3 papers
q-fin.TR2026
Sequential Structure in Intraday Futures Data: LSTM vs Gradient Boosting on MNQ
Mathias Mesfin
This paper compares gradient boosting and long short-term memory (LSTM) architectures for intraday directional prediction in Micro E-Mini Nasdaq 100 futures (MNQ). Motivated by rec…
q-fin.TR2026
A Validated Volatility-Volume-Gap Classifier for Regime Identification in MNQ Intraday Data
Mathias Mesfin
This paper builds and tests a day-classification system for MNQ (Micro E-Mini Nasdaq 100) futures based on three simultaneously elevated pre-market conditions: absolute overnight g…
q-fin.TR2026
Structural Limits of OHLCV-Based Intraday Momentum Signals in MNQ Futures: A Systematic Falsification Study
Mathias Mesfin
This paper tests whether common intraday momentum signals built from OHLCV data generate a tradable edge in Micro E-Mini Nasdaq 100 (MNQ) futures after realistic execution costs. F…