firms who are out-performing versus their peers are using a broader approach of pre-trade, real time and post-trade analytics to answer questions about how and why trading costs are incurred, and what actions can be taken to reduce them.
ITG Financial Engineering has recently completed its R&D work on international stock specific intraday volume profiles, extending its robust estimation methodology to common stocks and several other security types to cover more than 50 markets around the world.1 The intraday volume profiles, which include the estimated percentages of the daily volume to be traded in each 15-minute interval of the continuous trading session and at the and closing call auctions, are estimated for individual securities traded on each market and can be used for efficient execution of large orders.
Please find this article referenced in the Wall Street Journal.
Responding to many client requests, the FX team at ITG Analytics reviewed trade data surrounding the WM/Reuters London Closing Spot Rate Service (“the fix”). By observing the factors that influence trading costs using ITG TCA® for FX’s rich quote data we found trade patterns that were unique. Consistent with academic literature1,we show that volume and volatility around the fix spikes and the spread costs tighten temporarily. In addition, we see mean reversion of the FX rates on days when there is substantial price pressure shortly prior to the fix. Our analysis does not prove the allegations of manipulation brought about by some market participants.
This piece can also be found in the Summer issue of The Journal of Trading.
Shortly after the market opening on August 1st 2012, a single server owned by Knight Capital flooded the market with persistent buy and sell trades as it attempted to fill 212 small customer orders in 154 U.S. stocks. According to the SEC press release, the surge of trading activity caused by a faulty code deployment resulted in execution of 4 million child orders for almost 400 million shares during the first 45 minutes after the market opening. For 75 of those stocks, Knight’s executions exceeded 20% of the trading volume and contributed to price moves over 500 basis points (bps). For 37 of those stocks, the price moved by more than 10 percent, as Knight’s executions constituted more than 50% of the trading volume. The price impact of Knight’s trades resulted in large unwanted long and short positions and an estimated $461 million (mln). loss as Knight attempted to close these positions. As a result, Knight was forced to seek funding from external investors to stay afloat.
I recently received my copy of the Winter 2014 Journal of Trading. Quickly scanning the journal’s cover, I began flipping through to an article on real-time TCA visualization. I stopped, when I came across the title which I reuse for this comment. The Journal piece is an edited manuscript of a panel session of the same title held during a conference, organized by Robert Schwartz of Baruch College in New York. The participants, led by Andy Brooks of T. Rowe Price Associates, are well-known in the industry, and I recommend a read by anyone who did not see that crew in action.
Market participants do not need to be told that they are working in an era of Big Data. They experience it every day. However, developing an appropriate response is going to change the daily experience in a number of important ways. The relationship with technology will inevitably change. Internal relationships will be altered. And analytics will dominate any list of required capabilities.
On January 14th, Michel Barnier, the European Commissioner in charge of financial services in the European Union (EU) welcomed the agreement in principle reached on rule changes to the Markets in Financial Instruments Directive (MiFID II/ MiFIR). Barnier declared that although the speed of implementation was not ambitious enough, the agreement still represented “a key step towards establishing a safer, more open and more responsible financial system and restoring investor confidence in the wake of the financial crisis” (see: http://europa.eu/rapid/press-release_MEMO-14-15_en.htm?locale=en).
The unbundling of research and trading has been a discussion topic for many years both globally and in Asia. While in theory there are many good reasons to unbundle, the practical implications have often made it difficult for asset managers to do so. However now several important business factors are pushing Asia-based fund managers to review their processes and consider how they value research and trading, while using more sophisticated tools to manage and report on who and what they pay.
Traders commonly use market-on-close (MOC) or limit-on-close (LOC) orders to participate in the NYSE closing auction. An alternative mechanism is the D-Quote.Unlike MOC/LOC orders, which must be submitted prior to 3:45 unless offsetting a Regulatory Imbalance1, D-Quotes can be submitted or modified until 3:59:50,regardless of the current imbalance. Given the greater flexibility of D-Quotes, why don’t traders always use D-Quotes when participating in the close?