If he were still trading today, which industries or sectors would he focus on?
Alright, let's chat about this topic.
Imagine if B·N·F * (小手川隆), that legendary Japanese trader, were still active in the market today. Where would he be focusing his attention? That's actually a really interesting question.
The key to answering this isn't to guess whether he'd favor "AI" or "new energy," but first to understand his "fishing" method. His core philosophy is fundamentally different from the conventional "buy and hold good companies" strategy.
B·N·F's Core Weapon: Hunting for "Excessively Oversold" Opportunities
You can picture him as someone who specializes in scooping up bargains precisely when the market panics. His primary strategy is counter-trend trading, and his weapon is the technical indicator "Moving Average Bias (Bias Ratio)".
Sounds too technical? It's really quite simple; let me give you an analogy:
Imagine a rubber band (say, the 25-day moving average) representing a stock's average price over that period. The stock price is like a little ball attached to this rubber band.
Most of the time, the ball wobbles near the rubber band. But occasionally, when panic hits the market, it's like someone kicks that ball downward, sending it flying unusually far from the rubber band.
B·N·F bets on this: The tension in this rubber band will pull the kicked-too-far ball back slightly towards its normal range.
His play is to buy at the exact moment the ball is kicked to its furthest, most extreme point, and then sell when the rubber band pulls it back towards normalcy, pocketing the difference. He's essentially in the business of short-term rebounds.
Therefore, he wouldn't be drawn to crowded plays; he actively seeks out scenes of "fire and collapse."
If he were trading today, his "radar" would be scanning these areas:
Based on this "cigar butt" hunting style, he would likely focus on the following types of sectors or situations:
1. Tech Giants & Growth Stocks Hit by a "Black Swan"
- Why? Because these stocks are typically priced at a premium. When hit by negative news—like an earnings miss, founder troubles, or a sudden shift in competitive dynamics—panic is amplified, often leading to a "meteoric fall."
- For example: A leading AI company sees its stock plunge 20%-30% in two or three days due to doubts about a new model's effectiveness or regulatory rumors. While most panic-sell, an alert might flash on B·N·F’s screen. He’d coolly analyze: Is this decline "overdone"? Has market fear peaked? If yes, he’d quietly accumulate shares at a point where no one else dares to buy, waiting for a technical rebound.
2. Cyclical Industries "Wholesale Dumped" Due to Macro Data
- Why? Industries like shipping, non-ferrous metals, chemicals, and real estate are tightly tied to the economic cycle. Negative economic data (e.g., a weak PMI report) or rising rate hike expectations can trigger indiscriminate institutional selling across the entire sector.
- For example: Fears of a global recession intensify, causing a crash in shipping stocks. B·N·F wouldn't worry about the sector's long-term prospects next year. Instead, he'd look for companies within the sector with relatively solid fundamentals whose stock prices have been slammed down to rock bottom alongside weaker peers, sporting terrifyingly large bias ratios. He'd target these "wrongly condemned" stocks for a quick profit.
3. Specific Sectors Slammed by Policy Shifts or Sudden News
- Why? These events most easily spark irrational selling frenzies. Examples include sudden heavy-handed regulation or a product safety scandal.
- For example: Suppose stricter minor protection policies are announced for the gaming industry, causing game company stocks to plummet collectively. B·N·F's angle would be: Is the actual impact as dire as the stock price reaction suggests? Is the market overreacting? He'd search for the "deepest pit" where the fall far exceeds a reasonable range and dive in.
4. "Star Stocks" That Plummet Post-IPO, Victims of Exaggerated Hype
- Why? Unrealistically high expectations for hot IPOs lead to massive selling pressure from early investors and disappointed retail traders when performance disappoints after listing, causing rapid declines.
- For example: A highly anticipated unicorn IPO crashes 30% below its offering price within a month. Amidst media and investor despair, B·N·F would likely be calculating how far the stock has deviated from its 25-day moving average and whether the selling pressure is nearing exhaustion.
To Summarize
Rather than focusing on which sector, it's more accurate to say B·N·F would focus on what kind of "carnage."
He's like a battlefield surgeon: where the fighting is fiercest and casualties pile up, that's where he goes. He's not concerned with who wins the war long-term (industry development), but with whether he can quickly revive the "casualties" (oversold stocks) that still have a pulse but look near death, pocketing a "resuscitation cost."
So, if he were trading today, he likely wouldn't be on TV waxing lyrical about the future of AI or the boundless potential of new energy. He'd probably be silently glued to his screen, watching stocks you might not even recognize flicker by—stocks hammered down by all kinds of bad news—searching for that excessively stretched "rubber band."