Just a few days ago from the moment I typed these words, there was a flash crash in Bitcoin price when El Salvador officially using it as legal tender. There was $ 300 billion vanished from the crypto market values. Although that was a big loss to investors in the fields, the damage seems to be humbled compared to the 2010 flash crash where 1000 billion $ disappear from the US Stock markets. The main reason behind this event is a group of firms applying a strategy called high-frequency tradings. This event made high-frequency trading’s firms the criticized target for media and retail investors communities for years. However, the concept of using speed to add up advantages for trading has existed for centuries.
The most favorite story that should be mentioned about the early form of “cheetah trading” is the tale of Nathan Rothschild, who used racing pigeons to get the information of Napoleon’s defeat at Waterloo a few days before the official news came to London. He then silently acquired a large amount of England’s war bonds which turned out to double his wealth by holding it in just a year.
After the Rothschild era. These are the new inventions that has been used to offer the same advantages to anyone that can afford them.
- Telegraphy in the early 1850s.
- Telephone in early 1875.
- Radio in 1915.
- Screen trading in 1986.
Moving into the modern days, the approach is way more different and complex than what I listed above. Modern high-frequency traders (HFT) use decision-making algorithms, supercomputing power, and low-latency trading technology to exploit market pricing inefficiencies for profit. HFT strategies require investors to trade in high volumes and are most profitable in volatile markets, making HFT a convenient scapegoat for market instability. Their behaviors include :
- Acting upon the information revealed by low-frequency trader’s (LFT) actions.
- Engaging in sequential games.
- Hunting the LFT weakness.
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In most cases, their actions do nearly no harm to the market but the trading environment turns into a dangerous situation when they begin to behave like predators.
The predator algorithm is the kind of algorithm that sends orders to manipulate the stock markets in order to trigger a microstructure mechanism, which has a foreseeable outcome. These actions include:
- Quote stuffing: This strategy is executed since it is challenging and costly for the HFT to always keep themself one step ahead of other market participants. Therefore, they will try to slow down other algorithms’ performance by sending thousands of fake orders and flooding an exchange with information, which confuse the algorithms of brokers and make the majority of investors miss their chance to execute a trade without paying an explicit fee to HFT firms.
- Quote dangling or spoofing : This method is a fraud approach, which sends orders and cancels them immediately to create an illusion about the demand to buy or sell securities. This activity is intended to attract other traders to induce a particular market reaction. Spoofing can be a factor in the rise and fall of the price of shares and can be significantly profitable to the spoofer who can time buying and selling based on this manipulation.
- Pack and stop hunting: Predators hunting independently become aware of each other’s activities, and form a pack in order to maximize the chances of triggering a cascading effect. Which means the predator will collaborate with each other to push the market to a point where many stop-loss are activated which lead the market to move further in the direction that benefits the predators.
Be aware of the harmfulness generated by these predators, lawmakers around the world have established rules to ban illegal action such as spoofing, layering and front running. After that implementing circuit breakers is required for every exchange to stop the market when the flash crash happens to save investors from these risky events. However, these improvements to ensure the market being safer and more balanced are only applied to the stock market. We don’t have the same policies to protect anyone putting money into crypto.
During 2017, the “fear gauge,” index continued to decrease and reached a historic low in November 2017. This phenomenon created a situation that made the HFT suffer, with aggregate revenue from trading US equities dropping below $1 billion for the first time since the financial crisis.
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In the same years, the financial industry observed the crypto market in the opposite position. When BTC shoots from $900 to $20.000 at the end of the year, the institutional investors and HFT begin to notice. While the institutional investors seemed to be careful and had steady slow steps to investigate this market, the HFT had strong investment to acquire the potential profit.
The cryptocurrency market is particularly attractive to automated traders because of the market’s high volatility. In fact, cryptocurrency is the most volatile liquid asset on the market; the historical volatility of equities is approximately 13.4%, while the historical volatility of Bitcoin is 70%. It is also worth mentioning that Twitter plays such a big deal on the price movement of cryptocurrencies, the common fomo (fear of missing out) mentality among the investors made it easier to manipulate the market compared to their stock neighbors.
Moreover, like the forex market — where HFT is particularly active — the cryptocurrency market is operational 24 hours per day. Additionally, the cryptocurrency market offers investors trading variability. Cryptocurrencies can be bought, sold, and traded using fiat currency or another cryptocurrency, and with over 2000 cryptocurrencies and 180 fiat currencies, investors have plenty of opportunities to execute strategic arbitrage trades.
These new participants could suck such a big piece out of the target profit of anyone using crypto as their retirement plans ( An research estimate that the explicit fees to pay for HFT could eat up to 40% of the target profit). However, since there are not that much protection from lawmakers, it is better for the investors to take care of their own money.
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