Launching today
HeyTraders
Personal AI quant research & backtest with natural language
104 followers
Personal AI quant research & backtest with natural language
104 followers
HeyTraders is a Personal AI Quant for crypto markets that translates natural language into verifiable trading strategies. Stop trading based on gut feelings and complex charts. Just talk to our agent to research trends, verify ideas with instant backtesting, and get data-driven confidence.
HeyTraders
Hi Hunters! 👋 I’m Soonbeom, founder of HeyTraders.
The Story: I previously worked as a quantitative researcher at a crypto trading firm. Back then, I could focus on finding alpha because a dedicated engineering team handled the data and infrastructure.
But when I tried to trade my own strategies as an independent quant, I hit a wall. I spent 90% of my time building data pipelines and backtesting engines from scratch, and only 10% on actual trading. I realized: "Retail traders don't lack ideas. They lack the infrastructure."
The Solution: That’s why I built HeyTraders. It’s a Personal AI Quant that integrates research, backtesting, and validation into one conversation.
What you can do right now (MVP):
🔍 Ask Anything: "Why is Bitcoin moving today?" Our agent summarizes the key drivers.
📊 Verify Your Ideas: Just describe your strategy in plain English (e.g., "Buy ETH if RSI < 30"). We run the backtest and show you the win rate in seconds.
Roadmap (Coming Soon): 🚧 Automated Execution: Currently, we provide the trade signals and validation. Direct broker connection for auto-execution is our next priority.
📱 Mobile App: To receive real-time push notifications for the signals generated by your agent, download the app here
• iOS: https://apps.apple.com/app/id6754526355
• Android: https://play.google.com/store/apps/details?id=com.heytraders.mobile
Note: Your chat and strategies are fully encrypted and we never train on your data unless you opt-in.
I’d love your feedback: For those trading solo—what is the biggest pain point in trading crypto?
Thanks for checking us out! 🚀
HeyTraders
[UPDATE: 🚨 Live Support]
We are experiencing high traffic and shipping hotfixes in real-time! 👨💻
I'm fixing bugs as fast as possible.
If you encounter any issues, join our Live Telegram Channel for the fastest fix.
👉 Join here: https://t.me/heytradersofficial
Huge congrats on the launch! 🚀 Turning natural language into verifiable crypto quant strategies is a powerful unlock for serious traders on PH.
HeyTraders
@zeiki_yu Hey Zeiki, thanks! We believe serious traders should focus on finding Alpha, not fixing bugs. Hope this helps you save time!
instant backtesting is great, but slippage is the real killer in crypto. does the simulation engine account for exchange fees and liquidity, or is it just raw price data?
HeyTraders
@samet_sezer Thanks Samet, Great point. A backtest without friction costs is just a fantasy.
You are absolutely right. Here is how we handle it:
Currently: We set 5bps for exchange fees and an additional 5bps for slippage, but you can adjust these individually.
Roadmap: We are building a full "Real Market Mock" engine using orderbook snapshots. This will allow us to accurately simulate:
Fee Dynamics: Distinguishing between Taker Fees (Market Orders) and Maker Fees (Limit Orders).
Execution Logic: Calculating precise slippage based on order book depth vs. fill probability for limit orders.
Thanks for highlighting this—getting the simulation right is our top priority!
HeyTraders
Hey-Hunters! 👋 I'm Minseom, co-founder of HeyTraders.
While Soonbeom brings the quant expertise, I've been focused on making sure your data stays yours.
Here's our promise:
Your trading strategies are fully encrypted and stored securely.
We only use system data for stability improvements — never for training, never sold to third parties.
Your alpha stays your alpha.
We're just getting started, and your feedback means everything to us.
Try it out and let us know what you think — the good, the bad, all of it! 🙏
Wishing you all a great day ahead! 🌟
Interesting idea, would love to know if there will be a market for strategies later on, or even combo things together for better risk control
HeyTraders
@david_chen37 Thanks Siyuan, great ideas.
Marketplace: Yes, we envision an ecosystem where users can monetize proven alphas via a Marketplace and copy trading.
Combos: This is essential for risk management. We are planning a "Portfolio Backtest" feature to analyze correlations between strategies and see how they hedge each other.
Congrats for the launch. Curious if this is for short-term trading or long-term investing. Does it consider company fundamentals and news?
HeyTraders
@liang_tang Thanks for the question, Liang.
Fundamentals: Currently, we are crypto-first. While we don't parse company fundamentals like corporate balance sheets yet, we can handle market fundamentals (News, Narratives, Macro). We plan to expand to Stocks later and integrate company-specific data (Earnings, P/E).
Time Horizon: The AI is agnostic, but since Crypto has a relatively short history compared to Stocks, it is statistically difficult to validate multi-year investing strategies. Therefore, our current engine works best for short-to-mid-term horizons.
Product Hunt
HeyTraders
@curiouskitty This touches the core challenge of any quantitative analysis.
You are absolutely right. Many traders get tricked by perfect backtests. Here is how we handle those specific assumptions:
1. Handling the Assumptions
Fees & Slippage: We apply fees and slippages default to 5bps (0.05%) to be conservative, but this is fully configurable. We also plan to integrate Orderbook depth replay later for realistic impact simulation.
Execution (Bar-close): If a signal is generated based on bar-close data, we strictly execute at the Next Open. We never assume you can fill at the closing price of the signal candle.
Lookahead/Repainting: Our engine strictly enforces time-series separation. The strategy logic only sees data up to time T, making lookahead or repainting impossible by design.
2. How to Audit (Why you can trust the curve)
You can trust the backtest by trade history. On backtest detail page, you can click the chart to inspect every single trade entry/exit on the candle. You can visually verify exactly where the bot bought and sold relative to the price action.
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And more importantly, there are other major reasons why traders distrust AI Trading and backtesting. Here is how we address those specific fears:
Deterministic Protocol: LLMs are probabilistic, but trading must be precise. Our AI acts as a translator, not a creator. It converts your natural language logic into deterministic execution logic.
Trust Pipeline: We know backtesting is just a simulation and often fails in live markets. That is why we structured our flow as a verification pipeline: Backtest (Past check) → Live Signals (Real-time verification) → Automated Execution. We encourage you to verify the logic with Live Signals first. Only when you trust the real-time performance, should you enable automated execution.
Would love to hear your feedback on this approach!