- JPMorgan Chase, Goldman Sachs, and the three other largest US banks by trading revenue are collectively on pace for their best trading years in history, after a second-quarter earnings season that revealed record-shattering equity trading results across the board: Goldman posted $7.42 billion in Q2 equities revenue — its third consecutive all-time record for any bank — while JPMorgan’s equity traders posted $6.03 billion, an 86% year-over-year surge; combined, the five largest Wall Street trading desks generated more equity trading revenue in a single quarter than in most full calendar years from the pre-AI era.
- The trading boom is being driven by a confluence of factors that are simultaneously generating volume and volatility across asset classes: AI-driven market enthusiasm is producing massive equity inflows and record options activity as investors bet on technology beneficiaries; the Iran war is creating sustained commodity and rates volatility that benefits fixed-income trading desks; and overall market risk appetite has remained remarkably elevated — described by one senior banker as “clearly extremely risk-on” — despite the geopolitical backdrop, as equity markets have consistently treated volatility as a buying opportunity rather than a reason to de-risk.
- The trading revenue surge is particularly striking because it is occurring simultaneously with record investment banking fees: Goldman’s investment banking revenue hit $3.4 billion in Q2, its highest since 2021, while JPMorgan also reported record profits; the simultaneous boom in both trading and banking — categories that often run counter-cyclically — reflects an unusual environment where AI-driven capital formation (IPOs, equity raises, M&A) is generating banking fees at the same time as AI-driven market volatility is generating trading fees; the two cycles are feeding each other rather than competing.
- The historical context is striking: Wall Street’s five largest trading operations are generating revenue at a pace that would have been unimaginable five years ago, and the structural drivers — AI capital formation, geopolitical volatility, retail investor participation via options and ETFs, and the rise of quantitative strategies that generate continuous rebalancing activity — show no signs of abating; for the banks, the trading boom is also an efficiency story, as automation and AI-assisted risk management are allowing desks to handle dramatically higher volumes without proportional increases in headcount or infrastructure cost.
What Happened?
Q2 2026 earnings confirmed that Wall Street is in the midst of its best trading environment on record. JPMorgan and Goldman Sachs — the two dominant US trading franchises — both posted all-time equity trading records, with Goldman notching its third consecutive quarterly record and JPMorgan reporting an 86% year-over-year surge to $6.03 billion. The other three major US banks are posting similarly elevated results. The five firms combined are on pace to make more from trading in 2026 than in any prior year, driven by AI-related market activity and sustained geopolitical volatility.
Why It Matters?
The trading supercycle has significant implications beyond bank earnings. It reflects a market structure in which AI enthusiasm is generating continuous capital flows, rebalancing activity, and options demand that directly translates into bank revenue — meaning banks are among the most direct financial beneficiaries of the AI boom even without building a single AI product themselves. For investors, the durability of this trading cycle depends on whether AI market enthusiasm remains elevated and whether geopolitical volatility continues to drive rates and commodity trading; a sharp de-escalation in Iran or a significant AI market correction would hit trading revenues rapidly.
What’s Next?
Morgan Stanley reports next and will be the key peer comparison for Goldman given their similar franchise mix. Watch also for any signs of trading revenue normalization in Q3 guidance: bank executives have been careful not to project Q2 levels as a new baseline, citing the unusual confluence of AI enthusiasm and war-driven volatility; a return toward historical norms would still represent elevated revenues but would disappoint markets that may be pricing in a permanent step-change in bank earnings power.
Source: The Wall Street Journal
