MIFID II Best Execution with Kx

MIFID II Countdown: Best Execution and Kx Technology

21 Feb 2017 | , , , ,
Share on:

by Michael Gorman


The time for general discussion of MiFID II is now over for European banks, trading venues and asset managers with deployment mandated for less than a year away. Market participants have earmarked budgets, with tier one banks alone expecting to spend $40 million each to comply with the new rules, and the process of retooling and designing new infrastructure from the ground up has begun.

Commentators and vendors have spilled much ink about the requirements in, and the implications of, the new rules. Less concentration has been paid to the practical, implementation requirements for meeting best execution. Given where we are on the calendar, it is time to start organizing for implementation.

MiFID II and Best Execution

It is often said that MiFID I was about the ‘spirit of best execution.’ Under MiFID II, that spirit has morphed into ‘quantitative proof of best execution’ for clients who request it, regulators who audit it, and the service to which it must be reported (e.g., systematic internalizers reporting under RTS 27). Coupling this changing paradigm with MiFID II’s extended instrument scope into non-equities creates challenges for implementation that the entire industry is now facing.

Let’s address a few key implementation issues:

Data Capture

MiFID II, from a policy perspective, seeks to push OTC markets to venues. Accomplishing this requires changing attitudes and increasing the cost of continuing to operate bilaterally. This is quite clear for firms who choose to, or by definition, will be systematic internalizers for certain financial instruments.

FX markets are a good example. Most firms employ manual trading techniques, i.e., employ voice trading where all quotes are not captured. For firms that anticipate being a systematic internalizer, MiFID II is going to require new policies, procedures, and workflows — demanding a cultural shift on the trading desk. Additional build is also likely necessary to capture quotes. Depending on the trading platform, a simple manual GUI, like Kx for Flow, can ease the way to comply, allowing them to quickly capture the prices they quote to clients by phone or chat. This manual GUI would capture data like trade type, currency pair, bid or offer, price, volume, etc. Most firms are looking to deploy these with as much automated fill as possible—to reduce time and cost of compliance.

With a system built on Kx technology, which seamlessly scales to many terabytes of data, there is no loss of speed or performance as volumes rise.

Proving Best Execution — Employing TCA?

Another key challenge is what tools does a firm employ to demonstrate ‘quantitative proof of best execution’? Transaction cost analysis (TCA) has been refined in the equity markets, where it uses a small number of highly liquid instruments with known and trusted pricing sources to provide a robust metric for firms to employ.

As we know, the fixed-income markets operate differently. Trades are larger and less frequent than in equity markets, making TCA more difficult (but not impossible) to deploy. But quite similarly to the equity markets under MiFID I, the industry is seeing more electronic trading in fixed-income, which in turn is creating greater amounts of rich market data to employ in tools like TCA.

Increased electronic trading is occurring across all non-equity asset classes, spurred by the regulatory requirements in MiFID II (and in other jurisdictions). From an implementation perspective, this is leading to considering vendors who not only possess a strong understanding of the asset classes but present extensible solutions that can incorporate new market data seamlessly, operate a multi-asset class environment, employ robust time-stamping and include market replay functionality to evolve as the amount of electronic trading increases. Many firms are looking for ‘strategic solutions’ as opposed to tactical ones deployed for prior regulatory change.

Reporting Best Execution

From an implementation perspective, software solutions that can handle regulatory reporting, in addition to providing quantitative analytic tools are particularly attractive. RTS 27 (for venues) and RTS 28 (for all investment firms) will increase data demands and, for some firms, will require new solutions to make the data available for reporting. Whilst reporting is not ‘real-time,’ both RTS 27 and 28 require marshaling more data and creating greater transparency for the market. Working with a software solution that has already mapped the data points required and can integrate seamlessly with reporting, and other key requirements of MiFID II best execution, will help to accelerate compliance in 2017.


Capturing and analyzing data for proving and reporting best execution is a key MiFID II challenge. What’s more, it cannot be considered in a vacuum. Any software solution implemented to satisfy these regulatory requirements must be flexible enough to account for changing market behavior and evolving market conditions. As we often say, regulatory compliance is about data and systems—having the right data available, understanding how it needs to be presented, and having systems with the functionality needed to send it where it needs to be.

To complement Kx Systems’ product solutions, the company is supported by First Derivative’s Regulatory & Compliance consulting practice, which combines subject-matter expertise, strong product knowledge, and data & technology DNA to offer a range of consulting services that can accelerate implementation for MiFID II and MiFIR. Read more here.

© 2017 Kx Systems
Kx® and kdb+ are registered trademarks of Kx Systems, Inc., a subsidiary of First Derivatives plc.


Kx collaborating with Fintech startup chartiq

Collaboration: The Dominant Trend in Finance

13 Dec 2017 | , , , ,

In December we are re-blogging some of our favorite content from Kx partners and affiliated companies, starting with this article on the ChartIQ blog. ChartIQ is an agile FinTech company that sells an advanced HTML5 charting library used in technical data analysis, trading configurations and for charting in the capital markets industry. Kx offers a ChartIQ integration as an addition to our Dashboards. In Collaboration: The Dominant Trend in Finance, ChartIQ’s Hanni Chehak writes about the rise of FinTech companies, and the role collaboration plays as FinTech companies are increasingly disrupting the traditional banking sector.

Water system workers with kdb+ historical database

Kdb+ Use Case: Machine Learning Water System Maintenance Application

6 Dec 2017 | , , , ,

Kdb+ is being used much more widely in machine learning applications today. Its ability to quickly ingest and process data, particularly large, fragmented datasets, is one way that developers are adding kdb+ to their technology stack of artificial intelligence and machine learning tools.
For Australian kdb+ developer Sherief Khorshid, who also develops machine learning systems, incorporating kdb+ into a predictive maintenance application gave him the edge in a hackathon win that landed him a cash prize and a contract with the Water Corporation of Western Australia.

kdb+ FFI

Kdb+ FFI: Access external libraries more easily from q

22 Nov 2017 | , , ,

Following on from the hugely popular Python library and interface embedPy and PyQ, Kx has released an FFI as part of the Fusion for kdb+ interfaces. As with embedPy and PyQ, this FFI is open-sourced under the Apache 2 license.
The kdb+ FFI is a foreign function interface library for loading and calling dynamic libraries from q code. It has been adapted and expanded upon from a library originally written by Alex Belopolsky of Enlightenment Research. With the kdb+ FFI you can now call your favorite C/C++ libraries directly from q without the overhead of having to compile shared objects and load into q using the 2: command.