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 asks whether a small set of observable pre-market characteristics can identify trading days with systematically different intraday behavior in Micro E-Mini Nasdaq-100 (M…
q-fin.TR2026
Structural Limits of OHLCV-Based Intraday Signals in MNQ Futures: A Systematic Falsification Study
Mathias Mesfin
This paper asks a straightforward question: do common intraday momentum signals built from price and volume data produce a tradable edge in Micro E-Mini Nasdaq 100 (MNQ) futures on…