Asian Stocks to Fall as AI Bubble Bursts

The Asian stock market is on the brink of a significant downturn, driven by the intensifying interest in generative artificial intelligence (AI) and the potential bursting of the AI bubble. As investors pour money into AI-related stocks, the broader market faces the risk of a correction, with Asian stocks likely to be among the hardest hit.



The AI rally has been led by Nvidia, the maker of specialized chips crucial for running generative AI models. Nvidia's shares have returned more than 500% since the start of 2023, driven entirely by earnings growth. However, the current optimism around AI stocks, while not as high as prior peaks, could still lead to a bubble. If this bubble bursts, it could have a ripple effect on the broader market, including Asian stocks.

The current valuations of large tech stocks are not as stretched as they were in prior periods. The 10 largest tech companies are trading at 28 times earnings, significantly lower than the peak of the tech bubble in 2000 (52 times earnings) and the post-Covid rally in 2021 (43 times earnings). This suggests that current valuations are more reasonable and less likely to be in a bubble. However, the implied level of long-term earnings growth that investors expect has climbed to 11% a year, above the long-run average of 9% but still below the 16% growth that was expected at the height of the technology bubble in 2000 or the 13% growth implied by stock prices at the peak of the post-Covid rally in 2021.

The performance of different sectors within the Asian stock market may vary significantly in response to an expected downturn. The study on the Indian stock market revealed that the consideration of factors for investment decision-making is sector-specific. This implies that different sectors may react differently to economic downturns based on their unique attributes and the factors that influence investor decisions within those sectors.

For instance, the study found that 'must be' attributes, which are essential for investment decisions, include the condition of financial statements, current economic indicators, and the result of technical analysis. These attributes are likely to be crucial for sectors that are heavily dependent on economic stability and financial health, such as the banking and financial services sector. In an economic downturn, investors in these sectors would closely monitor financial statements and economic indicators to make informed decisions, potentially leading to a more cautious approach and reduced investment.

On the other hand, the 'delight' attribute, which includes insider information, may play a significant role in sectors where insider knowledge can provide a competitive edge, such as the technology and healthcare sectors. During a downturn, investors in these sectors might seek out insider information to identify opportunities for growth and innovation, potentially leading to more speculative investments.

The study also highlighted that the factors affecting investment decisions are sector-specific, which means that the performance of different sectors within the Asian stock market may vary based on how these factors are perceived and acted upon by investors. For example, sectors that are more resilient to economic downturns, such as consumer staples and utilities, may continue to attract investment due to their stable cash flows and essential nature. In contrast, sectors that are more sensitive to economic cycles, such as automotive and real estate, may experience a more significant decline in performance.

Investors can employ several strategies to mitigate risks and capitalize on opportunities during this period of market volatility. One key strategy is diversification across the different phases of the AI trade. Phase 1 is dominated by Nvidia, which has seen remarkable returns driven by earnings growth. Phase 2 involves companies building AI-related infrastructure, such as semiconductor designers and manufacturers, cloud providers, and data center real estate investment trusts. Phase 3 includes companies incorporating generative AI advances into their product offerings, with software and IT services stocks being best positioned. Phase 4 involves companies across various industries using AI to boost productivity, with software and services companies and commercial and professional services firms having the biggest potential for earnings gains from AI.

Another strategy is to consider the current valuations and growth expectations of large tech stocks. The 10 largest tech companies are trading at 28 times earnings, which is significantly lower than the peak of the tech bubble in 2000 (52 times earnings) and the post-Covid rally in 2021 (43 times earnings). This suggests that current valuations are more reasonable and less likely to be in a bubble. Analyst growth estimates for the 10 largest technology companies are optimistic but below what was seen during the technology bubble. The median large tech company is expected to deliver 15% earnings per share growth in three years, compared to 24% earnings growth analysts foresaw in March 2000. This indicates a more cautious and realistic outlook.

Investors should also consider sector-specific factors that influence investment decisions. For example, in the Indian stock market, the study revealed that the consideration of factors for investment decision-making is sector-specific. This helps various parties in understanding the investment decision behavior of investors. For instance, 'must be' attributes include the condition of financial statements, current economic indicators, and the result of technical analysis, while 'insider information' is a 'delight' attribute.

Understanding individual investor behavior towards the stock market can help in making informed decisions. For example, the study in the Indian stock market found that factors affecting the decision-making of investors include the condition of financial statements, current economic indicators, and the result of technical analysis. This information can be used to make more informed investment decisions.

Investors should also consider the dividend policy of companies, as it has a statistically significant impact on company financial performance. For example, the study by Raed KANAKRIYAH found a strong relation between Dividend Yield (DY), Dividend Pay-out Ratio (DPR), and Firm Size (FSIZE) variables that explain firm performance. This suggests that companies with a strong dividend policy are likely to have better financial performance.

In conclusion, the Asian stock market is on the brink of a significant downturn, driven by the intensifying interest in generative AI and the potential bursting of the AI bubble. Investors can mitigate risks and capitalize on opportunities by diversifying across the different phases of the AI trade, considering current valuations and growth expectations, understanding sector-specific factors, and considering the dividend policy of companies. By employing these strategies, investors can navigate the challenges of the current market environment and position themselves for success.