Assuming that US stock trading time is truly extended to 22 hours, it seems to provide investors with a more flexible trading window, but from a professional trading perspective, this measure is not simply ‘good news’. On the contrary, it may spark an intense game, profoundly altering the market structure and the rules of engagement for participants.
In this new ‘all-weather market’, the confrontation between individual investors, institutions, and AI trading algorithms reveals the complex logic and hidden risks behind the extension of US stock trading hours.
22-Hour Market: Who Benefits?
The 22-hour trading arrangement of US stocks undoubtedly benefits large financial institutions and high-frequency trading firms the most. For these institutions, the extension of trading time translates to an expanded market participation window, meaning they can operate more flexibly to capture price fluctuations brought by more global news events. For instance, the extended trading hours of US stocks allow for real-time interconnection between market dynamics in European and Asian time zones and the US market, enabling large institutions to respond quickly and seize cross-market arbitrage opportunities.
However, for individual investors, this market change feels more like an invisible pressure. Regular investors usually lack the conditions and efficient adaptability to monitor the market around the clock; in a 22-hour trading environment, they often can only passively endure more frequent market fluctuations. Furthermore, this ‘all-weather market’ setting places individual investors under the pressure of ‘never turning off the lights’, forcing them to pay more frequent attention to market dynamics, which to some extent undermines their judgment and increases the psychological burden of investing.
AI and High-Frequency Trading: The Confrontation Between Humans and Machines
In a 22-hour market environment, the accelerated trading pace further amplifies the advantages of AI algorithms and high-frequency trading. AI trading systems analyze data and recognize patterns to complete information parsing and trade execution within milliseconds, even profiting from low liquidity during non-mainstream night hours. For example, when the market enters a quiet night period, high-frequency trading algorithms can exploit the lack of liquidity to influence prices and rapidly drive price changes in a short time. This operational method far exceeds the trading reaction speed of human investors, leaving regular investors unable to keep up.
High-frequency traders in the market usually do not directly play the role of ‘long and short confrontation’, but rather frequently profit by exploiting small price fluctuations. In the 22-hour market, AI algorithms have a high precision in capturing price fluctuations, allowing them to buy and sell multiple times in a short period, accumulating small price differences to achieve continuous profits. This model undoubtedly poses a significant impact on long-term investors, especially regular investors. Human trading decisions cannot reach the accuracy of AI, making them more susceptible to short-term fluctuations when facing intensive and rapid market changes, leading to misjudgments.
Extreme Volatility and Low Liquidity Periods: Invisible Systemic Risks
In the setting of a 22-hour market, market volatility will inevitably increase. Especially during inactive trading periods such as night or early morning, the lack of liquidity often leads to more intense price fluctuations. This characteristic provides manipulation space for high-frequency trading and algorithmic trading, allowing them to drive price changes with less capital, while retail investors often get caught in the volatility before they can react.
Moreover, since AI trading algorithms are generally based on similar data sources and strategy designs, when extreme events occur, a large number of similar algorithms may simultaneously trigger selling instructions, leading to an immediate ‘stampede’ phenomenon in the market, further exacerbating severe price fluctuations. This ‘algorithmic resonance’ brings systemic risks that not only affect short-term market volatility but may also lead to a crisis of trust across the entire market.
For regular investors, price fluctuations during low liquidity periods not only affect their asset safety but may also directly lead to capital losses. The deep involvement of AI and high-frequency trading institutions makes the market more inclined towards short-term profits, gradually diminishing the advantages of long-term investors, and under severe price fluctuations, regular investors' long positions are easily forced out of the market.
Market Ecological Transformation: Reshaping Trading Strategies and Mindsets
The market ecology of 22-hour trading forces investors to rethink and adjust their trading strategies. Firstly, traditional strategies such as ‘morning trading’ or ‘pre-closing decision-making’ are no longer applicable, as the market no longer follows specific trading period rules. For institutional investors, adjusting trading strategies will be more complex, as they need to conduct more detailed analyses of global market interconnections. For regular investors, this change will further increase their learning and adaptation costs.
Secondly, market psychology will also be reshaped. Investors are likely to become more anxious amid constant price fluctuations day and night, and the frequent market volatility increases the psychological pressure on investors, exacerbating short-term thinking and the behavior of chasing gains and cutting losses. The ‘all-weather’ trading of the market seems to increase the freedom of investment choices, but in reality, it is an invisible psychological manipulation.
Regulation and Fairness: Repair Challenges Under Market Imbalance
From the perspective of market regulation, 22-hour trading also increases the difficulty of regulation. In the face of an all-day market, regulatory agencies need to pay extra attention to market manipulation behaviors during low liquidity periods, especially regarding real-time monitoring of high-frequency trading firms. How to effectively regulate AI algorithm trading strategies and prevent the occurrence of market ‘flash crash events’ has become a severe test for regulators.
Moreover, the issue of fairness will become the focus after the market extends its trading hours. In a 22-hour market environment, large institutions and high-frequency trading firms leverage AI advantages to gain a competitive position over regular investors, exacerbating market structural imbalances, where retail investors are at a disadvantage against AI. To balance this disparity, regulators need to introduce more policies, such as limiting the frequency of high-frequency trading or establishing protective rules to safeguard the fair rights of regular investors.
