Background to Algorithmic Trading
Similar
to most other fields, the use of technology is being optimized in trading in
the stock markets. Stock trading is getting increasingly automated through use
of sophisticated computer systems that operate through algorithms, which
minimize human involvement and decision-making. Not only does this lead to the
extensive use of technology by stock traders and investors, but it may also
create imbalances in the stock markets whereby certain players can use
technology to favour their own commercial interests at the cost of other
similar players in the markets.
to most other fields, the use of technology is being optimized in trading in
the stock markets. Stock trading is getting increasingly automated through use
of sophisticated computer systems that operate through algorithms, which
minimize human involvement and decision-making. Not only does this lead to the
extensive use of technology by stock traders and investors, but it may also
create imbalances in the stock markets whereby certain players can use
technology to favour their own commercial interests at the cost of other
similar players in the markets.
On
the one hand, such algorithmic trading (or algo trading) is beneficial as it
operates instantaneously based on information available in the markets, and
hence makes the markets more efficient. On the other hand, it has been
criticized on the ground that it creates distorted incentives in various market
players that could lead to imbalances and consequently significant risks to the
stock markets as well as the economy as a whole. Instances such as the flash crash that
occurred in the US markets in 2010 due to erroneous order entry into the
computer systems only highlight the risks of automated trading.
the one hand, such algorithmic trading (or algo trading) is beneficial as it
operates instantaneously based on information available in the markets, and
hence makes the markets more efficient. On the other hand, it has been
criticized on the ground that it creates distorted incentives in various market
players that could lead to imbalances and consequently significant risks to the
stock markets as well as the economy as a whole. Instances such as the flash crash that
occurred in the US markets in 2010 due to erroneous order entry into the
computer systems only highlight the risks of automated trading.
Interestingly,
the debate surrounding algo trading achieved high intensity a couple of years
ago, and was even the subject matter of a book Flash
Boys: A Wall Street Revolt by Michael Lewis. In the meanwhile, regulators
the world over have been consider the merits of restricting such algorithmic
trading so as to mitigate its risks.
the debate surrounding algo trading achieved high intensity a couple of years
ago, and was even the subject matter of a book Flash
Boys: A Wall Street Revolt by Michael Lewis. In the meanwhile, regulators
the world over have been consider the merits of restricting such algorithmic
trading so as to mitigate its risks.
Moving
to India, the scope and extent of algo trading has not been clear. Recognizing
the need to address the issues pertaining to algo trading, particularly from an
operational standpoint, the Securities and Exchange Board of India (SEBI) has
issued a series of guidelines to the stock exchanges (here,
here
and here).
However, in order to consider the regulatory aspects of algo trading on a
comprehensive basis, SEBI yesterday issued a Discussion
Paper on ‘Strengthening of the Regulatory Framework for Algorithmic Trading
& Co-Location’.
to India, the scope and extent of algo trading has not been clear. Recognizing
the need to address the issues pertaining to algo trading, particularly from an
operational standpoint, the Securities and Exchange Board of India (SEBI) has
issued a series of guidelines to the stock exchanges (here,
here
and here).
However, in order to consider the regulatory aspects of algo trading on a
comprehensive basis, SEBI yesterday issued a Discussion
Paper on ‘Strengthening of the Regulatory Framework for Algorithmic Trading
& Co-Location’.
SEBI’s Discussion Paper
At
the outset, the Discussion Paper seeks to clarify the various technical
concepts relating to the topic. Algo trading is the broader concept (as
discussed above), which provides greater speed to stock trading and also offers
anonymity. A sub-set of algo trading is “high frequency trading (HFT)”, which
uses high-speed networks and locational advantages to create trading
opportunities within miniscule fractions of a second. HFT usually relies upon
co-location, which in essence means that certain traders place their computer
servers within close proximity of the stock exchange system such that they have
access to trade information and prices a split second faster that others, which
they can work to their advantage.
the outset, the Discussion Paper seeks to clarify the various technical
concepts relating to the topic. Algo trading is the broader concept (as
discussed above), which provides greater speed to stock trading and also offers
anonymity. A sub-set of algo trading is “high frequency trading (HFT)”, which
uses high-speed networks and locational advantages to create trading
opportunities within miniscule fractions of a second. HFT usually relies upon
co-location, which in essence means that certain traders place their computer
servers within close proximity of the stock exchange system such that they have
access to trade information and prices a split second faster that others, which
they can work to their advantage.
After
introducing the concept, the Discussion Paper goes on to state:
introducing the concept, the Discussion Paper goes on to state:
2.5. Adoption of such advancements in
technology in our market in recent years have resulted in vast majority of
orders being generated through trading algorithms. Currently, more than 80% of
the orders placed on most of the exchange traded products are generated by
algorithms and such orders contribute to approximately 40% of the trades on the
exchanges.
technology in our market in recent years have resulted in vast majority of
orders being generated through trading algorithms. Currently, more than 80% of
the orders placed on most of the exchange traded products are generated by
algorithms and such orders contribute to approximately 40% of the trades on the
exchanges.
