Recap · August 4, 2025 · 47:33
Brandon Hong: $25M+ Trades, Crypto Market Future, and More | TG Podcast
The Signal
Brandon Hong lays out a deliberately unsentimental trading framework: define invalidation, favor a large upside over a contained loss, and react to observable structure instead of predicting a cycle. He explains why he was bearish on Pump.fun, how Hyperliquid and TRUMP became unusually asymmetric opportunities, and why most of his capital is now in private AI, robotics, defense, and aerospace companies.
Key Takeaways
- 01
Reaction over prediction
Hong limits his inputs to market structure, support and resistance, relative strength, and the way traders buy or sell an anticipated event. He treats broad cycle calls as assumptions rather than trade plans.
- 02
Pump lacked protection
He says Pump.fun may have been reasonable for ICO participants, but public buyers had little downside protection and no clean invalidation after the launch moved against them.
- 03
Breakouts create the setup
Bitcoin's $112,000 all-time-high break and Ethereum reclaiming $2,800 mattered because the level itself supplied a clear place to be wrong, rather than because of a grand forecast.
- 04
Hyperliquid paid for real use
Hong says he first used Hyperliquid because he needed a decentralized perpetuals venue, then received an airdrop that he gradually sold rather than trying to call the top.
- 05
Crypto profits moved private
He says most of his liquid crypto gains have gone into later-stage private companies, where he sees more asymmetric access than in increasingly efficient onchain markets.
On the Record
“The three fundamental assumptions I have when I'm trading are that market structure matters.”
“My approach to the markets is that I react. I don't predict.”
“I always lose small, win big, or win small. Never lose big.”
“The time is now to really try to make as much as possible.”
The Breakdown
Why he passed on Pump.fun
Hong opens by separating the ICO from the public launch. In his view, the public buyer was purchasing after the attractive entry had already gone: he puts typical public entries around $0.055 to $0.066, with holders soon down 30–40%. Without a defined point at which the thesis was invalidated, he says the project’s business quality did not by itself make the token an asymmetric trade.
The small set of inputs
His process starts with the chart’s structure: higher highs and higher lows versus the reverse, obvious higher-time-frame support and resistance, relative strength against Bitcoin, and whether a catalyst is already being bought in advance. He tends to sell speculation into an event when he thinks the event cannot exceed expectations; if it can, that nuance changes the trade. The point is not certainty; it is a favorable probability and payoff ratio.
Bitcoin and ETH at the levels
The recent Bitcoin break above $112,000 was his clearest example. A months-long ceiling gave the trade a nearby invalidation, just as Ethereum’s $2,800 area had repeatedly acted as an inflection point over the preceding year. He was long Bitcoin, Ethereum, PENGU, and other assets around those breakouts, with more muted targets than the post-election move from roughly $75,000 to above $100,000.
Airdrop, then realized gains
Hong says he used Hyperliquid early because US-based traders had few satisfactory perpetuals options. He later ran a $1,000-to-$100,000 challenge account that reached $1 million through the airdrop, while an earlier account became a top-30 HYPE recipient. He says he sold gradually in the $20-to-$30 range, separating the decision to realize gains from the impossible task of catching the highest print.
From coins to private markets
His larger shift is toward private investments: he names AI, robotics, defense, aerospace, and consumer businesses, with AI representing roughly 40–50% of the portfolio. He points to secondary-market access in companies such as Mercor and to Figure AI’s valuation move as examples of the opportunities he is pursuing. He frames the concentration as his own risk, not a general prescription.
Treasuries, TRUMP, and discipline
Hong still trades crypto narratives, including treasury-company equities, but calls them trades with limited lifecycles rather than permanent investments. He describes TRUMP as exceptionally asymmetric because a presidential launch could plausibly run much further while an obvious scam denial would create a defined downside. His standing rule comes from losing 34% of net worth in unrealized gains during a May 11 crash: scale out, record mistakes, and never allow a large loss.
Long now, skeptical longer term
At the close, he is long ETH and XRP while watching acceptance above key levels, but distinguishes Bitcoin from the altcoin market. Institutional accumulation may give Bitcoin a firmer floor, he says, while altcoin opportunities become harder and more sophisticated. He also rejects a universal retirement number: the relevant amount is what gives an individual security and contentment, not an internet benchmark.
Distilled from the episode transcript · Counterparty Recap Desk
