[ T H O U G H T
L E A D E R S H I P
|
G O L D M A N
S A C H S ]
DECIPHERING
GLOBAL EXECUTION
DYNAMICS FOR
OPTIMAL TRADING
I
n today’s increasingly com-
plex and inter-related market
environment, (i) information
dissemination is occurring almost
instantaneously around the world,
(ii) market participants and financial
products are more global in nature,
creating or reshaping linkages across
markets that didn’t exist just a few
years ago and (iii) the electronifica-
tion of trading is prevalent across
most asset classes. Against this
backdrop, algorithmic approaches
to execution are at an arms race
of consuming enormous amounts
of data, coupled with the need to
deploy more sophisticated models to
process, stratify and produce useful
forecasts out of such wealth (or
chaos) of information.
The quintessential pillars of any
execution modelling framework
are risk and transaction cost. More
passive, less impactful execution re-
quires trades to be more spread out,
thus carrying higher time risk. Con-
versely, to execute rather quickly
one would incur higher cost/induce
higher impact.
The question that naturally arises,
is, “how can we better model risk
and cost to optimally decide how
much and how fast one should
trade”? This quest of continuously
improving risk and cost models, as
well as optimisation processes, lies
at the heart of algorithmic research.
Below we highlight some of the
topics that our team, the Quanti-
tative Execution Services arm of
Goldman Sachs, has been tackling
and share some of our findings and
observations.
Several market micro and macro
challenges have changed the way
we think about and model execu-
tion dynamics, be they regulatory,
competitive pressure or economi-
cally driven. A tremendous amount
of our research effort is directed
towards solving the micro challeng-
es including placement logic, venue
selection, latency, high frequency
signal research etc. In this article we
deal with the more ‘macro’ effects—
of minute-frequency and lower.
Some of the key themes that have
emerged over the last decade are:
The shift from active to passive
investing – the rise of ETFs and
other index tracking investment
vehicles to the detriment of active
investment management is a
well-documented phenomenon.
Our research suggests that there is
a statistically significant relation-
Michael Steliaros, Global Head of
Quantitative Execution Services,
Goldman Sachs
ship between passive fund and ETF
ownership and volatility, specifically
towards the end of the trading day,
the closing auctions themselves and
subsequent overnight dynamics.
This is not necessarily apparent
when looking at simple, close-to-
// thetradenews.com
Issue
Issue 63
63 //
thetradenews.com // // 11 11