I will provide cleaned and verified es tick data
Quantitative Architect Financial Data Engineer Algorithmic Trading Specialis
About this Gig
Stop gambling with "dirty" data that ruins your backtesting.
In quantitative trading, your strategy is only as good as the data. Generic datasets often have gaps and duplicates that create false signals. I provide verified ES (S&P 500) Futures tick data, meticulously processed for professional-grade analysis.
I deliver a high-fidelity financial dataset optimized for high-performance trading.
Why this ES dataset is superior:
- Zero-Gap Policy: Verified RTH and ETH sessions.
- Deduplicated: My protocol removes bad prints and timestamp errors.
- Format Options: High-speed Parquet (for Python/Quants) or CSV.
- Platform Ready: Formatted for Sierra Chart, Python, or NinjaTrader.
>>> LAUNCH OFFER <<< I am accepting my first 3 projects at a discounted price while I build my profile. Get institutional-grade data at a lower entry cost. Once these 3 slots are filled, pricing returns to standard rates.
What is included:
- Price (Bid/Ask/Last) and Volume for every tick.
- Precise millisecond/microsecond timestamps.
- Cleaned and organized data structure.
Please message me before ordering to discuss specific years and roll logic. Lets build your strategy on a solid foundation.
My Portfolio
FAQ
In what format will I receive the ES data?
I provide data in high-speed Parquet format (highly recommended for Python/Pandas and quantitative analysis) or standard CSV. If you need a specific structure for your database, just let me know.
Does the dataset include overnight sessions (ETH)?
Yes. By default, I provide the full 24/5 session (both RTH and ETH). However, if your strategy only requires Regular Trading Hours (RTH), I can provide a filtered version at no extra cost.
Is the data compatible with Sierra Chart or NinjaTrader?
Absolutely. I can format the files to be natively compatible with Sierra Chart, NinjaTrader, or custom Python backtesting engines. Please specify your platform when ordering.
How do you ensure there are no gaps or bad prints?
I apply a Zero-Gap Policy. Every dataset undergoes a custom verification protocol that identifies and fixes missing ticks, removes duplicates, and filters out "bad prints" (out-of-range prices) to ensure your backtesting is 100% accurate.
How is the contract roll-over handled?
I use standard futures roll-logic based on volume/open interest transitions to provide a continuous backtesting string. If you have a specific custom roll preference, please message me to discuss it.

