n Expert opinion — Liquidnet
common knowledge that activity in dark venues
occurs in intense bursts. Peak dark volume often
rivals and sometimes exceeds lit market volume.
Liquidity transfer due to the activity of proprietary and institutional liquidity seeking algorithms
make lit and dark liquidity intimately intertwined.
Based on our observations we believe that this
entanglement of dark and lit liquidity often has
material impact on how less opportunistic, scheduled and participation algorithms may perform in
the wider market.
Opportunistic liquidity seeking can
outperform traditional rigid algorithms
Let us take a look at how traditional, lit-market only
algorithms trade two offsetting institutional orders
via VWAP or POV (Figure 1). Buyers and sellers drip
feed liquidity to the market. If there are no exogenous
disruptions, a fragile equilibrium exists. Relatively
balanced interaction between buyers and sellers
results in relatively stable price: both algorithms in
the end trade at an average price over an extended
time period. In this theoretical example the price
analytics which facilitate
efficient liquidity manage-
ment and identification of
trading patterns across dark
and lit venues. When a SOR
decides whether to explore
dark venues, to post lit,
or to take advantage of an
oversized lit offer, its activ-
ity ties dark and lit liquidity
together.
The dark liquidity
myth
The sanctity of the dark in
minimising information
leakage is considered vital
to buy-side institutions.
However, no two dark pools
are the same. Execution quality varies from one dark
venue to another and is never static.
Most dark liquidity is found in small, retail sized
chunks in Multilateral Trading Facilities (MTFs), broker crossing networks, and systematic internalisers.
It has been known for a long time that proprietary
high frequency trading across lit and retail sized
dark venues provides a transmission mechanism for
imbalance in dark to impact lit. Due to their proprietary, short-lived and bi-directional nature, their
price impact on markets is often contained. Modern
liquidity-seeking algorithms now perform a similar
liquidity transfer function in the institutional space.
The natural orders originating in large asset managers may have a more pronounced and less contained
impact on price.
Even though the nominal average dark volume
can be around 1/10 of lit volume in EMEA1, it is
Buy 350 shares, scheduled algorithm
Sell 350 shares, scheduled algorithm
Sha
re
s
P
r
ic
e
Time
Buyer Seller Price
FIGURE 1: LIT SCHEDULED ALGORITHM VS LIT SCHEDULED ALGORITHM
Source: Liquidnet
1. For example, according to BATS market share data (http://batstrading.
co.uk/market_data/market_share/market/) , on Aug 17, 2016 the 5-day
average lit and dark market volumes in EMEA were € 29.8B and €2.7B,
respectively. The latter did not include dark flow in Broker Crossing
Networks (BCNs). According to our data, BCNs may have added another
€500M or more of daily dark trading for this period.
Based on internal Liquidnet transaction cost analysis data since the
beginning of 2016 through July 2016.
