[ I N - D E P T H | A L G O T R A D I N G ]
correlation disappears .”
Flash Crash The benefits of algorithms are obvious : much more efficient investment research and faster trading execution . Algorithms are also used to reduce the market impact of big trades as they make it easier to sub-divide orders , so the size of the trades will not be apparent .
The behavioural biases of traders , at least in theory , are eliminated . This doesn ’ t come for free : market exchanges still experience software glitches , the effect of which can be magnified and spread by algorithms .
A classic example is the ‘ Flash Crash ’ of 6 May , 2010 when more than a trillion dollars was temporarily wiped off US equity prices . Computer programs exacerbated the damage by selling large volumes of stocks in response to the volatility . Greater use of market-wide circuit breakers was a result .
COVID-19 Rather than a financial or market-led crisis , COVID-19 is a crisis of health and the economy . Some argue that algorithmic trading allowed a prompt , if partial , recovery from the COVID-19 lows seen
“ Profitability should never take a back seat to risk management . We learned the hard way who focused on reward without sufficient focus on risk .”
STEVE SOSNICK , CHIEF STRATEGIST , INTERACTIVE BROKERS
“ There is no argument ” that algorithmic trading adds more liquidity to the markets , says Ashu Swami , chief technology officer at Apifiny , a global trading and financial value transfer network in New York . But , given their high volumes and automatic nature , “ if they go wrong and are not contained , they can cause sharp swings in the market ”. Swami previously led the high frequency market-making business at Morgan Stanley .
Algorithms are often used to instantly exploit even minor price discrepancies in the same security trading in different markets . The International Organisation of Securities Commissions ( IOSCO ) Technical Committee in 2011 found that algorithms can quickly transmit shocks rapidly from one market to the next , so amplifying systemic risk . early this year . The danger now , Swami says , is one of contagion .
When an algorithm goes wrong , “ the other algos either see it as an anomaly and pull their quotes , or they make unreasonable trading decisions based on the outlier prices ”. Swami is confident that the problem will tend to be reduced over time : “ More people using algos will lead to their democratisation and lessen deleterious contagion .”
The volatility seen in March was a function of the pandemic rather than being caused by algorithms , says Ray Ross , co-head of electronic trading at BMO Capital Markets in New York . BMO , he claims , performed well for its clients while using algorithms .
BMO uses algorithms to manage execution and market impact , rather than to generate trading ideas . Given the fact that they can be used for any kind of strategy , Ross sees little danger that they will all give off the same signal .
Neither does Ross see algorithms as being responsible for increased numbers of failed trades in March . He sees settlement and clearing as the more likely candidates : “ my guess is that it ’ s at that end .”
BMO Capital Markets has been functioning pretty much as usual with people working from home , Ross says . They will keep doing so for the foreseeable future and he expects the change in working
46 // TheTRADE // Fall 2020