[ I N - D E P T H | A L G O T R A D I N G ]
Following extreme market conditions at the height of the COVID-19 crisis , David Whitehouse explores how algorithmic trading performed in comparison to other market-moving events , and finds the human touch remains critical .
As the head of fixed income trading at a European bank in 2007 , Jens Kramarczik was troubled by the early stages of the US subprime mortgage crisis .
He shifted out of risk assets , shorted Italian government bonds and bought the yen as a flight to safety . In this case , human judgement was the key , and the shift was made “ long before the rocket science told us to ,” he says .
These days , Kramarczik is a consultant in trading algorithms , working from home in Frankfurt . He had a sense of déjà vu as the COVID-19 pandemic prompted market collapse . While algorithms did not cause the mess , they were “ not very helpful in March ,” he explains . There was the same sense of panic that he witnessed in 2007 . “ People think that if they use algorithms they are not emotionally involved ,” he says . “ But that ’ s not true .”
Kramarczik now uses simple algorithms to identify the best days of the month on which to buy securities , or the best hour within a day . He sees gold as a “ safety net ” against the massive amounts of liquidity that have been injected into the financial system . Even having reached record levels , gold can still provide “ insurance for the future ,” he believes .
Still , he treats algorithms as a tool rather than a guide . “ If there are moves that are not in your database , it becomes difficult ,” he says . “ Sometimes the
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