Measuring MiFID II: The Right Way To Judge Its Success
By Mark Northwood, Principal, Bips Global
A rigorous analytical approach is essential to quantify the impact of MiFID II on trade execution.
Much has been said and written about the challenges that all firms have had to overcome to comply with the numerous articles, technical standards and ongoing clarifications of the Markets in Financial Instruments Directive (MiFID) II, as well as the enormous implementation cost borne by the industry.
But that is only half the story, and now that we are in the post-MiFID II world, the European Securities and Markets Authority, the national competent authorities in each country, and the industry itself should begin figuring out how to assess whether or not the changes have achieved their objective.
The European Commission’s primary goal was to improve things for investors: the individuals, funds and other entities that put up the capital that the issuers of equity and debt securities need. Therefore, the cleanest approach is to measure the impact MiFID II has had on the investment outcomes for these investors, and ask: Was it worth the collective cost and effort in terms of measurable benefits to them?
One area where it should be possible to build a sound, quantitative judgement of the impact of MiFID II on investors is in trading. Best execution should get better. Everyone from the chief executive officer and chief investment officer down (as well as investors themselves) should be curious to know the actual verdict. Traders will need to be ready to provide it, but how?
Analysing trade data
The answer will be found in each firm’s trade cost data, and is simply expressed as the change in average implementation shortfall for each order segment. However, these numbers will only be valid if the data collection and analytical approach is rigorous and sound.
For equity investors, this will be about ensuring that any comparison of implementation costs before and after MiFID II is statistically robust. This means having a sufficient sample size and controlling the execution process so that similar orders are executed in a similar way. In practice, this is only likely to be achievable at those firms that have adopted a systematic approach to their order handling, which provides a consistent strategy selection based on the characteristics of each order, thus narrowing the number of variables.
For other asset classes the analysis will be more dependent on the extent to which those firms have been collecting quote data in the securities they have traded in recent years, because the arrival price is the key reference data point that is required. Beyond that the analytical approach will be similar to equities and requires that the characteristics of each security and the individual order drive the sampling approach for building the cost comparisons.
Some data is of course better than none, and a judgment based solely on “feel” will no longer be sufficient.
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