The
use of algo trading seems quite pervasive, although it is not clear whether the
Discussion Paper refers to these statistics with references to global markets
in general, or whether it relates to India. If the numbers pertain to India,
they look much higher that I would have thought.
use of algo trading seems quite pervasive, although it is not clear whether the
Discussion Paper refers to these statistics with references to global markets
in general, or whether it relates to India. If the numbers pertain to India,
they look much higher that I would have thought.
The
Discussion Paper then goes on to make a series of proposals in order to combat
the distortive effects of algo trading. Some of them are set out below:
Discussion Paper then goes on to make a series of proposals in order to combat
the distortive effects of algo trading. Some of them are set out below:
– Minimum Resting Time for Orders:
This would ensure that there would be a minimum time between when an order is
received and when it is allowed to be amended or cancelled. This is to avoid a
situation of “fleeting” orders that can be prevalent in algo trading where
large orders are made and then cancelled or amended in a split second, thereby
distorting the market. SEBI has proposed a minimum time of 500 milliseconds
before an order can be amended or cancelled. SEBI has also indicated that its
approach might be unique in that such a minimum resting mechanism is not
mandated by any regulator yet.
This would ensure that there would be a minimum time between when an order is
received and when it is allowed to be amended or cancelled. This is to avoid a
situation of “fleeting” orders that can be prevalent in algo trading where
large orders are made and then cancelled or amended in a split second, thereby
distorting the market. SEBI has proposed a minimum time of 500 milliseconds
before an order can be amended or cancelled. SEBI has also indicated that its
approach might be unique in that such a minimum resting mechanism is not
mandated by any regulator yet.
– Frequent Batch Auctions: Under
this mechanism, buy and sell orders would be accumulated for a length of time,
such as 100 milliseconds, at the end of which orders received during the time
interval will be matched. This will obliterate any advantages that HFT players
may have through co-location.
this mechanism, buy and sell orders would be accumulated for a length of time,
such as 100 milliseconds, at the end of which orders received during the time
interval will be matched. This will obliterate any advantages that HFT players
may have through co-location.
– Random Speed Bumps: This
involves “introduction of randomized order processing delay of few milliseconds
to orders”. This is again to nullify co-locational advantages that some players
might have.
involves “introduction of randomized order processing delay of few milliseconds
to orders”. This is again to nullify co-locational advantages that some players
might have.
– Randomization of Orders: Under
this proposal, all orders received during a predefined time period (such as 1
to 2 seconds) would be randomized in order to perform the order matching
routine. Here again, any advantage of speed or location would be of no use.
this proposal, all orders received during a predefined time period (such as 1
to 2 seconds) would be randomized in order to perform the order matching
routine. Here again, any advantage of speed or location would be of no use.
A
few other similar, and specific, proposals have been made in the Discussion
Paper.
few other similar, and specific, proposals have been made in the Discussion
Paper.
Implications
It
is not clear what form the final set of SEBI’s regulations relating to algo
trading will take, if at all. However, from nature of the proposals and the
tone of the Discussion Paper, it is clear that the approach is towards imposing
greater regulation on algo trading so as to bring about a level playing field
in the market. In other words, the use of technology ought not to create
disparities in the system (although proponents of algo trading may argue that
there is nothing unfair about it). To that extent, SEBI seems to be adopting a
rather strict approach towards regulating algo trading. Although I have not
undertaken detailed research on the issue, it appears from the Discussion Paper
and the surrounding debate that SEBI’s efforts in reining in algo trading may
have gone farther than most other regulators around the world. More broadly,
the idea seems to be that speed is not always beneficial, and sometimes delayed
responses may be necessary and may yield better results (as Professor Frank
Partnoy has argued in his book Wait:
The Art and Science of Delay).
is not clear what form the final set of SEBI’s regulations relating to algo
trading will take, if at all. However, from nature of the proposals and the
tone of the Discussion Paper, it is clear that the approach is towards imposing
greater regulation on algo trading so as to bring about a level playing field
in the market. In other words, the use of technology ought not to create
disparities in the system (although proponents of algo trading may argue that
there is nothing unfair about it). To that extent, SEBI seems to be adopting a
rather strict approach towards regulating algo trading. Although I have not
undertaken detailed research on the issue, it appears from the Discussion Paper
and the surrounding debate that SEBI’s efforts in reining in algo trading may
have gone farther than most other regulators around the world. More broadly,
the idea seems to be that speed is not always beneficial, and sometimes delayed
responses may be necessary and may yield better results (as Professor Frank
Partnoy has argued in his book Wait:
The Art and Science of Delay).
Comments
on the Discussion Paper are due from the public on August 31, 2016.
on the Discussion Paper are due from the public on August 31, 2016.