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Daily blog · Author
Writes GIO4X’s long-form series on the history and the future of trading.
50 posts under the byline @Abe, newest first
AnalysisEducationTokenized StocksA tokenized stock may be the share itself, a claim on a custodian or a derivative that tracks its price. That distinction matters more than the blockchain. In 2026, tokenization has moved into the plans of major US exchanges, while remaining a tiny part of the equity market.@Abe4 min read
Analysis
AnalysisEducationWill Stock Exchanges Ever Close?The trading floor is fading. The exchange’s more valuable functions—listing companies, enforcing rules and producing a trusted reference price—are harder to replace. Exchanges will keep changing shape, even as their buildings lose their original purpose.@Abe4 min read
AnalysisEducationTrading in 2035Picture trading in 2035: software drafts the decisions, markets stay open nearly all the time, and many assets settle in seconds. The human trader still has a role—supervising machines, choosing risk and deciding which opportunities deserve action.@Abe4 min read
AnalysisEducationThe Future of Trading TerminalsThe next trading terminal will begin with a request, not a menu. Charts, order tickets and news feeds will remain, but software will assemble them around what the trader wants to do. The terminal is becoming an assistant you brief.@Abe4 min read
AnalysisEducationQuantum Computing and Financial MarketsQuantum computing is already changing banks’ security priorities. Its effect on profitable trading strategies is likely to arrive later—and be smaller than the headlines imply. Encryption migration is a live project; most investment applications remain experiments.@Abe4 min read
AnalysisEducationWhat Happens When AIs Trade Against Other AIs?Machines have been trading against machines for more than a decade. The result is familiar: tighter spreads, fewer simple opportunities and failures that can unfold at extraordinary speed. Learning systems add a harder question—what happens when those machines adapt to one another?@Abe4 min read
AnalysisEducationAutonomous Trading AgentsA trading bot follows instructions. An autonomous agent chooses how to pursue a goal. The shift from “buy when the averages cross” to “grow this account within a 10 percent drawdown” changes both the software’s capabilities and the oversight it requires.@Abe4 min read
AnalysisEducationCan LLMs Understand Financial Markets?An LLM can read an earnings call brilliantly and still make a poor trade. Large language models are strong at interpreting what people say about markets; forecasting the next price move is a different task. Confusing the two is where much of the disappointment begins.@Abe4 min read
AnalysisEducationHuman Trader versus AI TraderA machine can watch thousands of markets without blinking. A human can recognise that the assumptions behind its signals have broken. Speed, breadth and consistency favour AI; context and unfamiliar situations still leave room for judgment. Your trading edge determines which strengths you need.@Abe3 min read
AnalysisEducationWill AI Replace Traders?AI is taking over the work traders do with their hands far faster than the work they do with their judgment. Execution and routine analysis are increasingly automated. Deciding what risks to take—and owning the consequences—remains a human responsibility.@Abe3 min read
ExplainerEducationThe First Trade in Human HistoryLong before coins, contracts or candlestick charts, volcanic glass was travelling across ancient landscapes. The first chapter in our trading story begins with a sharp edge and a question of trust.@Abe4 min readPage 3 of 5
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