Driving competitive advantage through FX TCA

“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.

Examining the WM/Reuters London Close through the Prism of Foreign Exchange Transaction Cost Analysis

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 literature,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.

TCA – No Argument?

In this interview from the Winter 2012/13 issue of Best Execution magazine, Jim Cochrane talks about the challenges of achieving best execution in the FX market.

FX traders push for greater transparency into execution processes and costs

While pricing more thinly traded currencies or emerging markets may be challenging, traders can now insist on certain measures in order to better understand the quality of their executions. Sean Hefkey offers some timely suggestions.

Algorithms for FX trading turning buyside into price makers, as well as price takers

The challenges of creating algorithms for FX trading are many, with no central limit order book, depth of book or volume information to draw upon. Firms are using new market microstructure knowledge and market data to move away from the historically manual FX processes to more automated, anonymous electronic trading.

FX regulatory environment sees massive shifts with future still uncertain

In the historically unregulated FX marketplace, trading practices have carried on in the same fashion for many decades, with a few major dealers dominating. By its very nature, FX trading transcends borders and therefore, has not come under the regulatory scrutiny that other asset classes have.

The Genesis of the Multi-Asset Trading Platform

The benefits of multi-asset system are undeniable—reduced possibility for data entry error, consolidated compliance, enterprise-wide risk management, and standard benchmarking for trading—not to mention seamless integration of data and workflow.

Constructing Fair Value Adjusted Indexes

For funds holding securities that trade on foreign exchanges that close before the US market, the usual method of computing Net Asset Value can result in stale fund prices. Some speculators profit from stale pricing to the detriment long-term shareholders. To solve the “mutual fund timing” problem and comply with SEC guidance, mutual fund companies are using fair value models to adjust the closing prices of foreign securities. Two challenges arise in implementation: (1) Fair value pricing creates tracking error relative to a benchmark index that uses stale foreign closing prices, and (2) Fund groups differ in their use of fair value models, distorting short-run peer comparisons. I argue that the implementation of fair value pricing across the financial industry would be expedited and simplified if public benchmark providers were to produce fair-value adjusted indexes. Such indexes are straightforward to produce and use, as demonstrated here, and would help coalesce pricing around a common industry standard.

I am very grateful to Richard Leibovitch for his invaluable comments and suggestions. I also thank Konstantin Zalutsky for expert research assistance. The information contained in this communication is for informational purposes only and has been compiled from sources, which we deem reliable. ITG Inc. does not guarantee its accuracy or completeness or make any warranties regarding the results from usage. All information, terms and pricing set forth herein is indicative, based on among other things, market conditions at the time of this writing and is subject to change without notice. Additional and supporting information is available upon request. ITG Inc. is a member of NASD, SIPC.

Mutual funds provide liquidity on a daily basis, allowing investors to transact in fund shares at the fund’s Net Asset Value (NAV). For funds holding securities that trade on foreign exchanges that close before the US market, the usual method of computing NAV, at 4:00 p.m. Eastern Time using closing prices for the day, can result in stale fund prices. In the case of US mutual funds holding Japanese stocks, as much as 15 hours can elapse from the close in Tokyo at 1:00 a.m. ET (3:00 p.m. in Japan) to the US close at 4:00 p.m., as shown in the time line below. Although European stock prices are less stale, the same issues arise as European exchanges close between 11 a.m. and 12 noon, ET.

Read the full paper

Implementing Fair Value Pricing

Mutual fund transactions occur at the fund’s Net Asset Value (NAV), typically computed at 4:00 p.m. Eastern Time using closing prices for the day. For funds whose securities trade on a foreign exchange that close before the US market, this convention can result in stale prices. Some shortterm speculators take advantage of stale prices, trading on information signals observed after the close of the foreign market and before the US market closes, earning substantial profits at the expense of long-term shareholders. Fair value models, that suggest adjustments to the closing prices of foreign securities based on information after the foreign market closes, provide a solution to the “mutual fund timing” problem.

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