TECHNOLOGY TRENDZ | Quants
Reasons For Using Algorithms
8.10%
Internal
crossing
April 2016 | www.wealth-monitor.com
10.40%
Trader
productivity
11.30%
Reduced
market impact
16.30%
Ease of use
8.60%
Execution
consistency
4.70%
Customisation
8.60%
Commission
Rates
12.50%
Price
improvement
4.30%
Speed
13%
Anonymity
What is Quantitative Trading?
Put simply, a quantitative trading strategy makes use of computer software programs
developed to track patterns or trends in an asset class. These trends may be a product of
the price, the volume and/ or frequency at which it is traded. By involving the computer
in the same, quant traders aim to take much of the human element out of investment
decisions.
patterns in a stock which get overseen by
humans is driving this behavior.
However, it is prudent to highlight here
that markets today are reflecting shorter
cycles than before. While the complex
quant strategies may display success,
One of the drivers of quant trading strategies
in recent years has been the emergence of HFT
stemming from the 2008 crisis, there is
a growing segment within this category
which is venturing out to try their hand
at DIY algo-trading platforms. As an
example, a very basic algorithm involves
- If volume in a particular stock hits
100,000 and the 50-day moving average
of the stock price crosses above the
100-day moving average, buy 100 shares.
The appeal of the system identifying
2.20%
Match
pre-trade
estimates
Source: The 2015 Algorithmic Trading Survey
T
o say mathematicians have fastened
their grip on the financial world over
the last decade in a manner unlike
before would not be too far away from
the truth. The rise of quantitative trading
bears witness to the growing inclination
of finance towards technology and data.
Aided by the increased demand for speed,
algorithm development, the core of quant
trading, is driving limitless possibilities
within the field of trading.
“Quant traders basically use quantitative
analysis (Analysis on historical data to
find relationships) to set up mathematical
algorithms that tries to capture trends or
mispricing between different securities
in order to generate a profit,” Yacoub
Husein Nuseibeh, CFA, CQF, member at
CFA Society Emirates elaborates. One of
the drivers of quant trading strategies in
recent years has been the emergence of
High Frequency Trading (HFT). Making
use of complex algorithms to analyze the
markets, it is able to spot emerging trends
in a fraction of a second. Blamed for the
6th May 2010 flash-crash on account of
exacerbating price declines, this strategy
has bought to the fore arguments
including demands for regulation and
unfair advantage larger firms possess.
Yacoub prefers to look at this in a more
mature manner highlighting that financial
markets are ultimately out there to make
profit; using an advanced algorithm in
trading, fundamental research or technical
analysis – provide the markets with depth
involving divergent term views as well as
different insights. Thus, enabling greater
efficiency in the system.
A trend worth highlighting here is
the appeal quant trading strategies
are seeing with the retail investor. With
an aim to minimize the human bias in
the investing process, giving into fears
over dependence on the computer could
spell disaster and thus needs to be used
judiciously. As Yacoub outlines, “‘No one
can predict the future, so the best guess
is usually what happened in the past.
Some quants will be more successful than
others. However I do not believe that
they will consistently generate profits
all the time, because these relationships
can change and they often do. Let’s not
forget that economics and finance is not
science like physics because humans run
governments, banks, companies, etc….
and humans do not necessarily behave in
fixed laws patterns, hence Quants can lose
money like any traders or investors.”
In conclusion, quantitative trading is
here to stay and, going ahead, is bound to
see a continued degree of focus in terms
of development. With the focus of trading
primarily continues to remain on how to
optimally execute trades, quant offers a
platform integrating a myriad of market
details and using that information to effect
trades in time frames, beyond the human
capacity. At the same time, it is expected
to continue to invite the vigil of market
watchmen and observers who view the
role of computers in the overall investing
process as one that needs to be exercised
with a human touch.
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