What is Algorithmic High-Frequency Trading?
High-frequency trading takes algorithmic trading on a different level. HFT involves placing thousands of orders at a staggeringly fast speed.
Algorithmic trading and HFT have become an integral part of the financial markets due to the consolidation of various factors, including the growing role of technology in the present-day markets.
How does Algorithmic HFT Amplify Systemic Risk?
Algorithmic HFT amplify systemic risks in a number of reasons.
First, since there’s a great deal of algorithmic HFT present in the markets nowadays, trying to come out most successful in the competition is an in-built quality of most algorithms, which can react instantaneously to market conditions.
As a result, during turbulent markets, algorithms may greatly widen their bid-ask spreads in order to avoid being forced to take trading positions, or will temporarily stop trading altogether, which decreases liquidity and worsens volatility.
Given the increasing degree of integration between markets and asset classes in the global economy, a meltdown in a major market or asset class often ripple across to other markets and asset classes in a domino effect event.
Algorithmic HFT is a huge contributor to exaggerated market volatility, and this can fuel investor uncertainty in the short term and shake consumer confidence over the longer term.
When the market suddenly collapses, investors will be left thinking about the reasons for such a drastic move. During the new vacuum often existing at such events, large traders including HFT firms will slash their trading positions to scale the risks, putting more downward pressure on the markets.
As the market moves lower, more stop-loss orders are triggered, and this negative feedback loop creates a free-fall. If a bear market comes out because of such phenomenon, consumer confidence is further shaken by the erosion of stock market wealth and the recessionary signals emanating from a major market crash.
The staggering speed at which most algorithmic HFT trading takes place means that one errant or faulty algorithm can stack up millions losses in just a very short period of time.
Unfortunately, the hyper-efficiency of algorithmic HFT, wherein algorithms constantly monitor markets for just this sort of price discrepancy, meant that rival trader flocked and took advantage of an errant algorithm’s dilemma.
Volatility swings that are worsened by algorithmic HFT can incur huge losses that investors would have to shoulder.
Many investors regularly place stop-loss orders on their stock holdings at levels that are 5 percent away from their current trading prices. If the markets gap down for no apparent reason, these stop loss orders will be triggered.
If the stocks subsequently rebound quickly, investors would have needlessly incurred trading losses and lost their holdings. While some trades are reversed or cancelled during unusual strikes of market volatility, most trades are not.
Loss of Market Integrity Confidence
Investors trade in the financial markets because they have the full faith and confidence in such markets’ integrity. But repeated episodes of unusual market volatility could shake this confidence and compel some conservative investors to ditch the markets altogether.