OpenClaw can create a Goldman Sachs-level trading model in half an hour!

Quantitative researchers should start to feel anxious. In the past, this work corresponded to:
- Junior Quant: $180K/year
- Senior Researcher: $300K/year
- VP Quant Trader: $400K+/year
And now, you only need to copy prompt words and replace asset parameters (Asset)) to get a complete model framework, risk control logic, and backtesting structure.
No physics PhDs required, you can run Wall Street-level systems. The following 12 core prompts basically cover the functions of a complete quantitative team:
1) Time Series Forecasting Model
2) Mean Reversion Strategy
3) Sentiment Analysis Trading Model
4) Portfolio Optimization
5) Feature Engineering Pipeline
6) High-Frequency Microstructure Signals
7) VaR Risk Management Model
8) Option Pricing and Greeks
9) Pairs Trading Cointegration Model
10) Machine Learning Backtesting System
11) Reinforcement Learning Trading Agent
12) Multi-Factor Investment Model
Simply replicate the structure below and replace the content in brackets with any asset:
You are a Quantitative Researcher at [Top Wall Street Firm].
I need a complete [MODEL/STRATEGY TYPE] for [ASSET].
Please provide:
• Data preprocessing
• Feature engineering
• Model selection
• Training approach
• Performance metrics
• Backtesting framework
• Risk management
• Implementation pseudocode
Format as a quantitative research report.
Asset: [DESCRIBE ASSET, TIMEFRAME, DATA SOURCE]
The difference now is not whether there is a model. It’s who can turn ideas into strategies faster and turn strategies into profit curves.
Quant trading is shifting from an elite profession to prompt engineering.