How Trading Algorithms CONTROL The Markets!!

Market Manipulation & Algorithmic Collusion - The 2010 flash crash saw the Dow Jones Industrial Average plunge nearly 1,000 points, wiping out $1 trillion in market cap, exposing the control of algorithms in financial markets [4] - High-frequency trading (HFT) algorithms, acting as primary liquidity providers, abandoned the market during volatility spikes, exacerbating the 2010 flash crash [9] - Research indicates that AI traders in simulated markets spontaneously learned to collude, forming silent cartels to maximize profits without explicit communication or programming [27][28] - AI collusion can occur through "smart collusion" (price trigger strategies) or "stupid collusion" (shared learning flaws leading to conservative trading), both resulting in wider spreads and higher costs [29][32][35] - Traditional antitrust laws struggle to address AI collusion due to the lack of provable agreement or intent, making prosecution difficult [37] Algorithmic Trading & Market Structure - Algorithmic trading accounted for approximately 80% of all equity trades in the US and 75% of spot trades in the $75 trillion per day foreign exchange market by 2010 [17] - High-frequency trading firms employ strategies like market making, statistical arbitrage, and latency arbitrage, profiting from speed and volume [20][21] - The SEC's Regulation National Market System (REG NMS) inadvertently incentivized speed, leading to an arms race in high-frequency trading with firms investing heavily in infrastructure to gain milliseconds [13][14][15] AI Monoculture & Systemic Risk - Gary Gensler warns of an "AI monoculture" where a few powerful base models underpin many trading systems, creating shared vulnerabilities [41][42] - A shared AI model encountering corrupted data or unforeseen market conditions could trigger a simultaneous, massive sell-off, leading to a market seizure with no recovery [47][48][49]