Multivariate Probabilistic Forecasting of Electricity Prices With Trading Applications
“LASSO Quantile Regression is better in terms if statistical evaluation of distributional fit, while DMLP outperforms in terms of Sharpe ratio (by 18%) in the trading application.”
StrategyMachine learning
TechniqueRecurrent neural networkfeedforward network
GeographyUK
ClaimSharpe ratioexcess return
Also stated: Long-short
Missing from abstract: benchmark, out-of-sample test, costs, multiple testing, universe
Institutional-grade audit of this strategy.
£5 — Request the audit- Audit of the paper claims accounting for costs, luck, crises, originality, geography, etc.
- Reproduction code integratable into Bloomberg, IBKR, etc.
- Bias-free datasets for backtesting included
- Delivered in 2 working days
The paper's neighbourhoodMachine learning return prediction by year
The family is counted across the whole universe. Asset, method and authors are counted inside the family.
| Similar papers | citation | same method | same asset | same authors | |
|---|---|---|---|---|---|
| Spatiotemporal Signals in Residuals: A Two-Stage Boosting Graph Neural Network for Stock Return Prediction by Liu et al. | 2026 | ||||
| Machine Learning for Cross-Sectional Return Prediction: A Comparative Study of US and Indian Equities by Khatu | 2026 | ||||
| Empirical Asset Pricing via Machine Learning: Evidence from Indian Equity Markets by Sharma | 2026 | ||||
| Stock Return Prediction Guided by a Revised Random Walk Hypothesis: Adaptive Information Smoothing and Signed Correlation-Aware TimeMixing by Seo and Yang | 2026 | ||||
| Visualizing Income Statements by Garfinkel et al. | 2026 |