algo-electricity-trading
Unverified ML strategy on Multi by anthonymakarewicz. BotFinder score 18 out of 100.
Intraday algorithmic trading on the German electricity market
Source: github
BotFinder analysis pending.
algo-electricity-trading
Algorithmic Trading on German Electricity Markets Project Overview This project leverages ensemble tree based machine learning models to predict the direction of the spread (imbalance vs. day-ahead prices) in the German Electricity Market, with the goal of maximizing cumulative Profit & Loss (P&L). The dataset consists of 15-minute interval observations with the primary features being: - Wind generation forecasts - Impact supply variability from renewable sources. - Solar generation forecasts - Capture solar energy’s contribution to the electricity grid. - Load (demand) forecasts - Reflect consumer demand patterns that influence electricity prices. Motivation The spread reflects the dynamics of electricity supply and demand: - When supply exceeds demand, imbalance prices tend to decrease to account for the excess. - When demand surpasses supply, imbalance prices generally increase. By modeling these relationships, the project aims to develop a systematic trading strategy to exploit these price differences. Instructions Clone the repository: Usage 1. Exploratory Data Analysis (EDA) No
⚠ No verified equity curve — no track-record source connected.
Drawdown profile
Data unavailable — contact the owner.
Verification ledger
How the score has moved
Recalculated at each data collection. Transparency means showing the bad weeks too.
No score history is stored yet — only the current score is shown.
Reviews & comments
No reviews collected from the source yet.
⚠ No live verification account connected — ask for proof before buying.
Alerts on changes: coming soon
Prop-firm compatibility not provided.
Open-source maintainer on GitHub.
Data-completeness & trust index (not a profitability rating)