Transaction cost analysis, is exactly like
its moniker, it analyzes the cost of execution. This intuitively
seems simple. If the broker charges a $1,000 for execution, isnt
the execution cost $1,000? Well, not really. To accurately measure
the cost of execution you need to measure more than broker
commission and fees. Execution cost is typically segmented into two
major categories: explicit and implicit costs. Explicit costs are
fairly easy to measure in a transparent market. They are brokerage
commissions and spreads. If the broker charges you $1,000 and you
bought at the offer, your explicit cost would be $1,000 plus the
Features : FX Transaction Cost Analysis: Reality or Pipedream?
Larry Tabb outlines why there will be greater pressure on dealers
and execution platforms to open their data and generate the metrics
needed so firms can truly measure their trading costs.
Calculating implicit cost however is much more difficult. Implicit
cost is typically split into market impact, delay, and missed
trades. Market impact is the affect the order had in the market, or
how much a buy order has pushed the market higher / sell order has
pushed the market lower. Delay, is the amount the market has moved
between the acquisition decision and the execution price and missed
trades are the prints (other executions) that you unfortunately
were unable to participate in.
If you guessed that in the equity market, commissions were the
lions share of the cost, well you would be wrong. Actually, the way
Plexus (now a subsidiary of ITG) measures it, the largest aspect of
transaction cost in the US Equities market is delay, not
commissions, impact, or missed trades. The lost time between the
decision to buy and the actual purchase happens to be deadly.
Importance of Data
However, if by just reading this you guessed that transaction cost
analysis requires a significant amount of data, you would be
absolutely right. Equity TCA requires that you have the universe of
your decision-point time-stamped orders, when they were received by
the trading desk, how the trader segmented the order, how
.if you are trying to mathematically
analyze your FX trading cost down to the gnats eyelash - the data
is just not there to do a sophisticated analysis.
orders were executed or delegated, all of the executions associated
with the segmented order, and all of the market data associated
with every single order in the market, or at least the volume
weighted average price of all of the asset that traded that day.
This is a significant amount of data. The question is, is this data
available in the FX market, can it be developed, and by who? And is
this data really important to developing new and maybe more
interesting TCA in the FX marketplace.
For the most part, the majority of underlying data is not available
for traditional TCA in most over-the-counter marketplaces. There
are no unified markets or trading venues in over-the-counter
markets, so there is no unified execution tape. The market is not
only bifurcated it is tri or even quad-forcated (if that is even a
word). There is an inter-dealer market where dealers trade, a
credit-intermediated dealer market where hedge funds trade,
dealer-to-client electronic RFQ systems to the buy-side, and the
phone or single dealer market where the bulk of the dealer to
customer business is done. These systems are not linked together
and there is no central trade reporting.
Because there isnt a unified market it is difficult to benchmark
your trades. Who can definitely say that the price from your dealer
was or was not the best? While it may have appeared to be best
according to the market data platform, there may have been an RFQ
transaction, a dealer to customer trade, or even a phone-based
order that may have been better priced. This fragmentation also
makes it difficult to measure both impact and missed trades, as
there is no way to calibrate your executions against the market.
So the idea of FX TCA looks bad huh? Well if you are trying to
mathematically analyze your FX trading cost down to the gnats
eyelash - the data is just not there to do a sophisticated
To more fully obtain accurate TCA information the industry must
develop an execution tape, a list of all executions across all
execution venues (inter-dealer broker, intermediated inter-dealer
broker, multi-dealer RFQ platforms, and dealer to customer
transactions) that provides the time and date of the transaction,
the product, quantity, and the price with a credit normalization
field that allows for consistent data analysis across the
counterparty creditworthiness. Credit normalization of FX TCA will
be important as unlike equities, FX prices are predicated upon
The chance of this occurring in the immediate future is limited.
The market is segmented, the dealers and trading platforms have a
vested interest in keeping the data private, there is no consistent
protocol in which all parties communicate, and there isnt even a
regulatory body to force everyone to play nicely in the sandbox.
Improved access to data
However, that said, life is changing. The buy-side, though
automated execution platforms and market data providers has greater
access to data than ever before. Platforms, such as EBS Prime
provides intermediated hedge fund access to the inter-dealer market
and platforms such as HotSpotFX and LavaFX enable the buy-side the
ability to trade with each other through a two sided marketplace.
Technology can grab, capture and store streaming quotes to provide
measurable time series. And we are also seeing increasing demand
for benchmarks such as EBSs SmoothRate, which is about as close to
a VWAP rate for FX as one could hope for in a fragmented
That said, firms are also beginning to move away from average price
executions and move toward an implementation shortfall approach to
measure transaction cost. Implementation shortfall ignores VWAP and
benchmarks the order against a decision price, which was the price
at the time it was determined to trade the asset. So if the
portfolio manager, treasurer, or fund manager decided to buy a
currency when it was at a specific level, that specific level would
be the benchmarked price, hence acquiring it lower would be
positive and acquiring it at a higher price would be counted as a
negative. The challenge with measuring trading cost in this manner
is that while it does measure how well you did against your order,
it does not help you understand the liquidity characteristics in
the market and how to better trade that product the next time.
While more sophisticated implementation shortfall methodologies use
volume and time and sales data to measure market impact and missed
trading opportunities, one needs to start somewhere. And that
starting point seems to have occurred. With greater client demand,
there will be greater pressure on dealers and execution platforms
to open their data, provide unified access, and generate the
metrics needed to better understand execution, and only then will
firms truly be able to measure trading cost in a sophisticated
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