US stock market analysis covering NASDAQ, NYSE and S&P 500
The spread between two stocks looked like a gift from the market gods. In 2019, two semiconductor companies traded with what appeared to be a near-perfect correlation of 0.94 over a rolling 90-day win
--- "Price is the effect. The order book is the cause." That aphorism circulates in quantitative trading circles for good reason. Every tick of price movement traces back to a visible or invisible tra
--- > "At 3:17 AM on a Tuesday, a memory leak in the order execution module caused the Python process to exit silently. By the time the trader checked the dashboard at 7:00 AM, three hours of opportun
--- The Number That Misled a Generation of Quants The number on the screen read 2.34. Your backtest showed a Sharpe ratio of 2.34 — exceptional by any standard. You ran the strategy for three years ac
On March 9, 2020, the New York Stock Exchange triggered market-wide circuit breakers for the first time since 1997. Trading in S&P 500 components halted for 15 minutes. When markets reopened, some sto
--- The Question Every Trader Should Ask Before Signing Up Two trading strategies are on the table. Strategy A returned 28% last year with a maximum drawdown of 20%. Strategy B also returned 28% last
"Volume is the only honest witness." The saying circulates in quant trading desks for good reason. Price can lie. Indicators can lag. But volume — the raw count of shares exchanged — tells you whether
--- Two strategies. Strategy A posts a Sharpe ratio of 2.1 over three years. Strategy B delivers 1.0. A rational allocator, guided by conventional wisdom, should prefer Strategy A. They should not. In
"Price is the effect. The order book is the cause." At 4:01 PM ET on August 5th, a semiconductor company's Q2 earnings crossed the wire. Revenue beat consensus by 12%. The headline number looked like
The number hit the wire at 8:30 AM ET. 287,000 jobs added in January — well above the 180,000 consensus estimate. EURUSD dropped 87 pips in 11 seconds. This is not an anomaly. It is the predictable co
--- The Model That Worked—Until It Didn't A quantitative researcher spent three months building a stock price prediction model. The model used a feature derived from commodity futures data. In-sample
--- "Three. Two. One." In the trading room where I spent my first year as a quant developer, that countdown was never about a rocket launch. It was about the 8:30 AM ET press release that moves curren
--- The 3 AM Realization At 3:17 AM on a Tuesday, alone in a room illuminated by three monitors and the glow of a Jupyter notebook, a trader watched their mean-reversion strategy trigger its 47th cons
--- The Backtest That Lied to You Imagine you built a mean-reversion strategy on a US-listed stock that went through a trading halt in 2019. Your backtest shows a Sharpe ratio of 2.1. You run it live.
--- The closing bell rings at 4:00 PM ET. Most traders close their terminals and head home. Inside a professional quantitative shop, a different clock starts ticking. Between 4:00 PM and 5:30 PM, a we
--- "Show me a quant fund that isn't thinking seriously about large language models right now, and I'll show you a fund with a retention problem." That assessment comes from a quantitative researcher
--- The Number That Broke My Backtest At 09:30:00.123 ET on March 15, 2024, Apple Inc. (AAPL) printed 47 trades on the Consolidated Tape. Your tick aggregation logic counted those trades and produced
--- "Eight thirty. The number hits the wire." At that moment, a single data print worth billions of dollars in expected labor market revisions tears through currency markets. EURUSD — the most liquid
Every trader has experienced this moment. You identify a stock that should rally. You place your order. The price moves against you before you can blink. You get filled — but at a worse price than you
"Two roads diverged in a wood, and I — I took the one less traveled by, and that has made all the difference." Robert Frost wrote that. Quant researchers rarely get such a clean choice. When you run a