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It's not about how much it will rise; any rise or fall serves as a directional signal. I've registered on the Longbridge App for NVIDIA's earnings live stream tomorrow early morning, treating it as my wake-up alarm.

Those who bought AI stocks are likely waiting for NVIDIA's earnings report tonight. While AI is a long-term trend, the 阶段性 performance of key players can directly impact short-term investor sentiment and cause volatility. Over the past year, whenever tech companies post strong results, the market has often reacted with sharp swings. NVIDIA's market reaction to its last earnings release was relatively mild.

Besides stocks, Bitcoin and cryptocurrencies have also seen recent gains. For mainstream crypto assets allocated beyond stock investments, returns should be managed based on longer-term expectations; ignoring short-term noise is key to holding steady.

For companies with unchanged fundamentals and promising business prospects, sharp drops following earnings reports or negative news may present opportunities to test the waters. I recently took a small position in Alibaba after their latest update to validate my thesis.

In the past two years, the growth of the Singapore stock market and the Straits Times Index has become a standout presence in global stock markets. The pragmatic approach of Singapore-listed companies, along with their relatively low volatility compared to other securities markets, serves as a very important stabilizing factor in investors' portfolios. Over these two years, I have heard many friends share that the Singapore stock market is by no means inferior to the US stock market; it is a highly worthwhile investment target. Do not overlook it simply because its total market cap and price gains are smaller; holding it will make your portfolio more balanced. I hope that after hitting new highs, the local stock market can continue to develop steadily at its own pace.

The strength of Singapore bank stocks, beyond the numbers on financial statements and reports, allows retail investors to gauge the security of banking performance based on Singapore's relatively stable political environment, its still-growing economy, and the continuous influx of foreign population. Benefiting from local banking business and foreign capital, the choice of overseas individuals to use Singapore as a safe haven for wealth banking serves as ammunition for performance assurance. However, even the most stable blue-chip stocks have cycles and volatility; establishing proper expectations and position management is also recommended stock trading practice.

From a macro perspective, the trend is for the market to have more usable commercial large models available. The difference lies in how the market prices these different models. You have your own psychological price target; once it's reached, you buy or sell, and you pay for your own cognition.

My ideal "Day of an AI-Era Investor" is not about having an extra chatbot that can answer anything.

Instead, it's about every morning, when I open my investment app, the AI already knows:

Which changes from last night truly impacted my holdings;

What's most worth paying attention to today isn't the ten hottest news stories in the market, but the three things most relevant to my investment logic;

Which stock gains are just price fluctuations, and which changes might be shaking the very reasons I bought them in the first place.

During the trading session, when breaking news emerges, I don't want the AI to just summarize the news for me.

I'd rather it tell me:

Which companies does this affect?

Is the impact transmitted through revenue, costs, valuation, or market sentiment?

Does it change my original judgment?

If I need to act, am I executing a predetermined strategy, or am I being pushed by short-term volatility?

When I have a vague idea, like "Are AI infrastructure opportunities spreading from GPUs to networks, storage, and power?", the AI shouldn't immediately give me a stock ticker.

It should first help me turn the idea into a hypothesis, the hypothesis into verifiable questions, and then organize the candidate companies, key data, and opposing viewpoints. The final decision is still mine, but the research doesn't have to start from scratch every time.

After a trade, the AI shouldn't just tell me how much I made.

It should remember why I bought, what I expected to happen, and under what conditions I would prove myself wrong. After the market closes, it can remind me: did today's gains come from correct judgment, taking on more risk, or just from luck?

For me, the AI-era investment experience is not about "making decisions for the investor," but about making every decision have context, be recorded, verifiable, and reviewable.

A truly valuable AI shouldn't just be another page in a market data software.

It should become a long-term investment partner that understands my investment goals, continuously challenges my judgment, but always leaves the final decision to me.

#Imagine Your Day as an AI-Era Investor