u/AardvarkOrganic372

I’m building Alpha Builders, a no-code backtesting tool for retail investors.

Most investors have market hunches, but very few test them properly.

Examples:

• “Stocks that drop 20% tend to bounce.”
• “Low-volatility names outperform long term.”
• “Small caps beat large caps after rate cuts.”

Today, testing these ideas usually means writing Python, using expensive platforms, or trusting someone else’s cherry-picked backtest.

Alpha Builders lets users describe an investing idea in plain English, turn it into a factor or rule, and backtest it on historical US stock data.

Current version:

• S&P 500 + Russell 2000
• 12 years of daily data
• 77 built-in factors
• AI-assisted factor creation
• visual custom factor builder
• no-code workflow

What I need roasted:

• Is this a real pain point or just a nice-to-have?
• Is “AI + backtesting” a red flag?
• What would make this product credible?

Please be direct. I’m trying to figure out whether this is worth pushing further or whether the positioning needs a major change.

alphabuildersus.com

Hey everyone — I’m looking for a few beta users to test something I’ve been building.

It’s a no-code backtesting tool for retail investors who have market hypotheses but don’t know Python or don’t want to use complicated quant platforms.

The basic idea is simple:

A lot of investors have thoughts like:

- “Do stocks that drop sharply tend to bounce?”

- “Do low-volatility stocks outperform over time?”

- “Do small caps behave differently after rate cuts?”

But most people never actually test these ideas. They either rely on intuition, random screenshots online, or tools that are too technical for them.

I’m building Alpha Builders to make that process easier. Users can describe a stock-market idea in plain English, turn it into a factor or rule, and backtest it on historical US stock data.

I’m not looking for praise — I’m specifically looking for feedback on:

1. Is the workflow clear for someone who doesn’t code?

2. Does the AI-generated factor logic make sense?

3. Do the backtest results feel understandable and credible?

4. What would make you trust or distrust a tool like this?

5. Is this actually useful, or does it sound better in theory than in practice?

The current version supports S&P 500 and Russell 2000 stocks with 12 years of daily data.

If you’re interested in testing it, I’d really appreciate honest feedback, especially from people who invest, trade, or have tried to backtest ideas before.

alphabuildersus.com