progrunners.comenergy & technology
progrunners  ·  Trading dashboards · Market data integration · Software development

Energy trading software and market data for companies that trade electricity.

progrunners — energy & technology. We combine intraday and balancing market knowledge with engineering: live market feeds, dashboards, quantitative analysis. Where most traders wait on IT and most developers don't understand the market, we do both.

Intraday vs Day-ahead · CZ · live demo LIVE
Intraday last Day-ahead spot
ID
live order book
AMQP
direct OTE feed
~1s
data latency
2
markets: ID + DA
What we do

Domain knowledge you can't code over a weekend

We work on the Czech balancing market and understand how its pieces fit together — from the day-ahead market through intraday to regulation energy and system imbalance. This knowledge is rarer than coding: companies hire developers easily, but a team that understands the market and can build their own tools is hard to find.

ID intraday DT day-ahead aFRR regulation energy OTE market participant ČEPS system imbalance ENTSO-E forecast / generation
Projects

What we build

We run these electricity market systems ourselves on the Czech market. The same building blocks — live data feeds, order book reconstruction, dashboards, backtesting — are what we build for clients on any European market.

CEPS Live live

Real-time balancing market dashboard · designed and built in-house

Aggregates live data from ČEPS, OTE and ENTSO-E in one place: system imbalance, regulation energy prices, renewable generation and forecast, day-ahead and intraday prices. A Python backend translates REST into SOAP/AMQP calls; the frontend renders with auto-refresh.

  • Custom fast XLSX parser (30–50× faster than openpyxl) via direct ZIP + iterparse
  • ENTSO-E integration (forecast A69, generation A75) and regelleistung.net (aFRR bids)
  • Stale-while-revalidate caching, cloud keepalive, API failure handling
Pythonhttp.serverSOAPRESTRenderJS / Canvas

Intraday Order Book Bridge live

Bridge from OTE AMQP to a live order book · in-house

Connects to OTE's official AMQP interface via certificate, receiving the live intraday (XBID) order book. The client reconstructs the full book from delta messages like a professional trading terminal, computing best bid/ask, VWAP and the intraday-vs-day-ahead spread for every hour and quarter-hour.

  • TLS with client certificate, AMQP login/subscribe workflow per OTE spec
  • Incremental order book reconstruction from deltas (ordrId tracking, cancel handling)
  • Long/short intraday-vs-day-ahead spread signals for arbitrage screening
Pythonpika / AMQPTLS / x509gzipRabbitMQ

Quantitative analysis & backtesting

Trading strategy research

Hypothesis testing on historical data: correlation of German renewable forecast error with Czech regulation-energy price (forecast-error analysis, Pearson, lag analysis), and technical-strategy backtests with emphasis on realistic assumptions — fees, slippage, walk-forward.

  • Focus on rigor: we distinguish a descriptive relationship from a tradeable edge
  • Interactive result dashboards (scatter, correlation, equity curves)
PythonJavaScriptSVG / Canvasstatistika

Crypto trading & bots

Algorithmic strategies and backtesting

Systematic testing of trading strategies on crypto futures (perpetuals): technical indicators, trailing/fixed exits, money management. Emphasis on realistic modeling — taker/maker fees, slippage, walk-forward — instead of over-optimistic curves.

  • Backtest engine with visual dashboards (metrics, year-by-year, equity/P&L)
  • Building custom technical indicators and testing them against standard ones
  • Testnet paper trading before deployment, maker-only logic to save fees
PythonReactBybit APITradingView / Pinebacktesting
Skills

Market × engineering

Energy markets

Intraday, day-ahead, regulation energy, system imbalance, BRP mechanics, market coupling, OTE/ČEPS processes.

Market data

OTE AMQP, ENTSO-E Transparency, ČEPS SOAP, regelleistung.net, energy-charts. Order book, forecast, generation.

Engineering

Python (backend, parsing, AMQP/SOAP/REST), JavaScript, data visualization, cloud deployment, Git.

Analysis

Correlation and lag analysis, backtesting with realistic assumptions, hypothesis testing, critical view of my own results.

How we work: We build tools we actually use for market decisions, so they reach real deployment, not a drawer. We're skeptical of our own results — we'd rather have a small verified edge than a pretty chart with no proof.
Tools & more
Python dev Web development Excel advanced TradingView / Pine Script Technical analysis Custom indicators GitHub Render AI-assisted dev Claude GPT Gemini Grok Copilot Crypto trading Crypto bots / automation EN fluent
Data sources

Where we get our data

Our dashboards and strategies are built on real market and meteorological data from verified sources — no simulated data, no placeholders. Below is the full range each interface provides.

OTE-ČR
DA spot (hourly & 15min) Intraday order book (AMQP / XBID) Intraday trades, last, VWAPID trades, last, VWAP Best bid / ask, spread DA block price DA auction results Imbalance settlement Gas market DA / ID Guarantees of origin
ČEPS (SOAP)
System imbalance (per minute) aFRR+ / aFRR− activation mFRR+ / mFRR− / mFRR5 Reg. energy price (aFRR/mFRR) Estimated imbalance price RES output wind + solar (min) System load Cross-border flow balance Unit output / reserves FCR / aFRR / mFRR reservation
ENTSO-E Transparency
Actual generation per type (A75) Wind / solar forecast (A69) Total load + forecast (A65) Residual load (CZ / DE) Day-ahead prices (A44) Cross-border flows (A11) Offered capacity NTC / ATC Planned unit outages Installed capacity per type Balancing reserves
netztransparenz.de
NRV balance DE (15min) NRV balance per minute Activated aFRR / mFRR AEP imbalance price estimate reBAP imbalance price TrafficLight signal RZ balance per TSO Spotmarktpreise OZE Hochrechnung wind/solar
SMARD (Bundesnetzagentur)
DE residual load actual Generation by source (15min) Consumption / load Import / export balance Wholesale prices
MetDesk MAGMA
Wind forecast (Power Gen V2) Solar forecast (Power Gen V2) CZ / DE / AT / HU / NL 15min step, ensemble model Temperature / wind / cloud
regelleistung.net
aFRR energy bids DE + AT mFRR energy bids Merit-order ladder (POS/NEG) Price for 200 / 500 / 1000 MW Capacity auction results Per QH slot
EU Power Prices
DE price forecast (16 days) Hourly XGBoost model Multiple market zones
Energy-Charts (Fraunhofer ISE)
DE generation mix Historical spot data Emission factors Public power / load
Technical guide
The ENTSO-E API, as it actually behaves

Tell us what you need

A dashboard, a market data integration, backtesting — or just a question about one of the APIs. We reply within 24 hours.

By sending you agree to your data being processed as described in our privacy policy.

Or directly: info@progrunners.com · +420 776 718 774

Everything on this site

Live data, a guide to each market, and what we build for companies. The guides cover where market data actually comes from in each country — which interfaces, which formats, and where it hurts.

Live tools
Prices by country
Market guides
progrunners
DE · CS