3 Definition of a Best Execution Process Model
3.1 Determination of Relevant Factors and Their Weight
Best Execution Factors. Condition precedent to formulate a process model is to describe the factors referred to in Article 21(1): price, costs, speed, likelihood of exe- cution and settlement, size, nature or any other consideration relevant to the execution of the order, hereafter best execution factors.
Since liquidity and transaction costs are considered to be major indicators of mar- ket quality, we define the factors in reference to Harris’ liquidity dimensions [11].
Furthermore, we concentrate on a disjunctive differentiation of the factors.
Prices of financial instruments consist of bid and ask. By considering the spread (breadth) as a benchmark, the factor price reflects one major part of implicit transac- tion costs.
The factor costs comprises explicit costs which can be divided into external and in- ternal costs. External direct costs are composed of taxes and fees which accrue for accessing venues and completing transactions there (e.g. commissions). Internal costs have to be considered whenever a firm’s execution policy allows for more than one execution venue [12]. In this case investment firms have to incorporate their own commissions into the execution policy.
Speed denotes the time period between placing an executable order and the actual execution by the venue. If an order is not immediately executable, speed refers to the time elapsed between the moment the order is theoretically executable and the actual execution. Therefore, the factor speed is related to the liquidity dimension immediacy.
Furthermore, opportunity costs are being implicitly considered. Speed deficits in- crease the risk of indicated conditions being already obsolete when an order is actu- ally executed.
Likelihood of execution and settlement addresses the risk of an order not being executed at the indicated price. The more liquid a venue, the more likely an order is executed. Thus, this factor is mainly affected by the depth of the order books.
The factor size is confusing since it seems to describe a feature of the customer’s order instead of the venue’s quality. Therefore, size must be interpreted as the ability of a venue to execute orders without affecting the price (“market impact”).The market impact is often responsible for the bulk of transaction costs if orders are large.
The factor nature of an order has to be interpreted as well. Its wording is equally misleading since it circumscribes characteristics of the order. In contrast to size, there is no reasonable interpretation. The nature of an order is part of the order itself.
Evaluating a venue by means of an order’s nature is not possible so that this factor takes an exceptional position as an exclusion criterion.
Any other consideration relevant to the execution of the order allows investment firms to define further criteria if they have an impact on best execution (e.g. security features like market supervision or safety measures).
Best Execution Criteria. In the next step, investment firms have to weigh the afore- mentioned aspects according to their relevance. We examine the degree of detail the best execution criteria must hold below.
Characteristics of the clients are being explicitly defined; the differentiation be- tween retail clients and professional clients complies with MiFID’s requirements.
Characteristics of the client orders include any characteristics of an order that de- termine its execution. Article 21(6) explicitly mentions size and type of order. Type of order refers to the status as a limit order, market order, or other specific type of order.
For size evaluation purposes we suggest to introduce intervals whose size each in- vestment firm has to individually settle according to their service and customer port- folio. Some evidence can be found in Article 26 of the implementing regulation [3]
where the retail order size is limited to 7.500€€ . According a firm’s customer topology, two intervals I1[0;7.500€€ ) and I2[7.500€€ ;∞) might sufficiently reflect customer needs.
The characteristics of financial instruments are probably the most important. In order to handle complexity, investment firms should define product groups within classes of instruments that aggregate financial instruments with similar or identical features.
The characteristics of the execution venues appear to be a foreign object compared to the other criteria. This criterion has been put at an unfortunate and misleading posi- tion, since it actually is the task of an execution policy to identify the best possible venues using the weighted factors relevant to best execution. The weighting deter- mines the execution venue; consequentially a venue simply cannot be a best execution criterion. Thus, the legislators’ intention must be interpreted. We suppose that the characteristics of an execution venue circumscribe the matching of the weighted fac- tors (step 1) and the evaluated venues (step 2).
Weighting of the Best Execution Factors. Fig. 1 gives an overview of the best exe- cution factors and weighting criteria that have to be included in the execution policy.
The characteristics of the execution venues will be considered in the third step of the process model. The nature of an order as a best execution factor is an exclusion criterion and must be reflected whenever concrete client orders are being executed (cp. section 3.4).
In fact, the best execution factors have a different importance, e.g. in respect to dif- ferent order sizes. As an example, let’s consider the factor size which reflects the market impact. The execution of client orders being larger than the size allocated to an indicated quote at a specific venue accounts for a deterioration of the achieved average execution price. Thus, the market impact can account for the largest propor- tion of transaction costs when it comes to the execution of large-volume orders [13].
Each investment firm is obliged to keep appropriate weightings for all hypothetical shapes of client orders. To this end, possible client orders should be classified into
order groups using the best execution criteria. Subsequently, a specific weighting vector wrh for each order group h can be configured dependent on the applicable cus- tomer needs.
Characteristics of the client
Characteristics of the client order
Characteristics of financial instruments
Characteristics of the execution venues
Price Costs Speed Likelihood
Nature
Other considerations Retail
clients
Size of order
Interval 1 … Interval n Product group 1
Product group m
…
Matching of weighted best execution factors and execution
venues Type of order
Exclusion criterion when choosing execution venues Professional
clients
Size
Fig. 1. Relevant best execution factors and criteria
In the course of this procedure some combinations are likely to get identical or very similar weighting vectors. Inter-product group consolidation of these combina- tions into order clusters would in fact make the weighting of the execution factors more compact. However, the allocation of execution venues would turn much more opaque since venues have to be tested for their best execution potential regarding individual product groups2. For the sake of clarity, we refrain from further clustering of order groups although clustering within product groups would not cause any issues.
Table 1. Example of weighting best execution factors Characteristics of the client
Best execution factor Retail client (A) Professional client (B)
Price (w1) 0.4 0.3
Costs (w2) 0.4 0.3
Speed (w3) 0.1 0.2
Likelihood (w4) 0 0.1
Size (w5) 0 0
Other considerations (w6) 0.1 0.1
To visualize a specific weighting vector, we have to hold all criteria constant ex- cept for one. The following matrix shows an exemplary weighting, considering the product group limit orders in liquid domestic shares up to a transaction volume of 7.500 €€ . We differentiate retail and professional clients (Table 1). This example does not claim to be accurate. We do not propose a universally valid methodology to
2 It is unrealistic to assign the same performance to a trading venue for different product groups.
specify the weights since the correct weighting shall not exist anyway since every investment firm has its own peculiarities.
For both column (A) and column (B), a separate order group h with weighting vec- tor wrh=(w1h,w2h,K,whn) should be created.