In a previous article Building and Testing Trend-Following Strategies on One-Minute SPY Data, we investigated whether retail activity indicators derived from one-minute SPY data could be used to construct profitable trend-following strategies. The results suggested that we are able to construct strategies that are often able to achieve superior risk-adjusted performance. In this article, we examine an alternative hypothesis. Instead of assuming that changes in retail activity signal the continuation of an existing trend, we investigate whether persistent declines in order flow may create conditions for a subsequent market reversal. More specifically, we analyze situations in which selected trading activity indicators decrease for several consecutive trading days and evaluate whether such sequences are followed by above-average SPY returns.

Intraday trading strategies have gained increasing attention as advances in computing power and market data availability have made intraday strategy analysis more accessible. While many trading strategies are traditionally developed and evaluated using daily price data, shorter timeframes can provide additional opportunities to identify and exploit market trends within a single trading session. In this article, we investigate the performance of trend-following strategies based on selected technical indicators computed from one-minute price data for SPY ETF. The historical dataset, provided by Algoseek, serves as the basis for designing, backtesting, and comparing several intraday trading approaches.

Holidays put people in motion. In the days surrounding major U.S. holidays, airports become busier as travelers visit their families or take advantage of extended weekends. Financial markets themselves are known to display a holiday-related seasonality. In our previous research on the Pre-Holiday Effect in Commodities, we identified a short-term price drift in crude oil and gasoline before major U.S. holidays. Increased travel and the associated expectation of higher fuel consumption offered one possible explanation. This naturally raises another question: if holiday travel leaves a seasonal footprint in energy markets, can it also be detected in the stocks of the airlines transporting those travelers? To investigate this possibility, we analyze the performance of the U.S. Global Jets ETF (JETS) around major U.S. holidays. We first examine its daily returns from ten trading days before to ten trading days after each holiday and use the resulting return profile to identify the strongest seasonal windows. We then formulate two directional JETS strategies and a JETS–USO strategy.

The explosive growth of hyper-liquid 0-DTE markets has pushed traditional options pricing infrastructure to its breaking point, as continuous Black-Scholes calculus can collapse into an unusable point mass at expiration. Rather than patching a broken formula with hand-fitted tweaks, a new paper suggests dismantling legacy math by replacing continuous geometric Brownian motion with a discrete, order-book-driven structural layer. Instead of smoothing over intraday price action, this model captures the raw physical reality of high-frequency liquidity by deriving a closed-form framework where the implied volatility surface is built directly from actual market microstructure.

Hello all,

– new report in the Live Strategies section called Composite Analysis
– 11 new Quantpedia Premium strategies
– 5 new related research papers
– 8 new backtests
– and finally, 5 new posts on our Quantpedia blog

The integration of artificial intelligence into algorithmic trading has ignited a race to transform generative text into systematic alpha. A new paper written by Steven Edwards empirically investigates whether constructing a synthetic consensus using large language models can simulate information aggregation dynamics or if it merely acts as a sophisticated echo chamber. By utilizing an expansive framework to evaluate portfolio construction across distinct synthetic mandates, the study challenges whether generative agents can truly democratize the wisdom of crowds within highly efficient capital markets.